JP6988853B2 - Buried object detection device and buried object detection method - Google Patents

Description

The present invention relates to a buried object detecting device and a buried object detecting method.

As a device for searching for buried objects in concrete, a buried object detecting device for detecting buried objects from reflected waves of electromagnetic waves radiated toward concrete while moving the surface of concrete is used (for example, Patent Document 1). reference).
In such a buried object detection device, the position of the buried object is displayed on the display screen when the operator manually moves the surface of the concrete.

Japanese Unexamined Patent Publication No. 5-142344

However, there is a restriction that the algorithm for identifying the buried object must be completed by acquiring the reflected wave information for each scan, and the scanning time varies from person to person in the operating speed of the user. Therefore, when the moving speed is high, the process of identifying the buried object may not be in time and the process may be thinned out.
An object of the present invention is to provide a buried object detecting device and a buried object detecting method capable of accurately detecting a buried object even when the moving speed is high.

The buried object detection device according to the first invention detects buried objects in an object by using data on reflected waves of electromagnetic waves radiated toward the object while moving on the surface of the object. The apparatus includes a detection unit, a scanning state acquisition unit, and a processing division unit. The detection unit detects the timing of electromagnetic wave radiation for each predetermined moving distance. The scanning state acquisition unit acquires information on the moving speed during scanning depending on the timing. When the movement speed predicted based on the information on the movement speed is faster than a predetermined value, the processing division unit performs a plurality of processes for detecting the buried object performed on the data on the reflected wave acquired at each timing. Is divided and pipeline processing is performed.

In this way, if the moving speed is faster than the predetermined value, it is possible that the process for identifying the buried object will not be completed by the next timing. Therefore, by performing the pipeline process, the buried object will be processed. The buried object can be detected with high accuracy without thinning out the process for detecting.
Further, by performing the pipeline processing, even if the processing for identifying the buried object is not completed during the timing, the processing can be completed as quickly as possible without thinning out the processing.

The buried object detecting device according to the second invention is the buried object detecting device according to the first invention, and the scanning state acquisition unit acquires the time of the timing interval as information regarding the moving speed. The processing division unit performs pipeline processing when the predicted time predicted from the time of the timing interval is smaller than a predetermined value.
As a result, the interval until the next timing can be predicted by the timing interval, and it is possible to determine whether or not to perform the pipeline processing based on the predicted time.

The buried object detecting device according to the third invention is the buried object detecting device according to the first or second invention, and the processing dividing unit increases the number of processing to be divided as the moving speed is faster. ..
This makes it possible to change the number of divisions when performing pipeline processing according to the speed.
The buried object detection device according to the fourth invention is the buried object detection device according to any one of the first to third inventions, and the processing division unit divides the memory and burys it according to the number of the divided memories. Pipeline processing is performed by dividing the processing for detecting objects.
As a result, pipeline processing can be performed on the divided memory.

The buried object detection device according to the fifth invention is the buried object detection device according to any one of the first to fourth inventions, and includes a reflected wave acquisition unit, a reflected wave analysis unit, and a buried object determination unit. Further prepare. The reflected wave acquisition unit acquires data on the reflected wave of the electromagnetic wave radiated at each timing. The reflected wave analysis unit detects the peak of the signal intensity in the depth direction of the object at each timing based on the signal intensity in the depth direction of the object in the data regarding the reflected wave obtained at each timing. The buried object determination unit determines the presence or absence of the buried object based on the peak of the signal strength. When performing pipeline processing, the processing division unit divides the processing by the reflected wave acquisition unit, the processing by the reflected wave analysis unit, and the processing by the buried object determination unit into at least two or more.
As a result, the processing division unit can perform pipeline processing for processing by the reflected wave acquisition unit, processing by the reflected wave analysis unit, and processing by the buried object determination unit.

The buried object detecting device according to the sixth invention is the buried object detecting device according to the fifth invention, and further includes a buried object registration unit. The buried object registration unit registers the position of the determined buried object. When performing pipeline processing, the processing division unit divides the processing by the reflected wave acquisition unit, the processing by the reflected wave analysis unit, the processing by the buried object determination unit, and the processing by the buried object registration unit into at least two or more.
As a result, the processing division unit can perform pipeline processing for processing by the reflected wave acquisition unit, processing by the reflected wave analysis unit, processing by the buried object determination unit, and processing by the buried object registration unit.

The buried object detecting device according to the seventh invention is the buried object detecting device according to the sixth invention, and includes a first control module and a second control module. The first control module has a reflected wave acquisition unit and a transmission unit that transmits data related to the acquired reflected wave. The second control module has a reflected wave analysis unit, a buried object determination unit, a buried object registration unit, and a receiving unit for receiving data related to the reflected wave. When performing pipeline processing, the processing division unit performs at least two or more processes by the reflected wave acquisition unit, processing by the reflected wave analysis unit, processing by the buried object determination unit, processing by the buried object registration unit, and processing by the transmission unit. Divide into.
As a result, the processing division unit performs pipeline processing for processing by the reflected wave acquisition unit, processing by the reflected wave analysis unit, processing by the buried object determination unit, processing by the buried object registration unit, and processing by the transmission unit. Can be done.

The buried object detection method according to the eighth aspect of the invention is for detecting buried objects in the object by using data on reflected waves of electromagnetic waves radiated toward the object while moving on the surface of the object. The method includes a detection step, a scanning state acquisition step, and a processing division step. The detection step detects the timing of electromagnetic wave radiation for each predetermined travel distance. The scanning state acquisition step acquires information on the moving speed during scanning depending on the timing. The processing division step is a plurality of processes for detecting buried objects performed on the data on the reflected wave acquired at each timing when the movement speed predicted based on the information on the movement speed is faster than a predetermined value. Is divided and pipeline processing is performed.

In this way, if the moving speed is faster than the predetermined value, it is possible that the process for identifying the buried object will not be completed by the next timing. Therefore, by performing the pipeline process, the buried object will be processed. The buried object can be detected with high accuracy without thinning out the process for detecting.
Further, by performing the pipeline processing, even if the processing for identifying the buried object is not completed during the timing, the processing can be completed as quickly as possible without thinning out the processing.

INDUSTRIAL APPLICABILITY According to the present invention, it is possible to provide a buried object detecting device and a buried object detecting method capable of accurately detecting a buried object even when the moving speed is high.

The perspective view which shows the structure of the buried object detection apparatus in embodiment which concerns on this invention. The block diagram which shows the structure of the buried object detection apparatus of FIG. The block diagram which shows the structure of the pulse control module of FIG. The block diagram which shows the structure of the 1st control part of FIG. 3A. The figure which shows the data of the reflected wave acquired by the MPU of FIG. The figure which shows the table for demonstrating the acquisition of the predicted processing time. The block diagram which shows the structure of the main control module of FIG. The block diagram which shows the structure of the reflected wave analysis part of FIG. 6A. The block diagram which shows the structure of the buried object determination part of FIG. 6A. (A) A diagram showing image data before the difference processing, and (b) a diagram showing the image data after the difference processing. (A) A diagram showing image data after performing moving average processing, and (b) a diagram showing signal strength of RF data of line L1 in FIG. 10 (a). An enlarged view between P10 and P3 in FIG. 7 (b). FIG. 5 is a diagram for explaining processing by the first derivative processing unit and the chattering removal unit of FIG. The figure which shows the image data. (A)-(d) The figure for demonstrating the processing by a grouping part. (A) A diagram showing the depth positions of a plurality of peaks grouped by the grouping portion of FIG. 5, and (b) a diagram of differentiating the waveform of FIG. 18 (a). (A) The figure which added the 2nd condition to FIG. 18 (a). (B) The figure which added the 2nd condition to FIG. 18 (b). (A) A diagram showing an example in which the shaded portion of the differentiated graph is equal to or more than a predetermined threshold value, and (b) a diagram showing an example in which the shaded portion of the differentiated graph is less than a predetermined threshold value. (A)-(c) The figure which shows the example of the vertex grouping. (A)-(c) The figure for demonstrating pipeline processing. The figure which shows the pipeline processing when the number of processing divisions becomes three. The figure which shows the pipeline processing when the scanning speed by an operator becomes slow from the middle, and the number of processing divisions is reduced from 5 to 3. The figure which shows the pipeline processing when the scanning speed by an operator becomes high from the middle, and the number of processing divisions increased from 3 to 5. The figure which shows the pipeline processing when the scanning speed by an operator changes, and the number of processing divisions changes to 5, 5, 5, 3, 5, 3, 5, 3, 5, 3. The flow chart which shows the buried object exploration process of the buried object detection apparatus of this embodiment. FIG. 2 is a flow chart showing a scanning state detection process of FIG. 22. FIG. 2 is a flow chart showing a process division number determination process of FIG. 22. FIG. 2 is a flow chart showing a scanning result acquisition process of FIG. 22. The flow chart which shows the reflected wave acquisition process of FIG. The flow diagram which shows the reflected wave / processing division number transmission processing of FIG. FIG. 2 is a flow chart showing a buried object detection process of FIG. 22. The flow chart which shows the reflected wave analysis processing of FIG. 28. The flow chart which shows the moving average processing of FIG. The flow diagram which shows the difference processing of FIG. 29. FIG. 9 is a flow chart showing the first derivative processing of the difference result of FIG. 29. FIG. 9 is a flow chart showing a chattering removal process of FIG. 29. The flow chart which shows the peak detection process of FIG. 29. FIG. 9 is a flow chart showing a buried object determination process of FIG. 29. The flow chart which shows the grouping process of FIG. 35. FIG. 3 is a flow chart showing a buried object determination process of FIG. 35. The flow chart which shows the chevron waveform vertex detection process of FIG. 35. FIG. 3 is a flow chart showing a buried object determination process of FIG. 35.

