JP6984630B2 - 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 the buried object detection device, as shown in FIG. 37 (a), since the electromagnetic wave radiated from the transmitting antenna has a spread in the depth direction, the reflected wave (RF1) from the reinforcing bar 1000 at the position P1001. To receive. Therefore, the distance from the position P1001 to the reinforcing bar 1000 is displayed as D1. Then, at the position P1002, the distance to the reinforcing bar 1000 is displayed as closest to D2, and at the position P1003, the distance from the position P1003 to the reinforcing bar 1000 is displayed as D3, which is farther than D2.

Therefore, the waveform of the reflected wave by the reinforcing bar 1000 becomes the chevron waveform 1004.
When the reflected wave of the buried object has a perfect chevron waveform, the buried object detection device detects the apex of the buried object as the buried object.

Japanese Patent No. 5789088

However, as shown in FIG. 37 (b), when the end of the chevron waveform 1006 of the reflected wave received from the shallow buried object 1005 overlaps near the apex of the chevron waveform 1007 of the reflected wave received from the deeper buried object 1008. In some cases, the chevron waveform of the reflected wave from the deep buried object 1008 became incomplete, and the buried object 1008 could not be detected.
An object of the present invention is to provide a buried object detecting device and a buried object detecting method capable of detecting a buried object even from a reflected wave having an incomplete shape.

The buried object detection device according to the first invention is a data processing device for detecting 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. It includes a receiving unit, a signal intensity peak detecting unit, a grouping unit, an interpolating unit, and a buried object detecting unit. The receiving unit receives data related to the reflected wave at each timing associated with the movement. The signal strength peak detection unit detects the peak of the signal strength in the depth direction of the object at each timing based on the signal strength in the depth direction of the object at the timing. The grouping unit groups the depth positions of a plurality of signal strength peaks that are continuous within a predetermined interval in the moving direction among the depth positions of the signal strength peaks detected at each timing. The interpolation unit interpolates between the groups when a predetermined interpolation condition is satisfied for the plurality of groups detected by the grouping unit to form one group. The buried object detection unit detects buried objects based on the group.

As a result, an incomplete group that is interrupted in the middle can be interpolated into one group, so that the buried object can be detected from the reflected wave having an incomplete shape. That is, even if the end of the group based on the reflected wave received from the shallow buried object overlaps near the apex of the group based on the reflected wave received from the deeper buried object and the group related to the deep buried object is interrupted in the middle. It is possible to interpolate the part. Therefore, the presence of deep buried objects can be detected.

The buried object detecting device according to the second invention is the buried object detecting device according to the first invention, and the predetermined interpolation condition is set to another within a predetermined region from the first end in the moving direction of the predetermined group. There is a second end opposite to the direction of movement of the group. The interpolation unit sets a predetermined group and another group into one group when a predetermined interpolation condition is satisfied.
Thereby, when the end of a predetermined group and the end of another group are within a predetermined range, the ends can be connected to each other and the buried object can be determined as one group.

The buried object detection device according to the third invention is the buried object detection device according to the second invention, and the interpolation unit includes a range calculation unit and an interpolation determination unit. The range calculation unit calculates the upper limit of the slope and the lower limit of the slope based on the slope in the predetermined range from the first end of the predetermined group. The interpolation determination unit determines whether or not the second end exists in a predetermined region which is within a predetermined range from the first end in the moving direction and is within the range of the upper limit of the inclination and the lower limit of the inclination.
As a result, when the end of a predetermined group is interrupted but the end of another group exists in the range where it can be determined that it continues in the moving direction, it is determined that the end is interrupted and the interrupted part is interpolated. Can be done. Therefore, it is possible to accurately detect the buried object by performing interpolation as a group based on the reflected wave of one buried object.

The buried object detecting device according to the fourth invention is the buried object detecting device according to the first invention, and the buried object detecting unit includes a depth position peak detecting unit and a determination unit. The depth position peak detection unit detects the peak at the depth position of the group. The determination unit determines the presence of the buried object from the peak at the detected depth position.
This makes it possible to determine the presence of buried objects based on the peak at the depth position.

The buried object detecting device according to the fifth invention is the buried object detecting device according to the first invention, and the depth position peak detecting unit satisfies a predetermined condition in a plane in a moving direction and a depth direction. Determine if it is. The determination unit determines the existence of the buried object when it is determined that the group satisfies the predetermined condition.
Thereby, it can be determined that the buried object exists when, for example, the chevron shape is satisfied as a predetermined condition.

The buried object detecting device according to the sixth invention is the buried object detecting device according to the fifth invention, and the predetermined condition is that the differential value is positive when the group is differentiated in the planes in the moving direction and the depth direction. The first condition that the value of the value passes through zero and becomes a negative value, the second condition that the group exists in a predetermined range or more in each of the moving direction and the opposite direction from the depth position of zero in the first condition, and the zero This is the third condition in which the area of the differential value in the predetermined range from the depth position to the moving direction and the opposite direction is equal to or larger than the predetermined threshold value. The depth position peak detection unit determines whether or not the group satisfies the first condition, the second condition, and the third condition, and if the first condition, the second condition, and the third condition are satisfied, the depth position peak detection unit is zero. The depth position is detected as the peak of the depth position of the group.
When the three conditions are satisfied as described above, it can be determined that the waveform has a mountain shape, for example, and the position of the buried object can be detected by detecting the peak position of the waveform of the mountain shape.

The buried object detecting device according to the seventh invention is the buried object detecting device according to the sixth invention, and the determination unit has a plurality of peaks at the depth position in the depth direction within a predetermined range in the moving direction. If so, the peak at the shallower depth is determined to be the position of the buried object.
As a result, the position of the shallower peak can be set as the position of the buried object.

The buried object detection device according to the eighth invention is the buried object detection device according to the seventh invention, and the determination unit is determined when there is only one peak at the depth position within a predetermined range. The peak at the detected depth position is not determined to be the position of the buried object.
This makes it possible to reduce erroneous detection due to noise or the like.

The buried object detecting device according to the ninth invention is the buried object detecting device according to any one of the first to eighth inventions, and further includes a first-order differential processing unit. The first derivative processing unit detects the difference in the change in the signal strength at a predetermined depth position from the signal strength at the previous depth position in the depth direction or the surface direction vice versa.
This makes it possible to extract changes in signal strength due to the influence of buried objects.

The buried object detecting device according to the tenth invention is the buried object detecting device according to the ninth invention, and the signal intensity peak detecting unit has a depth position in which the difference changes from a decrease to an increase and a difference decreases from an increase. At least one of the depth positions changing to is detected as the peak of the signal strength.
In this way, the peak of the signal strength can be detected by using the data of the increase / decrease in the signal strength.

The buried object detecting method according to the eleventh invention includes a receiving step, a signal strength peak detecting step, a grouping step, an interpolation step, and a buried object detecting step. The reception step receives data on the reflected wave at each timing associated with the movement. The signal strength peak detection step detects the peak of the signal strength in the depth direction of the object at each timing based on the signal strength in the depth direction of the object at the timing. In the grouping step, among the depth positions at the peaks of the signal strength detected at each timing, the depth positions at the peaks of a plurality of signal strengths that are continuous within a predetermined interval in the moving direction are grouped. In the interpolation step, for a plurality of groups detected by the grouping unit, if a predetermined interpolation condition is satisfied, the interpolated groups are interpolated into one group. The buried object determination step detects buried objects based on the group.

As a result, an incomplete group that is interrupted in the middle can be interpolated into one group, so that the buried object can be detected from the reflected wave having an incomplete shape. That is, even if the end of the group based on the reflected wave received from the shallow buried object overlaps near the apex of the group based on the reflected wave received from the deeper buried object and the group related to the deep buried object is interrupted in the middle. It is possible to interpolate the part. Therefore, the presence of deep buried objects can be detected.

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 detecting a buried object even from a reflected wave having an incomplete shape.