Hereinafter, the buried object detection device according to the embodiment of the present invention will be described with reference to the drawings.
<Structure>
(Outline of buried object detection device 1)
FIG. 1 is a perspective view showing a state in which the buried object detection device 1 according to the embodiment of the present invention is arranged on the concrete 100. FIG. 2 is a block diagram showing a schematic configuration of the buried object detection device 1 according to the present embodiment.

The buried object detection device 1 of the present embodiment radiates an electromagnetic wave to the concrete 100 while moving on the surface 100a of an object such as the concrete 100, and receives and analyzes the reflected wave to bury the object in the concrete 100. The positions of objects 101a, 101b, 101c, and 101d are detected.
In FIG. 1, the buried objects 101a, 101b, 101c, and 101d are reinforcing bars, and are, for example, buried at depths of 20 cm, 15 cm, 10 cm, and 5 cm in order from the surface 100a. The moving direction is indicated by arrows A1 and A2, the depth direction is indicated by arrow B, and the surface direction is indicated by arrow C.

The buried object detection device 1 includes a main body 2, a handle 3, a wheel 4, an impulse control module 5 (an example of a first control module), a main control module 6 (an example of a second control module), and an encoder 7. It has (an example of a detection unit), a display unit 8, and a memory 9.
A handle 3 is provided on the upper surface of the main body 2. Four wheels are rotatably attached to the lower part of the main body 2. When detecting the buried object inside the concrete 100, the operator moves the buried object detecting device 1 on the surface 100a of the concrete 100 while grasping the handle 3 and rotating the wheel 4.

The impulse control module 5 controls the timing of radiating an electromagnetic wave toward the concrete 100, the timing of receiving the reflected wave of the radiated electromagnetic wave, and the like.
The encoder 7 is provided on the wheel 4, and transmits a signal for controlling the reception timing of the reflected wave to the impulse control module 5 based on the rotation of the wheel 4.
The main control module 6 receives data on the reflected wave received by the impulse control module 5 and detects the buried object.

The display unit 8 is provided on the upper surface of the main body unit 2 and displays an image showing the positions of the buried objects 101a, 101b, 101c, and 101d.
The memory 9 is expanded when the main control module 6 and the impulse control module 5 execute the program. Further, the memory 9 is divided according to the scanning speed of the buried object detection device 1, and pipeline processing is performed in the divided area.

(Impulse control module 5)
FIG. 3A is a block diagram showing the configuration of the impulse control module 5.
The impulse control module 5 includes a first control unit 10, a transmitting antenna 11, a receiving antenna 12, a pulse generating unit 13, a delay unit 14, a gate unit 15, and a storage unit 16. FIG. 3B is a block diagram showing the configuration of the first control unit 10.

The first control unit 10 is composed of an MPU (Micro Processing Unit) or the like, and commands the pulse generation unit 13 to generate a pulse by using an encoder input as a trigger. The pulse generation unit 13 generates a pulse based on a command from the MPU and sends it to the transmission antenna 11. The transmitting antenna 11 radiates an electromagnetic wave at a fixed cycle based on the pulse cycle. The input timing of the encoder 7 corresponds to an example of timing. Further, the first control unit 10 expands and executes the program stored in the storage unit 17 on the memory 9 (see FIG. 2). The details of the first control unit 10 will be described later.

The receiving antenna 12 receives the reflected wave of the radiated electromagnetic wave. When the gate unit 15 receives the pulse from the delay unit 14, the gate unit 15 takes in the reflected wave received by the receiving antenna 12 and transmits it to the first control unit 10. The delay unit 14 transmits a pulse to the gate unit 15 at predetermined intervals to capture the reflected wave. This predetermined interval is, for example, a 2.5 mm pitch.
As a result, the impulse control module 5 outputs electromagnetic waves from the transmitting antenna 11 a plurality of times, using the input from the encoder 7 as a trigger. Then, the impulse control module 5 can acquire the reception data for each distance from the reception antenna 12 by delaying the reception timing by using the delay IC by the delay unit 14.

FIG. 4 is a diagram showing data of reflected waves acquired by the MPU. The vertical axis indicates the intensity of the received signal in a gradation of −4096 to +4096 with the axis O as the center, and the arrow direction indicates the negative side. The horizontal axis indicates the distance from the receiving antenna 12, and the arrow direction (corresponding to the depth direction B) indicates that the distance from the receiving antenna 12 is long. Further, a long distance corresponds to a deep depth.

Although the details will be described later, since the waveform W1 shown in FIG. 4 includes the reflected wave reflected by the antenna without being irradiated in the concrete 100 (p1 etc.), the difference from the signal strength of the reference value is calculated. By doing so, the change in the data of the reflected wave from the inside of the concrete 100 is extracted.
Further, the data shown in FIG. 4 is data from the time when the input of the encoder 7 is input to the time when the input of the encoder 7 is next. By gradually delaying the reception timing, the reflected wave is received from a position that is a long distance from the receiving antenna 12, but if there is an input from the encoder 7, the delay in the reception timing is restored and the reception timing is reset again. Gradually delay. That is, the reflected wave in the depth direction B at the predetermined measurement position in the moving direction A (the position where the input from the encoder 7 is received) is received. The reflected wave data from the input of the encoder 7 shown in FIG. 4 to the input of the next encoder is referred to as data for one line. The first control unit 10 transmits RF (Radio Frequency) data for one line to the main control module 6 every time data for one line is accumulated.

Since the buried object detection device 1 is moved, the measurement positions are not exactly the same, and the depth direction B is not exactly perpendicular to the surface 100a of the concrete 100.
Further, between the inputs of the encoder 7, the reflected wave acquisition process, the reflected wave / divided number transmission process, the reflected wave analysis process, the buried object determination process, and the determination result registration process of the buried object, which will be described later, are performed in this order. When the scanning speed of the operator is high, pipeline processing is performed for the above-mentioned plurality of processing.

(1st control unit 10)
As shown in FIG. 3B, the first control unit 10 includes a scanning state detecting unit 61 (an example of a scanning state acquisition unit), a processing division number determination unit 62, and a scanning result acquisition unit 63. The scanning state detection unit 61 acquires the predicted processing time from the input of the encoder 7. The processing division number determination unit 62 determines whether or not to perform pipeline processing based on the scanning speed of the operator, and if the pipeline processing is performed, determines the number of processing and the number to divide the memory 9. The scanning result acquisition unit 63 acquires RF data for one line received from the receiving antenna 12 via the gate unit 15.

FIG. 5A is a diagram showing a table for explaining the acquisition of the predicted processing time. The scanning state detection unit 61 approximates the time difference between the past four encoder inputs by the least squares method, and calculates the next time difference. This time difference is the time difference between the predicted next encoder inputs, and is the predicted processing time. For example, the time difference between the second time and the first time, the time difference between the third time and the second time, and so on, the time difference between this time and the previous time can be obtained. Then, for example, the sixth time difference T is predicted by the least squares method from the second 10 ms, the third 12 ms, the fourth 12 ms, and the fifth 13 ms. In FIG. 5A, the sixth predicted processing time T is 14, and the actual time difference is 15. Then, the 7th predicted processing time is obtained by the least squares method using the values of the 3rd 12 ms, the 4th 12 ms, the 5th 13 ms, and the 6th 15 ms (actual measurement time). In this way, the predicted processing time T is obtained for each input of the encoder 7. The calculation of the predicted processing time T is not limited to the least squares method, and may be, for example, the average of five time differences.

The processing division number determination unit 62 divides the processing and the memory based on the calculated predicted processing time T. The processing division number determination unit 62 determines the processing division number based on the table as shown in FIG. 5B stored in the storage unit 17. When the predicted processing time T calculated by the scanning state detection unit 61 is 6 ms or less, the processing time is assumed to be short, the number of processing divisions is 5, and the memory 9 is divided into 5. When the predicted processing time T is larger than 6 ms and 8 ms or less, the number of processing divisions is set to 3 and the memory 9 is divided into three. Further, when the predicted processing time T is larger than 8 ms, it is assumed that all the processes for specifying the buried object between the encoder inputs are completed, and the pipeline process is not performed.

In this way, the predicted processing time T is obtained for each input of the encoder 7, it is determined whether or not the pipeline processing is performed, and when the pipeline processing is performed, the memory 9 and the number of divisions of the processing are determined. ..
The scanning result acquisition unit 63 includes a first processing division unit 71 (an example of a processing division unit), a reflected wave acquisition unit 72, and a reflected wave / processing division number transmission unit 73 (an example of a transmission unit). The first processing division unit 71 instructs the reflected wave acquisition unit 72 and the reflected wave / processing division number transmission unit 73 to perform division processing based on the processing division number determined by the processing division number determination unit 62.