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 figure which shows the data of the reflected wave acquired by the MPU of FIG. The block diagram which shows the structure of the main control module of FIG. (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. The figure for demonstrating the reason why a part of the chevron waveform of the group (a)-(d) is missing. The figure which shows the image data which the chevron waveform was interrupted in the middle, and two groups were detected. The figure which shows the outline of the interpolation process by the interpolation part of FIG. (A)-(d) The figure for demonstrating the process of determining a predetermined range by the range calculation part of FIG. (A)-(c) The figure which shows the specific example of the method of calculating the upper limit differential value and the lower limit differential value in a predetermined range. 16 is a diagram for explaining interpolation processing in a predetermined range set in FIGS. 16A to 16C. (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) A diagram showing an example of data in which the middle of the chevron waveform is missing, and (b) a diagram showing an example of data obtained by interpolating the data of FIG. 22 (a). The flow chart which shows the impulse control processing of the buried object detection apparatus of FIG. The flow diagram which shows the processing of the main control module of the buried object detection apparatus of FIG. The flow chart which shows the preprocessing of FIG. 24. The flow chart which shows the moving average processing of FIG. The flow diagram which shows the difference processing of FIG. FIG. 5 is a flow chart showing a first-order differential process of the difference result of FIG. 25. The flow chart which shows the chattering removal process of FIG. The flow chart which shows the peak detection processing of FIG. FIG. 2 is a flow chart showing a buried object determination process of FIG. 24. The flow chart which shows the grouping process of FIG. FIG. 3 is a flow chart showing a buried object determination process of FIG. 31. The flow chart which shows the chevron waveform interpolation processing of FIG. The flow chart which shows the chevron waveform vertex detection process of FIG. 31. FIG. 3 is a flow chart showing a buried object determination process of FIG. 31. (A), (b) The figure for demonstrating the conventional problem.

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 depth direction is indicated by the arrow B, and the surface direction is indicated by the arrow C.

The buried object detection device 1 includes a main body portion 2, a handle 3, a wheel 4, an impulse control module 5, a main control module 6, an encoder 7, and a display unit 8.
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.

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

The 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.

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 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 a predetermined measurement position (the position where the input from the encoder 7 is received) in the moving directions A1 and A2 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. Each time the data for one line is accumulated, the control unit 10 transmits the RF (Radio Frequency) data for one line to the main control module 6.

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.

(Main control module 6)
FIG. 5 is a block diagram showing the configuration of the main control module 6. The main control module 6 includes a receiving unit 21, an RF data management unit 22, a preprocessing unit 23, a buried object determination unit 24, a determination result registration unit 25, and a display control unit 26.
The 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 receiving unit 21.
The preprocessing unit 23 detects the peak of the signal strength for each 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 pretreatment unit 23, and specifies the position thereof.

The determination result registration unit 25 registers the position of the buried object determined 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 A1 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.

(Pretreatment unit 23)
As shown in FIG. 5, the preprocessing unit 23 includes a moving average processing unit 33, a difference processing unit 32, a first-order differential processing unit 34 (an example of a difference processing unit), a chattering removing unit 35, and a peak detection unit 36. (An example of a signal strength peak detection unit) 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. 6A is a diagram showing image data before the difference processing is performed, and FIG. 6B 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. 6 (b).
FIG. 7A is a partially enlarged view of the image data subjected to the difference processing, and FIG. 7B is a diagram showing the signal strength of the RF data of the line L1 of FIG. 7A. The horizontal axis of FIG. 7B indicates the depth position, and is deepened along the arrow direction. The vertical axis of FIG. 7B 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. 7A is shown by P1 to P5. These P1 to P5 are also shown in FIG. 7 (b). Also, in FIG. 7B, 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. 8 is an enlarged view between P10 and P3 of FIG. 7 (b). FIG. 9 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. 9 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. 8, 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. 9 shows the graph 151 of the portion surrounded by the 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 due to noise occurs in the sequence number 11. 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 (+/-) values of the sequence number 34 correspond to the changes between the data D3 to D4 in FIG. 9, and the difference and change (+/-) values of the sequence number 35 correspond to the changes 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. 9, 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. 9, 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. 7), 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. 7, 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)
As shown in FIG. 5, the buried object determination unit 24 includes a grouping unit 51, a chattering removing unit 52, an interpolation unit 53, and a buried object detecting 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. The interpolation unit 53 performs interpolation processing on a plurality of groups after chattering is removed. 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 of 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. 10 is a diagram showing image data after preprocessing by the preprocessing unit 23. In FIG. 10, the line L2 acquired this time is shown. 11 (a) to 11 (d) are diagrams for explaining the processing by the grouping unit 51.

FIG. 11A 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. 10). 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. 11B 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. 11B, the position of the peak rises (moves to the shallow side) in the moving direction. FIG. 11C 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. 11 (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. 11D, 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. 10).