The reflected wave acquisition unit 72 controls the delay unit 14, captures the reflected wave received by the receiving antenna 12 via the gate unit 15, and stores it in the storage unit 16. The reflected wave / processing division number transmission unit 73 receives the scanning result receiving unit of the main control module 6 for the reflected wave data for one line stored in the storage unit 16 and the processing division number determined by the processing division number determination unit 62. Send to 21.
The description of the pipeline processing will be given after the description of the configuration of the main control module 6.

(Main control module 6)
FIG. 6A is a block diagram showing the configuration of the main control module 6. The main control module 6 includes a scanning result receiving unit 21 (an example of a receiving unit), an RF data management unit 22, a second control unit 20, a display control unit 26, and a storage unit 27.
The scanning result receiving unit 21 receives RF data for one line each time it is transmitted from the impulse control module 5.

The RF data management unit 22 stores RF data for one line received by the scanning result receiving unit 21.
The second control unit 20 detects the buried object 101 from the RF data and registers its position. The second control unit 20 is composed of an MPU (Micro Processing Unit) or the like, and expands and executes a program stored in the storage unit 27 on the memory 9.

The second control unit 20 includes a reflected wave analysis unit 23, a buried object determination unit 24, a determination result registration unit 25, and a second processing division unit 29 (an example of the processing division unit).
The reflected wave analysis unit 23 detects the peak of the signal strength for each averaged line of data.
The buried object determination unit 24 determines the presence or absence of the buried object 101 by using the peak of the signal intensity for each RF data for one line detected by the reflected wave analysis unit 23, and detects the position thereof.

The determination result registration unit 25 registers the position of the buried object detected by the buried object determination unit 24 in the RF data management unit 22.
The display control unit 26 controls the display unit 8 to display an image in which the signal intensity is gradation-processed by color in the planes of the moving direction A and the depth direction B. Further, the display control unit 26 controls the display unit 8 to display the position of the buried object 101.

The second processing division unit 29 instructs the reflected wave analysis unit 23, the buried object determination unit 24, and the determination result registration unit 25 to perform pipeline processing based on the number of processing divisions received by the scanning result receiving unit 21. ..

(Reflected wave analysis unit 23)
FIG. 6B is a block diagram showing the configuration of the reflected wave analysis unit 23.
As shown in FIG. 6B, the reflected wave analysis unit 23 includes a moving average processing unit 33, a difference processing unit 32, a first-order differential processing unit 34, a chattering removal unit 35, and a peak detection unit 36 (signal intensity peak detection unit 36). An example) and.
(Moving average processing unit 33)
The moving average processing unit 33 performs moving average processing for each line of RF data. In the present embodiment, for example, the moving average processing can be performed with an 8-point average.

(Difference processing unit 32)
The difference processing unit 32 extracts the RF data of the changed portion from the RF data subjected to the moving average processing by calculating the difference from the signal strength of the reference value. FIG. 7A is a diagram showing image data before the difference processing is performed, and FIG. 7B is a diagram showing the image data after the difference processing is performed.

Here, the signal strength of the reference value is stored in advance. Subtract the reference value signal strength from the signal strength. By performing this calculation for all depth positions of all lines, changes in the RF data signal can be clarified as shown in FIG. 7 (b).
FIG. 8A is a partially enlarged view of the image data subjected to the difference processing, and FIG. 8B is a diagram showing the signal strength of the RF data of the line L1 of FIG. 8A. The horizontal axis of FIG. 8B indicates the depth position, and is deepened along the arrow direction. The vertical axis of FIG. 8B shows the signal strength, and the signal strength increases along the direction of the arrow.

In the present embodiment, the stronger the signal strength, the whiter the gradation, and the weaker the signal strength, the blacker the gradation. Further, in the present embodiment, a downward peak, that is, a position where the black color is the darkest, and an upward peak, that is, a position where the white color is the lightest are detected. For example, the position of the downward peak indicates the position of the reinforcing bar or the like in the concrete, and the position of the upward peak indicates the position of the cavity or the resin in the concrete.

Since the principle of detecting the downward peak and the upward peak is the same, the following description specifically describes the detection of the downward peak (the position where the black color is the darkest).
The black portion (downward peak) on L1 in FIG. 8A is shown by P1 to P5. These P1 to P5 are also shown in FIG. 8 (b). Also, in FIG. 8B, one of the upward peaks between P2 and P3 is shown as P10.

(First derivative processing unit 34)
The first derivative processing unit 34 performs the first derivative process on the data subjected to the difference process in order to detect the downward peak. The first derivative processing unit 34 calculates the difference from the signal strength at a predetermined depth position to the signal strength at the next depth position.
FIG. 9 is an enlarged view between P10 and P3 of FIG. 8 (b). FIG. 10 is a diagram showing Table 150 as a result of the signal strength and the first derivative processing of the graph of FIG. As will be described later, FIG. 10 also shows the result of the chattering process and the graph 151.

The sequence number is shown in the leftmost column of Table 150 shown in FIG. The position becomes deeper as the sequence number increases. The second column from the left shows the signal strength at each sequence number. In the third column from the left, the difference calculated by the first derivative processing unit 34 is shown.
The difference of the sequence number n is a value obtained by subtracting the signal strength of the sequence number n from the signal strength of the sequence number n + 1. For example, the difference of the sequence number 7 is a value (-15) obtained by subtracting the 7th signal strength (432) from the 8th signal strength (416).
In this way, the first derivative processing unit 34 performs the first derivative process on all the data in one line.

(Chattering removal unit 35)
The chattering removing unit 35 performs a chattering removing process on the result of the first derivative processing.

In the data shown in FIG. 9, in the region R1, although the signal strength data is reduced as a whole, the data D2 is larger than the previous (shallow) data D1, and chattering due to noise occurs. You can see that it is doing. Further, in the region R2, the data D4 and D5 are smaller than the data D3, and it can be seen that chattering due to noise occurs. Such chattering occurs when the reflected wave changes depending on the material and particle size of the aggregate contained in the concrete. The chattering removing unit 35 removes such chattering.

The chattering removing unit 35 determines whether the difference between the sequence numbers is a positive value or a negative value. The fourth column from the left shows whether it is a positive change (increase) or a negative change (decrease), and in the case of a positive (+) change, 1 is shown and it is negative. In the case of the change of (-), -1 is shown.
That is, the chattering removing unit 35 determines whether the change in signal strength from the predetermined depth position to the next depth position on the deeper side is an increase or a decrease.

Here, FIG. 10 shows a graph 151 of a portion surrounded by hatching in Table 150. In the data of ◆ showing the change (+/-), only the sequence number 11 shows the positive (+) change despite the negative (-) change in the surroundings, and chattering occurs in the sequence number 11 due to noise. You can see that it is doing. The difference and change (+/-) values of the sequence number 11 correspond to the data D1 to D2 in FIG.

Further, it can be seen that the sequence numbers 34 and 35 show a positive (+) change in spite of the negative (−) change in the surroundings, and that chattering due to noise occurs in the sequence numbers 34 and 35. The difference and change (+/-) value of the sequence number 34 corresponds to the change between the data D3 to D4 in FIG. 10, and the difference and change (+/-) value of the sequence number 35 corresponds to the change between the data D3 and D4 in FIG. Corresponds to the change between the data D4 and D5 of.

The chattering removing unit 35 performs a chattering removing process with respect to the value of the above change (+/-). The rightmost column of Table 1 shows the value of the change (+/-) after noise removal by the chattering removal process. The chattering removing unit 35 determines that the change is positive (+) when all three consecutive values are larger than 0, and determines that the change is negative (-) when all three consecutive values are smaller than 0. However, everything else retains the previous value.

More specifically, in the chattering removing unit 35, when the nth change (+/-), the n + 1st change (+/-), and the n + 2nd change (+/-) of the sequence number are all positive values (1). Is determined to be the nth change (+/-) as a positive value (1). Further, in the chattering removing unit 35, when the nth change (+/-) of the sequence number, the n + 1st change (+/-), and the n + 2nd change (+/-) are all negative values (-1). Is determined to be the nth change (+/-) as a negative value (-1). The chattering removing unit 35 is the n-1st change when the positive / negative of the nth change (+/-) of the sequence number, the n + 1st change (+/-) and the n + 2nd change (+/-) do not match. Hold (+/-).

For example, the value of the 6th change (+/-) is -1, the value of the 7th change (+/-) is -1, and the value of the 8th change (+/-) is -1. Is. Therefore, the chattering removing unit 35 sets the value of the change (+/-) after the sixth chattering process to -1.
On the other hand, the value of the 11th change (+/-) in which chattering occurred is 1, the value of the next 12th change (+/-) is -1, and the value of the 13th change (+/-). ) Is -1. Therefore, the chattering removing unit 35 holds -1, which is the value of the change (+/-) after the tenth chattering process, as the value of the eleventh change (+/-).

The value of the 34th change (+/-) in which chattering occurred is 1, the value of the next 35th change (+/-) is 1, and the value of the 36th change (+/-). The value of is -1. Therefore, the chattering removing unit 35 holds -1, which is the value of the change (+/-) after the 33rd chattering process, as the value of the 34th change (+/-).
The value of the 35th change (+/-) in which chattering occurred is 1, the value of the 36th change (+/-) following it is -1, and the value of the 37th change (+/-) is -1. ) Is 1. Therefore, the chattering removing unit 35 holds -1, which is the value of the change (+/-) after the 34th chattering process, as the value of the 35th change (+/-).

In the data of (3) showing the change (+/-) after the chattering process in the graph 151, the value of the change (+/-) of the sequence number 11 is changed to the negative (-) change, and the sequence numbers 34 and 35 It can be seen that the change (+/-) value has been changed to a positive (+) change, and chattering has been removed.
The chattering removal process by the chattering removal unit 35 as described above is performed for each RF data of the line.

(Peak detection unit 36)
The peak detection unit 36 extracts the peak of one line of RF data after performing the first derivative processing. For example, when extracting a downward peak (black peak), the peak detection unit 36 extracts a point at which the change after the first derivative processing changes from a negative change to a positive change as a peak. Specifically, as shown in Table 150 of FIG. 10, the change in the sequence number 36 is a negative (−) change, and the change in the sequence number 37 is a positive (+) change. , The peak detection unit 36 determines that the signal strength is a downward peak at the depth position of the sequence number 37, and extracts the sequence number 37 as a downward peak.

When detecting an upward peak (the position where the white color is the lightest), the peak detection unit 36 determines the point at which the change after the first derivative processing changes from a positive change to a negative change. Extract as a peak. For example, in Table 150 of FIG. 10, it is determined that the signal strength is an upward peak at the depth position of the sequence number 5, and the sequence number 5 is extracted as an upward peak.

Further, the peak detection unit 36 detects the extracted peak as a peak when the absolute value of the signal strength is equal to or higher than a predetermined threshold value. When the intensity value of the extracted peak is outside the range of −E or more and + E or less (see FIG. 8), the peak detection unit 36 detects the extracted peak as a peak. On the other hand, when the intensity value of the extracted peak is within the range of the threshold value ± E, the peak detection unit 36 does not detect the extracted peak as a peak. In the example of FIG. 8, P2, P3, and P4 are detected as peaks among the extracted downward peaks P1 to P5, but P1 and P5 are detected as peaks because they exist in the range of −E or more and + E or less. Not done.

(Buried object determination unit 24)
FIG. 6C is a block diagram showing the configuration of the buried object determination unit 24.
As shown in FIG. 6C, the buried object determination unit 24 includes a grouping unit 51, a chattering removing unit 52, and a buried object detection unit 58. The grouping unit 51 extracts continuous peaks in the moving direction as a group from the plurality of peaks detected by the peak detection unit 36. The chattering removing unit 52 removes the chattering of the group. When the group has a predetermined chevron waveform, the buried object detection unit 58 detects the vertices, puts them in the vertex group, and determines the position of the buried object from a plurality of vertices.

(Grouping unit 51)
The grouping unit 51 groups the peak detection results by the peak detection unit 36. The grouping unit 51 confirms the presence / absence of a peak detection result in order from the past line. Using the result as a starting point, the presence or absence of continuous peak detection in the traveling direction is checked. FIG. 11 is a diagram showing image data after the reflected wave analysis processing by the reflected wave analysis unit 23. In FIG. 11, the line L2 acquired this time is shown. 12 (a) to 12 (d) are diagrams for explaining the processing by the grouping unit 51.

FIG. 12A is a diagram showing a target range for confirming whether or not a peak of the next line exists. The grouping unit 51 determines whether or not the peak of the next line exists within 1 pixel of the moving direction A1 and within 5 pixels above and below, starting from the position QS of the peak found first (indicated by ● in FIG. 11). Confirm. The line where the peak position Q is found is used as the current line. The specific numerical value of the number of pixels is not necessarily limited to 1 pixel and 5 pixels.

FIG. 12B shows a case where the position Q2 of the next peak exists within 1 pixel of the moving direction A1 of the peak position QS of the current line and within the upper 5 pixels. In FIG. 12B, the position of the peak rises (moves to the shallow side) in the moving direction. FIG. 12 (c) shows a case where the peak position Q2 of the next line exists within 1 pixel of the moving direction A1 of the peak position QS of the current line and within 5 pixels of the lower side. In FIG. 12 (c), the position of the peak is descending (moving to the deeper side) in the moving direction.

Subsequently, the line where the peak position Q2 exists is set as the current line, and it is confirmed whether or not the peak of the next line exists within 1 pixel of the moving direction A1 of the peak position Q2 and within 5 pixels above and below. In this way, each time the RF data of the line is received, the current line is shifted in the moving direction and the continuity of the peak is confirmed.
Then, as shown in FIG. 12 (d), when the peak of the next line does not exist within 1 pixel of the moving direction A1 of the peak position of the current line and within 5 pixels above and below, the peak position Qe Is the end point of the group (indicated by ■ in FIG. 11).

As described above, the grouping unit 51 groups the peak positions. In FIG. 11, a group (for example, group G1) in which a black circle and a black square are connected by a line is shown.
Similarly, grouping at the position of the upward peak (the position where the white color is the lightest) is also performed.

(Chattering removal unit 52)
The chattering removing unit 52 performs a moving average process on all the results grouped by the grouping unit 51.
The chattering removing unit 52 performs a moving average process for each group at the positions of consecutive peaks grouped by the grouping unit 51. In the present embodiment, the moving average processing can be performed at 8 points.

(Buried object detection unit 58)
The buried object detection unit 58 detects the buried object based on the group in which the chattering is removed.
The buried object detection unit 58 includes a chevron waveform apex detection unit 56 and a determination unit 57. The chevron waveform vertex detection unit 56 determines whether or not the detected group is a predetermined chevron waveform, and if it is determined to be a predetermined chevron waveform, the position of the peak of the chevron waveform is put in the vertex group.
The determination unit 57 determines the position of the buried object based on the vertex group.

(Yamagata waveform vertex detection unit 56)
The chevron waveform apex detection unit 56 determines whether or not the shape of the group is a predetermined chevron waveform. The chevron waveform apex detection unit 56 determines that the group is a predetermined chevron waveform when the three conditions of the first condition, the second condition, and the third condition are satisfied.
The first condition is that the differential value becomes negative from plus via zero when differentiated, and the second condition is that there are peak values of Xpixel or more before and after the zero point of the first condition. The third condition is that the area of the differential value within the Xpixel range is equal to or larger than a predetermined threshold value with respect to the zero point of the first condition.
When these three conditions are satisfied, the chevron waveform vertex detection unit 56 determines that the shape of the group is a predetermined chevron waveform, and detects the vertices corresponding to the zero point of the first condition.

FIG. 13A is a diagram showing the positions of a plurality of grouped peaks. The chevron waveform apex detection unit 56 differentiates the data shown in FIG. 13A, and determines that the first condition is satisfied when the differential data becomes negative from plus via zero. FIG. 13B is a diagram showing data obtained by differentiating FIG. 13A. In FIG. 13B, since the differential value changes from positive to negative along the moving direction A1 via zero, it is determined that the first condition is satisfied. The zero point H indicates the peak Qp at the depth position shown in FIG. 13 (a).

Next, as a second condition, the chevron waveform apex detection unit 56 determines whether or not there is a signal intensity peak of Xpixel or more in the anteroposterior direction from the zero point H (peak Qp at the depth position) of the differentiated data. judge. 14 (a) is a diagram showing the second condition in FIG. 13 (a). FIG. 14 (b) is a diagram showing the second condition in FIG. 13 (b). As shown in FIGS. 14 (a) and 14 (b), since there is a peak value of signal intensity equal to or higher than Xpixel in the anteroposterior direction from the zero point H (peak Qp at the depth position), FIGS. 14 (a) and 14 (b) and FIG. The data shown in FIG. 14B is determined to satisfy the second condition.

Next, as a third condition, the chevron waveform apex detection unit 56 calculates the area of the shaded area 300 shown in FIG. 14B, and determines whether or not the calculated area is equal to or larger than a predetermined threshold value. FIG. 15A is a diagram showing an example in which the area of the shaded portion 300 is equal to or larger than a predetermined threshold value, and FIG. 15B is a diagram showing an example in which the area of the shaded portion 300 is less than a predetermined threshold value. When the calculated area is equal to or larger than a predetermined threshold value, the chevron waveform vertex detection unit 56 puts the vertex Qp into the vertex group of the chevron waveform. On the other hand, when the calculated area is equal to or larger than a predetermined threshold value, the chevron waveform vertex detection unit 56 does not put the vertex Qp in the vertex group of the chevron waveform.

(Determination unit 57)
The determination unit 57 determines the position of the buried object 101 based on the vertices put in the vertex group of the chevron waveform.
The determination unit 57 performs vertex grouping based on the shallow vertices at the vertices whose area when differentiated is equal to or larger than a predetermined threshold value. The determination unit 57 determines whether or not the object is a buried object based on the positional relationship of the vertices grouped by the vertices. When two or more vertices exist in the range of vertex grouping, the determination unit 57 registers the shallower vertex position as the position of the buried object.