As described above, the grouping unit 51 groups the peak positions. In FIG. 10, 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.

(Interpolation unit 53)
Before explaining the interpolation unit 53, the reason why the group is interpolated by the interpolation unit 53 will be described.
The buried object detection unit 58 detects the buried object based on the shape of the group after the chattering is removed. As will be described in detail later, the buried object detection unit 58 can detect the buried object when the shape of the group in the plane in the moving direction A1 and the depth direction B is a chevron waveform.
However, if the end of the group based on the reflected wave received from the shallow buried object overlaps near the apex of the group based on the reflected wave received from the deeper buried object, the chevron waveform of the reflected wave from the deep buried object Although it is incomplete, the buried object can be detected by performing the interpolation processing of the present embodiment.

FIG. 12 is a diagram for explaining the reason why a part of the chevron waveform of the group is missing.
FIG. 12B shows image data of the reflected wave when the buried object detecting device 1 receives the reflected wave from the buried object 201 at the receiving position P1 shown in FIG. 12A. In the image data, as described above, the magnitude of the reflected wave is shown in gray scale (white when it is large and black when it is small). The reflected waveform by the buried object 201 is displayed as, for example, a black-and-white chevron waveform. As shown in FIG. 12B, the above-mentioned peak detection unit 36 has −E or more and + E or less among the extracted downward peaks (which can be said to be black peaks) and upward peaks (which can also be said to be white peaks). Those outside the threshold range of are detected as peaks (peaks 1 to 7 shown in FIG. 12B).

FIG. 12 (d) shows image data of the reflected wave when the buried object detecting device 1 receives the reflected wave from the buried object 201 at the receiving position P2 shown in FIG. 12 (c). As shown in FIG. 12 (d), when there are a plurality of buried objects (buried objects 201, 202), for example, the time T1 at which the white with high intensity is reflected from the buried object 201 and the black with low intensity from the buried object 202 When the reflected time T1 is the same, white and black are added together to cancel each other out and become gray, so that it is within the threshold range and cannot be detected as a peak (see Z in FIG. 12 (d)).

Therefore, as shown in FIG. 13, the chevron waveform is interrupted in the middle and two groups are detected. FIG. 13 is a diagram showing image data in which the chevron waveform is interrupted in the middle and two groups, group G11 and group G12, are detected. The interrupted portion is indicated by 203.
The interpolation unit 53 interpolates between the groups when a predetermined interpolation condition is satisfied with respect to the group after chattering removal to form one group.

The interpolation unit 53 includes a range calculation unit 54 and an interpolation determination unit 55.
The range calculation unit 54 determines a predetermined range F for each group after chattering removal, with reference to an end point on the movement direction A1 side of the group. If the end points of other groups exist within the predetermined range F, the interpolation determination unit 55 sets the two groups into one group.
FIG. 14 is a diagram for explaining the interpolation process. In FIG. 14, the range calculation unit 54 determines the predetermined range F with reference to the end point Qe on the movement direction A1 side of the group G11. In FIG. 14, the interpolation determination unit 55 groups the group G11 and the group G12 as one group because the end point Qs on the side opposite to the moving direction A1 of the group G12 exists in the predetermined range F.

15 (a) to 15 (d) are diagrams for explaining a process of determining a predetermined range F by the range calculation unit 54.
FIG. 15A shows a chevron waveform as a result of grouping. The range calculation unit 54 differentiates the group G11 shown in FIG. 15A. FIG. 15B is a diagram showing a group G11'that is a derivative of the group G11. The range calculation unit 54 predicts possible values after the end point Qe from the differential value.

Specifically, the range calculation unit 54 sets the value obtained by merging the maximum value of the differential values of the past 8 points as the upper limit differential value (see the upper limit differential value UL of FIG. 15C), and sets the value of the past 8 points. The value obtained by merging the minimum value of the differential value is defined as the lower limit differential value (see the lower limit differential value LL in FIG. 15 (c)).
16 (a) to 16 (c) are diagrams showing a specific example of a method for calculating the upper limit differential value UL (an example of the upper limit of the slope) and the lower limit differential value LL (an example of the lower limit of the slope).