In the apex grouping, the apex in the range of ± Jpixel in the anteroposterior direction (arrows A1 and A2 directions) and the apex in the vertical direction (arrows B and C directions) up to the lower maximum is grouped with the shallowest apex as a reference. 16 (a) to 16 (c) are diagrams showing an example of vertex grouping. In FIG. 16, the white squares indicate the vertices of the white peak, and the black squares indicate the vertices of the black peak.
In FIG. 16A, the white peak and the black peak are shown in order from the shallowest within the range of the vertex grouping. In FIG. 16B, a black peak, a white peak, and a black peak are shown in order from the shallowest within the range of the vertex grouping. In FIG. 16 (c), only black peaks are shown within the range of vertex grouping.
In this case, in FIG. 16A, the position of the shallowest white peak (shown as P20) is registered as the position of the buried object. Further, in FIG. 16B, the position of the shallowest black peak (indicated as P21) is registered as the position of the buried object. On the other hand, in FIG. 16C, since there is only one peak in the vertex group range, it is not registered as the position of the buried object.

(Judgment result registration unit 25)
The determination result registration unit 25 registers the result (group, peak position, determined position of the buried object, etc.) determined by the buried object determination unit 24 in the RF data management unit 22.

(Display control unit 26)
The display control unit 26 indicates a group, a peak position, and the like on the data image, and causes the display unit 8 to display the group and the peak position. For example, as in the image data of FIG. 11, the image data obtained by black-and-white gradation of the RF data and the determined position of the buried object (for example, x mark) are displayed on the display unit 8.

(Pipeline processing)
Next, pipeline processing will be described.
In the pipeline processing of the present embodiment, (1) reflected wave acquisition processing by the reflected wave acquisition unit 72, (2) reflected wave / processing division number transmission processing by the reflected wave / processing division number transmission unit 73, and reflected wave. Five processes of (3) reflected wave analysis process by the analysis unit 23, (4) buried object determination process by the buried object determination unit 24, and (5) determination result registration process by the determination result registration unit 25 are the targets of division. Become.

As described above, when the number of processing divisions is determined to be 5 by the processing division number determination unit 62, each of the above processes (1) to (5) is divided and pipelined.
17 (a) to 17 (c) are diagrams for explaining pipeline processing. The intervals between the arrows shown in FIGS. 17A to 17C indicate the input intervals of the encoder 7, and indicate the processing completion time.
FIG. 17A is a diagram showing the progress of control when pipeline processing is not performed. (1) shown in the figure shows the reflected wave acquisition processing, (2) shows the reflected wave / processing division number transmission processing, (3) shows the reflected wave analysis processing, and (4) shows the buried object determination processing. (5) shows the determination result registration process.

In FIG. 17A, the measurement is performed from the A to the Jth using the encoder input as a trigger, and the processes of (1) to (5) are performed in order, but the processing is performed during the input interval of the encoder. It is finished and all the results of A to J are obtained.
FIG. 17B is a diagram showing a case where the operator moves the buried object detection device 1 quickly, and is a diagram showing a case where the pipeline processing is not performed. As shown in FIG. 17B, when the scanning by the operator becomes faster, the processing is not completed by the encoder input, and the results of B, D, F, and H are lost.

Therefore, in the present embodiment, pipeline processing is performed as shown in FIG. 17 (c). The area in which the memory 9 is divided into five is referred to as a first divided memory to a fifth divided memory.
That is, at the time of measurement A, the (1) reflected wave acquisition process of measurement A is performed in the first divided memory, and at the time of measurement B, the (2) reflected wave / processed division number of measurement A is performed in the first divided memory. The transmission process is performed, and the (1) reflected wave acquisition process of measurement B is performed in the second partition memory. Then, at the time of measurement C, (3) reflected wave analysis processing of measurement A is performed in the first division memory, and (2) reflected wave / processing division number transmission processing of measurement B is performed in the second division memory. (1) Reflected wave acquisition processing of measurement C is performed in the third divided memory. Then, at the time of measurement D, the (4) buried object determination process of measurement A is performed in the first divided memory, the (3) reflected wave analysis process of measurement B is performed in the second divided memory, and the third divided memory. (2) Reflected wave / processing division number transmission processing of measurement C is performed, and (1) reflected wave acquisition processing of measurement D is performed in the fourth division memory. Then, at the time of measurement E, (5) determination result registration processing of measurement A is performed in the first division memory, (4) buried object determination processing of measurement B is performed in the second division memory, and the third division memory. The (3) reflected wave analysis process of the measurement C is performed in, the (2) reflected wave / processed division number transmission process of the measurement D is performed in the fourth divided memory, and the (1) reflection of the measurement E is performed in the fifth divided memory. Wave acquisition processing is performed. At the time of measurement E, the result of measurement A will be obtained. Therefore, at the time of the next measurement F, the (1) reflected wave acquisition process of the measurement F is performed in the first divided memory.

After that, the result of measurement B, the result of measurement C, the result of measurement D, the result of measurement E, and the result of measurement F are sequentially calculated.
FIG. 18 is a diagram showing the progress of processing when the number of processing divisions becomes three. In the three cases, for example, (1) reflected wave acquisition processing and (2) reflected wave / processing division number transmission processing are performed as continuous processing, (3) reflected wave analysis processing and (4) buried object determination processing. Is performed as a continuous process, and (5) the determination result registration unit 25 is performed independently.

At the time of measurement of A, (1) reflected wave acquisition processing and (2) reflected wave / processing division number transmission processing of A measurement are continuously performed in the first division memory. Then, at the time of B measurement, (3) reflected wave analysis processing and (4) buried object determination processing of A measurement are continuously performed in the first division memory, and B measurement (B) measurement is performed in the second division memory. 1) Reflected wave acquisition processing and (2) Reflected wave / processing division number transmission processing are continuously performed. Then, at the time of C measurement, (5) determination result registration processing of A measurement is performed in the first division memory, and (3) reflected wave analysis processing and (4) burying of B measurement in the second division memory. The object determination process is continuously performed, and (1) reflected wave acquisition process and (2) reflected wave / processed partition number transmission process of C measurement are continuously performed in the third division memory. When measuring C, the result of measurement A is required.

In the next measurement of D, (1) reflected wave acquisition processing and (2) reflected wave / processing division number transmission processing of C measurement are continuously performed in the first division memory, and (5) in the second division memory. The determination result registration process is performed, and (3) reflected wave analysis process and (4) buried object determination process of C measurement are continuously performed in the third division memory. After that, pipeline processing is sequentially performed.
FIG. 19 is a diagram showing pipeline processing when the scanning speed by the operator slows down from the middle and the number of processing divisions is reduced from 5 to 3.

The speed is high from measurement A to measurement C, and the number of processing divisions is 5, but from measurement D, the number of processing divisions is 3. In this case, at the time of measurement D, (4) buried object determination process and (5) determination result registration process of measurement A are continuously performed. Further, since the processing of the measurement D is started in the 4th division memory, the 4th division memory is used until the processing of (1) to (5) of the measurement D is completed, and then the number of processing divisions is 3. It becomes.

FIG. 20 is a diagram showing pipeline processing when the scanning speed by the operator increases from the middle and the number of processing divisions increases from 3 to 5.
The number of processing divisions is 3 from measurement A to measurement C, but the number of processing divisions is 5 from measurement D. In this case, the first division memory is used when the processing of the measurement F is started after the processing of the measurement A is completed in the first division memory. Further, after the processing of the measurement B is completed in the second divided memory, the second divided memory is used when the processing of the measurement G is started.

FIG. 21 is a diagram showing pipeline processing when the scanning speed by the operator changes and the number of processing divisions changes to 5, 5, 5, 3, 5, 3, 5, 3, 5, 3. ..
As described above, as shown in FIGS. 19 to 21, even if the speed changes in the middle of the movement in the moving direction A1, the scanning state detection unit 61 detects the scanning speed from the input from the encoder 7, and the predicted time. Pipeline processing can be performed by calculating T and appropriately changing the number of divisions.

<Operation>
Next, the operation of the buried object detection device 1 according to the embodiment of the present invention will be described.
(Buried exploration process)
FIG. 22 is a flow chart showing a buried object exploration process.
When the buried object exploration process is started, in step 201, the scanning state detecting unit 61 detects the scanning speed of the buried object detecting device 1.

Next, in step S202, the processing division number determination unit 62 determines the processing division number according to the scanning speed.
Next, in step S203, RF data is acquired by the scanning result acquisition unit 63 and transmitted to the impulse control module.
Next, in step S204, the buried object detection process is performed by the second control unit 20.

Next, in step S205, the display control unit 26 indicates the position of the buried object 101 together with the image data to the display unit 8.

(Scanning state detection process)
FIG. 23 is a flow chart showing the scanning state detection process in step S201 of FIG. 22.
When the scanning state detection process is started, in step S211 when there is an input from the encoder 7, the scanning state detection unit 61 calculates the time difference between the past four encoder inputs in step S212. Step S211 corresponds to an example of the detection step.
Next, in step S213, the scanning state detection unit 61 approximates the calculated time difference by the least squares method to calculate the next time difference (predicted processing time), and the scanning state detection process ends. Steps S212 and S213 correspond to an example of the scanning state acquisition process.

(Processing division number determination processing)
FIG. 24 is a flow chart showing a process division number determination process in step S202 of FIG. 22.
When the processing division number determination processing is started, in step S221, the processing division number determination unit 62 determines the number of divisions of the first processing division unit 71 based on the table (see FIG. 5) from the predicted processing time, and stores the memory. Also determine the number of divisions of 9.

Next, in step S222, the processing division number determination unit 62 determines the division number of the second processing division unit 29 based on the table (see FIG. 5) from the predicted processing time, and also determines the division number of the memory 9. Processing The process of determining the number of divisions ends.
When the processing division number determination unit 62 determines that the processing division number is 1, the first processing division unit 71 is (1) by the reflected wave acquisition unit 72 and by the reflected wave acquisition processing and the reflected wave / processing division number transmission unit 73 ( 2) Reflected wave / number of processing divisions The transmission processing is not divided. In addition, the second processing division unit 29 has (3) reflected wave analysis processing by the reflected wave analysis unit 23, (4) buried object determination processing by the buried object determination unit 24, and (5) determination by the determination result registration unit 25. Do not divide the result registration process.

When the processing division number determination unit 62 determines that the processing division number is 5, the first processing division unit 71 divides the processing of (1) and (2) into two memory areas, and the second processing division unit 29. Divides the processes of (3), (4) and (5) into three memory areas. Further, when the processing division number determination unit 62 determines that the processing division number is 3, the first processing division unit 71 does not divide the processing of (1) and (2), and the second processing division unit 29 is (3) (. 4) The process of (5) is divided into two memory areas.

(Scanning result acquisition process)
FIG. 25 is a flow chart showing the scanning result acquisition process in step S203 of FIG. 22.
When the scanning result acquisition process is started, in step S231, the first process division unit 71 performs the reflected wave acquisition process in step S232 and the reflected wave / process in step S232, if necessary based on the number of process divisions. Number of divisions The transmission process is divided and the pipeline process is performed. Step S231 corresponds to an example of the processing division step.

In step S232, the reflected wave acquisition unit 72 controls the delay unit 14, captures the reflected wave received by the receiving antenna 12 via the gate unit 15, and stores it in the storage unit 16.
In step S233, the reflected wave / processing division number transmission unit 73 transmits the RF data acquired by the reflected wave acquisition unit 72 to the impulse control module 5.

(Reflected wave acquisition processing)
FIG. 26 is a flow chart showing the reflected wave acquisition process in step S232 of FIG. 25.
When the reflected wave acquisition process is started, the impulse output control is started in step S2, and the electromagnetic wave pulse is output from the transmitting antenna 11 at a fixed cycle (for example, 1 MHz) based on the pulse from the pulse generating unit 13.
Next, in step S3, the delay unit 14 sets the delay time in the delay IC. For example, the Delay time can be set from 0 to 5120 psec in units of 10 psec.

Next, in step S4, the first control unit 10 AD-converts the RF data received from the receiving antenna 12 via the gate unit 15.
Next, in step S5, it is determined whether or not the Delay time is the maximum (for example, 5120 psec), and if it is not the maximum, the control returns to step S3. By repeating steps S3, S4, and S5, data for one line can be acquired. Step S5 corresponds to an example of a receiving step.

Next, in step S6, the AD-converted RF data is transmitted to the main control module 6.
Then, in step S7, the impulse control is stopped and the reflected wave acquisition process is completed.
Next, when the buried object detection device 1 is moved in the moving direction A (A1 or A2) by the operator, there is an input from the encoder 7, the steps S2 to S7 are controlled, and the next one line is controlled. The data is acquired and transmitted to the main control module 6.

(Reflected wave / Processing division number transmission processing)
FIG. 27 is a flow chart showing the reflected wave / processing division number transmission processing in step S233 of FIG. 25.
When the reflected wave / processed division number transmission processing is started, the reflected wave / processing division number transmission unit 73 receives the reflected wave data for one line acquired by the reflected wave acquisition unit 72 and stored in the storage unit 16. The number of processing divisions determined by the processing division number determination unit 62 is transmitted to the scanning result receiving unit 21 of the main control module 6, and the control ends.

(Buried object detection process)
FIG. 28 is a flow chart showing the buried object detection process in step S204 of FIG. 22.
First, in step S10, when the scanning result receiving unit 21 receives RF data for one line from the impulse control module 5, in step S11, the second processing division unit 29 is required based on the number of processing divisions. , The reflected wave analysis process in step S12, the buried object determination process in step S13, and the determination result registration process in step S14 are divided, and the pipeline process is performed. Step S11 corresponds to an example of the processing division step.

Next, in step S12, the reflected wave analysis unit 23 performs the reflection analysis process before determining the buried object.
Next, in step S13, the presence or absence of the buried object is determined by the buried object determination unit 24, and the position of the buried object is specified.
Next, in step S14, the result determined by the buried object determination unit 24 is registered by the determination result registration unit 25.
Next, the processing in each step will be described in detail.

(Reflected wave analysis processing)
FIG. 29 is a flow chart showing the reflected wave analysis process in step S12 of FIG. 28.
First, in step S22, the moving average processing unit 33 performs moving average processing on the received RF data.

Next, in step S23, the difference processing unit 32 calculates the difference between the signal strength of the reference value stored in advance and the RF data subjected to the moving average processing, and the change in the RF data is extracted.
Next, in step S24, the first derivative processing unit 34 performs the first derivative process on the difference result processed by the moving average, and the difference between the adjacent data in the depth direction is positive (increase) or negative (decrease). Judgment is made.

Next, in step S25, the chattering removing unit 35 performs the chattering removing process on the data after the first derivative processing.
Finally, in step S26, the peak detection unit 36 detects the peak of the signal strength using the determination result of the chattering removal process. Step S26 corresponds to an example of the signal strength peak detection step.

(Moving average processing)
Next, the moving average processing in step S22 of FIG. 29 will be described. FIG. 30 is a flow chart showing a moving average process.
When the moving average processing is started, in step S31, the moving average processing unit 33 selects the received data of sequence number 1 from the received RF data.

Then, after the moving average processing unit 33 processes the data of sequence number 1 in step S32, the control proceeds to step S33.
In step S33, it is determined whether or not the sequence number is the maximum value, and if the sequence number is not the maximum value, the control returns to step S31, the sequence number is incremented by one, and the received data of the sequence number 2 is received. Be selected. Then, the process of step S32 is performed on the data of the sequence number 2.

In this way, the flow is repeated until the processing of step S32 is performed for all the data for one line.
In step S32, the moving average processing unit 33 performs moving average processing on the RF data for one line that has been differentially processed. For example, a moving average process can be performed using an 8-point average.

(Difference processing)
Next, the difference processing in step S23 of FIG. 29 will be described. FIG. 31 is a flow chart showing the difference processing.
When the difference processing is disclosed, in step S41, the difference processing unit 32 selects the received data of sequence number 1 from the RF data subjected to the moving average processing.

Then, after the difference processing unit 32 processes the data of sequence number 1 in step S42, the control proceeds to step S43.
In step S43, it is determined whether or not the sequence number is the maximum value, and if the sequence number is not the maximum value, the control returns to step S41, the sequence number is incremented by one, and the received data of the sequence number 2 is received. Be selected. Then, the process of step S42 is performed on the data of the sequence number 2.

In this way, the flow is repeated until the processing of step S42 is performed for all the data for one line.
In step S42, the difference processing unit 32 calculates the difference between the signal strength of the reference value stored in the RF data management unit 22 and the received data of each line.
By this difference processing, changes in RF data can be extracted as in the image data shown in FIG. 7 (b).

(First derivative processing of difference result)
Next, the first derivative processing of the difference result in step S24 of FIG. 29 will be described. FIG. 32 is a flow chart showing the first derivative processing of the difference result.
When the first-order differential processing of the difference result is started, in step S51, the first-order differential processing unit 34 selects the difference result of sequence number 1 from the difference results obtained by the difference processing.

Next, in step S52, the first derivative processing unit 34 performs the first derivative process of the difference result. Here, the first-order differential processing is to calculate the difference between the difference result data at a predetermined position and the difference result data at the next position in the depth direction. That is, the difference between the sequence number 1 and the next sequence number 2 is calculated.
Next, in step S53, it is determined whether or not the sequence number is the maximum value, and if the sequence number is not the maximum value, the control returns to step S51, the number is incremented by one, and the sequence number 2 is received. The data is selected. Then, the difference between the sequence number 2 and the sequence number 3 is calculated.

In this way, the numbers are sequentially incremented and step S52 is repeated until the first derivative processing is performed on all the data for one line.
That is, when performing the first derivative processing of the sequence number n, the first derivative process is performed on the data of the sequence number n by subtracting the data of the difference result of the sequence number n from the data of the difference result of the sequence number n + 1. It can be carried out.
As a result, the difference in the third column from the left in Table 150 of FIG. 10 is calculated.

(Chattering removal process)
Next, the chattering removal process in step S25 of FIG. 29 will be described. FIG. 33 is a flow chart showing the chattering removal process.
When the chattering removal process is started, in step S61, the chattering removal unit 35 selects the sequence number 1 in which the first derivative processing has been performed.

Then, after the chattering removing unit 35 controls any of steps S62 to S66 with respect to the data of sequence number 1, the control proceeds to step S67.
In step S67, it is determined whether or not the sequence number is the maximum value, and if the sequence number is not the maximum value, the control returns to step S61, the number is incremented by one, and the received data of the sequence number 2 is selected. Will be done.

In this way, until the chattering removing unit 35 processes all the data for one line, the numbers are sequentially incremented and the process of any one of steps S62 to S66 is repeated.
Here, steps S62 to S66 will be described assuming that the chattering removal process is performed on the nth data.

In step S62, the chattering removal unit 35 determines whether or not all three consecutive first-order differential results are greater than zero. Since the sequence number n is selected, when the first derivative results of the sequence numbers n, n + 1, and n + 2 are all 0 or more, the chattering removing unit 35 sets the sequence number n as the first derivative after the chattering removing process in step S63. The result is stored as positive (+).

On the other hand, in step S62, when the chattering removing unit 35 has even one of the first derivative results of three consecutive sequence numbers of 0 or less, in step S64, all three consecutive first derivative results are smaller than 0. Judge whether or not. Since the sequence number n is selected, when the first derivative results of the sequence numbers n, n + 1, and n + 2 are all smaller than 0, the chattering removing unit 35 sets the sequence number n as the primary after the chattering removing process in step S65. The differential result is stored as negative (-).

Further, in step S64, if even one of the three consecutive first-order differential results is larger than 0, the control proceeds to step S66.
Then, in step S66, the chattering removing unit 35 stores the state of the previous sequence number as the state of the current sequence number. Since the sequence number n is selected, the chattering removal unit 35 displays the positive (+) or negative (-) result after the chattering removal processing stored for the sequence number n-1 after the chattering removal processing of the sequence number n. Memorize as a result of.
As a result, the change after the chattering process on the rightmost side of Table 150 in FIG. 10 can be obtained.

(Peak detection processing)
Next, the peak detection process in step S26 of FIG. 29 will be described. FIG. 34 is a flow chart showing the peak detection process.

When the peak detection process is started, in step S71, the peak detection unit 36 selects the sequence number 1 in which the chattering removal process has been performed.
Then, the peak detection unit 36 controls steps S72, S73, and S74 with respect to the data of sequence number 1, and then the control proceeds to step S75.
In step S75, it is determined whether or not the sequence number is the maximum value, and if the sequence number is not the maximum value, the control returns to step S71, the sequence number is incremented by one, and the received data of the sequence number 2 is received. Be selected. Then, the processes of steps S72, S73, and S74 are performed on the data of the sequence number 2.

In this way, until the chattering removing unit 35 processes all the data for one line, the numbers are sequentially incremented and the processes of steps S72, S73, and S74 are repeated.
Here, steps S72 to S74 will be described assuming that the peak detection process is performed on the nth data.

In step S72, the peak detection unit 36 determines whether or not the state of the previous sequence number n-1 after the chattering removal is negative (−) and the state of the current sequence number n is positive (+). It is determined whether or not the state of the previous sequence number n-1 after the chattering removal is positive (+) and the state of the current sequence number n is negative (−).
Then, when the state of the previous sequence number n-1 is negative (-) and the state of the current sequence number n is positive (+), or the state of the previous sequence number n-1 after chattering is removed is the state. When it is positive (+) and the state of the sequence number n this time is negative (−), the peak detection unit 36 extracts the nth coordinate as a peak.

Next, in step S73, the peak detection unit 36 determines whether or not the signal strength of the extracted peak at the nth coordinate is outside the range of a predetermined threshold value (−E or more, + E or less).
Then, when the signal strength of the peak of the extracted nth coordinate is out of the predetermined range, the nth coordinate is stored in the RF data management unit 22 as the peak coordinate in step S74. The coordinates can be indicated by, for example, a moving distance (which can be said to be a line number) and a depth position in pixels.
Thereby, as described above, for example, sequence numbers 5 (white peak) and 37 (black peak) in Table 150 of FIG. 10 can be detected as peaks.

(Buried object judgment process)
Next, the buried object determination process shown in step S13 of FIG. 29 will be described. FIG. 35 is a flow chart showing a buried object determination process.

When the buried object determination process is started, first, in step S81, the grouping unit 51 performs the grouping process of the peak detection result performed by the reflected wave analysis unit 23. This step S81 corresponds to an example of a grouping step.
Next, in step S82, the chattering removing unit 52 performs a chattering removing process on the grouped groups.

Next, in step S83, the chevron waveform apex detection unit 56 detects the apex of the chevron waveform when the group satisfies a predetermined chevron waveform.
Next, in step S84, the determination unit 57 performs a determination process for the buried object based on the vertices of the plurality of chevron waveforms. Steps S83 and S84 correspond to an example of the buried object detection step.
Next, in step S85, the display control unit 26 marks the position of the buried object determined by the determination unit 57 (for example, a cross mark, a circle mark, etc.) and causes the display unit 8 to display the position.

(Grouping process of peak detection results)
The grouping process of the peak detection result in step S81 of FIG. 35 will be described. FIG. 36 is a flow chart showing a grouping process of peak detection results.

First, in step S91, the grouping unit 51 sets the detection state to the “undetected” state.
All the data acquired in the past are targeted, and in step S92, the grouping unit 51 selects the old data in the past as the processing target. Then, in step S101, the grouping unit 51 determines whether all the data acquired in the past up to the line acquired this time has been processed, and if not, the control returns to step S92, and the next step is Old data is processed. In this way, for example, the processes of steps S93 to S100 are performed in order from the sequence number 1 of the oldest line.

In step S93, the grouping unit 51 determines whether or not the state has not been detected. Since the initial state is "not detected", the control proceeds to step S94.
In step S94, the grouping unit 51 determines whether or not there is a position where a peak is detected within a predetermined range. If no peak is detected in the predetermined range, the control proceeds to step S101. The predetermined range can be set as appropriate, for example, it may be set for one line, or it may be set for the sequence number of one line.

In this way, in step S94, it is determined whether or not there is a position where peaks are detected in order from the oldest data, and when there is a position where peaks are detected, in step S95, the grouping unit 51 determines. The detection status is set to "Detecting".
Next, in step S96, the grouping unit 51 stores the point where the peak is detected. This point is a coordinate in pixels, and can be indicated by, for example, a moving distance (which can be said to be a line number) and a depth position. This point corresponds to the starting point (●) in FIG.

Next, the next data is processed through steps S101 and S92.
Next, in step S93, since the detection state is “detecting”, the control proceeds to step S97.
In step S97, the grouping unit 51 determines whether or not there is a position where a peak is detected within a predetermined range from the position stored in step S96. This predetermined range can be set, for example, within 1 pixel in the moving direction described with reference to FIGS. 12 (a) to 12 (d), and within 5 pixels above and below. When the position where the peak is detected exists within a predetermined range, in step S98, the grouping unit 51 assumes that there is a continuous position and stores the position.

Next, the next data is processed through steps S101 and S92.
Next, in step S93, since the detection state is “detecting”, the control proceeds to step S97.
In this step S97, it is detected whether or not there is a point where a peak is detected within a predetermined range from the point stored in step S98 last time, and if so, that point is stored in step S98. .. As a result, continuous points are sequentially grouped.

Then, if the peak is not detected within the predetermined range in step S97, the control proceeds to step S99.
In step S99, the grouping unit 51 determines that there are no continuous points, and saves the detection results up to that point. The last detected point corresponds to the end point (■) in FIG.

Next, in step S100, the grouping unit 51 sets the detection state to the “undetected” state.
Then, in step S101, when it is determined that the processing has been performed for all the data of the lines acquired in the past, the processing ends.

(Chattering removal process)
Next, the chattering removal process shown in step S82 of FIG. 35 will be described. FIG. 37 is a flow chart showing a buried object determination process.
When the chattering removal process is disclosed, in step S111, the chattering removal unit 52 selects any one of the plurality of grouped groups.
Then, in step S112, the chattering removing unit 52 performs a moving average process on the selected group. For example, a moving average process can be performed using an 8-point average.

Next, in step S113, it is determined whether or not the moving average processing has been performed on all the groups, and if the processing has not been performed on all the groups, the control returns to step S111, and the other steps are taken. Group is selected. Then, the moving average processing is performed on the selected group.
In this way, the flow is repeated until the processing of step S112 is performed for all the grouped results.

(Yamagata waveform vertex detection processing)
Next, the chevron waveform vertex detection process shown in step S83 of FIG. 35 will be described. FIG. 38 is a flow chart showing the chevron waveform vertex detection process.
When the chevron waveform vertex detection process is started, in step S131, the chevron waveform vertex detection unit 56 selects one group from the grouping results.

Then, in step S132, the chevron waveform vertex detection unit 56 differentiates the selected group in the planes of the moving direction A1 and the depth direction B.
Next, in step S133, the chevron waveform vertex detection unit 56 determines whether or not there is a zero point such that the differential value passes from plus to zero and becomes negative. If there is no such zero point, the group is determined not to have a predetermined chevron waveform and control proceeds to step S138.

On the other hand, if it is determined in step S133 that such a zero point exists, the control proceeds to step S134. This zero point corresponds to the peak of the chevron waveform.
Then, in step S134, the chevron waveform apex detection unit 56 determines whether or not a peak of Xpixel or more exists in the front-rear direction from the apex of the chevron waveform. If there is no peak above Xpixel, the control proceeds to step S138, assuming that the waveform is not a chevron waveform that can be determined to have a buried object.

On the other hand, if it is determined in step S134 that a peak of Xpixel or higher is present, the control proceeds to step S135.
Then, in step S135, the chevron waveform apex detection unit 56 calculates the area of the differential value within the range within Xpixel in the front-back direction from the apex.
Next, in step S136, the chevron waveform apex detection unit 56 determines whether or not the calculated area is equal to or larger than a predetermined threshold value. If it is determined that the threshold value is not equal to or higher than the predetermined threshold value, the control proceeds to step S138, assuming that the waveform is not a chevron waveform that can determine that the buried object exists.

On the other hand, when it is determined in step S136 that the threshold value is equal to or higher than the predetermined threshold value, the chevron waveform vertex detection unit 56 puts the vertices corresponding to the zero points into the chevron waveform vertex group in step S137.
Next, in step S138, the chevron waveform vertex detection unit 56 confirms whether or not the chevron waveform vertex detection processing has been performed on all the groups subjected to the chevron waveform interpolation processing, and the processing is performed on all the groups. If not, control returns to step S131 and another group is selected. Then, steps S132 to S137 are repeated until the chevron waveform vertex detection process is performed for all the groups subjected to the chevron waveform interpolation processing.

(Buried object judgment process)
Next, the buried object determination process shown in step S84 of FIG. 35 will be described. FIG. 39 is a flow chart showing a buried object determination process.
When the buried object determination process is started, in step S141, the determination unit 57 selects one vertex put in the vertex group in order from the shallowest one.

Then, in step S142, the determination unit 57 determines whether or not there are other vertices within ± Jpixel in the front-back direction from the apex and in the entire range in the downward direction.
If it is determined in step S142 that another vertex exists, the determination unit 57 stores the vertex coordinates of the selected vertex in the RF data management unit 22 as an embedded object in step S143. On the other hand, when it is determined in step S142 that no other vertex exists, since only one vertex exists in the determined range, it is not stored as the position of the buried object, and the control proceeds to step S144.

Next, in step S144, it is determined whether or not the buried object determination process has been performed on all the vertices put in the vertex group. If no processing is performed, in step S141, the determination unit 57 selects another vertex of the vertex group. Here, the vertices detected as other vertices in step S142 are excluded from the selection target as if they have been processed.

Steps S142 and S143 are repeated until all the vertices put in the vertex group are selected or excluded from the selection target. Then, when all the vertices put in the vertex group are selected or excluded from the selection target, the control ends.
As shown in FIG. 35, regarding the position of the buried object registered by the determination result registration process, the display control unit 26 controls the display unit 8 to display the buried object (marks such as × and ○) in step S86. indicate.

[Other embodiments]
Although one embodiment of the present invention has been described above, the present invention is not limited to the above embodiment, and various modifications can be made without departing from the gist of the invention.
(A)
In the above embodiment, the control method of the buried object detecting device 1 and the buried object detecting device 1 has been described with reference to the flowcharts shown in FIGS. 22 to 39, but the present invention is not limited thereto. ..

For example, the present invention may be realized as a program for causing a computer to execute the buried object detecting device 1 and the buried object detecting method implemented according to the flowcharts shown in FIGS. 22 to 39.
Further, one usage mode of the program may be a mode in which the program is recorded on a recording medium such as a ROM that can be read by a computer and operates in cooperation with the computer.

Further, one form of use of the program may be a mode in which transmission is performed in a transmission medium such as the Internet or a transmission medium such as light, radio waves, and sound waves, is read by a computer, and operates in cooperation with the computer.
Further, the computer described above is not limited to hardware such as a CPU (Central Processing Unit), and may include firmware, an OS, and peripheral devices.
As described above, the power consumption body control method may be realized by software or hardware.

(B)
In the above embodiment, the impulse control module 5 is provided with the first control unit 10 and the main control module 6 is provided with the second control unit 20, but only one control unit is provided, and one is provided with the other. It may also serve as.

In that case, it is not necessary to transmit the reflected wave data from the impulse control module 5 to the main control module 6 by the reflected wave / processing division number transmission unit 73, and the control to be the target of the pipeline processing is the reflected wave acquisition processing and the reflection. There are four processes: wave analysis process, buried object determination process, and determination result registration process. Further, in this case, the first processing division unit 71 and the second processing division unit 29 may be one processing division unit.

(C)
In the above embodiment, the number of divisions of the memory 9 and the number of divisions of the processing are matched, but the number of divisions is not limited to this. However, in order to efficiently perform the pipeline processing, it is preferable to match the number of divisions of the memory 9 with the number of divisions of the processing.
(D)
In the above embodiment, only one memory 9 is provided, but a plurality of memories 9 may be provided. For example, one may be provided for the first control unit 10 and one may be provided for the second control unit 20. Each memory is appropriately divided by the commands of the first processing division unit 71 and the second processing division unit 29.

(E)
In the above embodiment, the reinforcing bar has been described as an example of the buried object, but the reinforcing bar may not be limited to the reinforcing bar, and may be a gas pipe, a water pipe, wood, or the like, and the buried object is provided. The object is not limited to concrete.
(F)
In the above embodiment, black is set to indicate the reinforcing bar by gradation processing, but the present invention is not limited to this, and white may be set to indicate the reinforcing bar.

(G)
In the above embodiment, the main control module 6 is provided in the main body 2 of the buried object detection device 1, but the main control module 6 may be provided separately from the main body 2. In this case, the main control module 6 and the display unit 8 may be provided on a tablet or the like. Communication may be performed wirelessly or by wire between the main body 2 and the tablet.

The buried object detection device and the buried object detection method of the present invention have an effect of being able to accurately detect buried objects even when the moving speed is high, and are useful for detecting buried objects in concrete. ..

1 Buried object detection device 29 Second processing division unit 61 Scanning state detection unit 71 First processing division unit

Claims (8)

It is a buried object detection device for detecting an embedded object in the object by using the data on the reflected wave of the electromagnetic wave radiated toward the object while moving on the surface of the object.
A detector that detects the timing of the emission of the electromagnetic wave for each predetermined movement distance,
A scanning state acquisition unit that acquires information on the moving speed during scanning according to the timing, and a scanning state acquisition unit.
When the movement speed predicted based on the information on the movement speed is faster than a predetermined value, a plurality of processes for detecting the buried object performed on the data on the reflected wave acquired at each timing are divided. A buried object detection device equipped with a processing division unit that performs pipeline processing. The scanning state acquisition unit acquires the time of the timing interval as information regarding the movement speed.
The processing division unit performs pipeline processing when the predicted time predicted from the time of the timing interval is smaller than a predetermined value.
The buried object detection device according to claim 1. The processing division unit increases the number of processing to be divided as the moving speed increases.
The buried object detection device according to claim 1 or 2. The processing division unit divides the memory, divides the processing for detecting the buried object according to the number of the divided memories, and performs the pipeline processing.
The buried object detection device according to any one of claims 1 to 3. A reflected wave acquisition unit that acquires data related to the reflected wave of the electromagnetic wave radiated at each timing, and a reflected wave acquisition unit.
A reflected wave analysis unit that detects the peak of the signal intensity in the depth direction of the object at each timing based on the signal intensity in the depth direction of the object in the data related to the reflected wave obtained at each timing. When,
Further, a buried object determination unit for determining the presence or absence of an embedded object based on the peak of the signal strength is provided.
When performing the pipeline processing, the processing division unit divides the processing by the reflected wave acquisition unit, the processing by the reflected wave analysis unit, and the processing by the buried object determination unit into at least two or more.
The buried object detection device according to any one of claims 1 to 4. Further provided with a buried object registration unit for registering the determined position of the buried object,
When performing the pipeline processing, the processing division unit performs at least two processes: a process by the reflected wave acquisition unit, a process by the reflected wave analysis unit, a process by the buried object determination unit, and a process by the buried object registration unit. Divide into the above,
The buried object detection device according to claim 5. A first control module having the reflected wave acquisition unit and a transmission unit for transmitting data related to the acquired reflected wave.
A second control module having the reflected wave analysis unit, the buried object determination unit, the buried object registration unit, and a receiving unit for receiving data related to the reflected wave is provided.
When performing the pipeline processing, the processing division unit performs processing by the reflected wave acquisition unit, processing by the reflected wave analysis unit, processing by the buried object determination unit, processing by the buried object registration unit, and processing by the transmission unit. Is divided into at least two,
The buried object detection device according to claim 6. It is a buried object detection method for detecting an embedded object in the object by using data on a reflected wave of an electromagnetic wave radiated toward the object while moving on the surface of the object.
A detection step that detects the timing of emission of the electromagnetic wave for each predetermined travel distance, and
A scanning state acquisition step for acquiring information on the moving speed during scanning according to the timing, and a scanning state acquisition step.
When the movement speed predicted based on the information on the movement speed is faster than a predetermined value, a plurality of processes for detecting the buried object performed on the data on the reflected wave acquired at each timing are divided. A method for detecting buried objects, including a processing division step for performing pipeline processing.

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