FIG. 16A is a diagram showing the shape of the original group. x indicates the distance in the moving direction and indicates the position of the pixel. In the table shown in FIG. 16A, x = 70 is the endpoint Qe of the group G11. F (x) shown in FIG. 16 (a) indicates a position in the depth direction. The range calculation unit 54 calculates f'(x) shown in FIG. 16 (a). f'(x) can be obtained by the equation of f'(x) = (f (x + h) -f (x-h)) / 2h (central derivative).

Next, the range calculation unit 54 extracts the maximum value of the differential values of the past eight points. In the table shown in FIG. 16 (a), it is 0.01. The range calculation unit 54 adds a merge to this 0.01 and calculates the upper limit differential value as 1.01. Then, based on the equation f (N) = f'(x) (N is x + 1 to x + 11), as shown in the table of FIG. 16B, the range calculation unit 54 has the upper limit differential value of 71 to 81. Is 1.01. FIG. 15 (c) shows the upper limit differential UL connecting the upper limit differential values. Further, the range calculation unit 54 integrates the upper limit differential value using the equation f (N2) = 2 × f ′ (N2-1) + f (N) (N2 is x + 2 to x + 11) in each pixel. The value of the upper limit value f (x) is calculated. FIG. 15D shows an upper limit waveform UM connected by the calculated upper limit value f (x).

On the other hand, the range calculation unit 54 extracts the minimum value of the differential values of the past eight points. In the table shown in FIG. 16 (a), it is −1.25. The range calculation unit 54 adds a merge to this −1.25 and calculates the lower limit differential value as -2.25. Then, based on the equation f (N) = f'(x) (N is x + 1 to x + 11), as shown in the table of FIG. 16 (c), the range calculation unit 54 has the lower limit differential value of 71 to 81. Is -2.25. FIG. 15C shows a lower limit derivative LL in which lower limit derivative values are connected. Further, the range calculation unit 54 integrates the lower limit differential value using the equation f (N2) = 2 × f ′ (N2-1) + f (N) (N2 is x + 2 to x + 11) in each pixel. The value of the lower limit value f (x) is calculated. FIG. 15D shows a lower limit waveform LM connected to the calculated lower limit value f (x).

As described above, when the chevron waveform is interrupted in the middle, it is predicted that it continues in the range of the upper limit waveform UM and the lower limit waveform LM.
In the interpolation determination unit 55, between the upper limit waveform UM and the lower limit waveform LM, the end Qs of the other group G12 is within a predetermined range F within the range of 10 pixels in the moving direction A1 from the end Qe (an example of the first end). Determine if it exists. The presence of the end of another group in the predetermined range F is an example of a predetermined interpolation condition. As shown in FIG. 17, when the end point Qs of another group G12 (an example of the second end) exists, the end point Qe of the group G11 and the end point Qe of the group G12 are interpolated between the group G11 and the group G12. Connecting. If the end of the other group does not exist within the predetermined range F from the end Qe, the interpolation determination unit 55 does not perform interpolation to connect the end Qe with the other group.

(Buried object detection unit)
The buried object detection unit 58 detects the buried object for both the group interpolated by the interpolation unit 53 and the group not interpolated.
The buried object detection unit 58 includes a chevron waveform apex detection unit 56 (an example of a depth position peak detection unit) 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. 18A is a diagram showing the positions of a plurality of grouped peaks. The chevron waveform vertex detection unit 56 differentiates the data shown in FIG. 18A, and determines that the first condition is satisfied when the differential data becomes negative from plus via zero. FIG. 18B is a diagram showing data obtained by differentiating FIG. 18A. In FIG. 18B, 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. 18A.

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. FIG. 19 (a) is a diagram showing the second condition in FIG. 18 (a). FIG. 19 (b) is a diagram showing the second condition in FIG. 18 (b). As shown in FIGS. 19 (a) and 19 (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. 19 (a) and 19 (b) and FIG. The data shown in FIG. 19B 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. 19B, and determines whether or not the calculated area is equal to or larger than a predetermined threshold value. FIG. 20A 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. 20B 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. 21 (a) to 21 (c) are diagrams showing an example of vertex grouping. In FIG. 21, the white squares indicate the vertices of the white peak, and the black squares indicate the vertices of the black peak.
In FIG. 21 (a), the white peak and the black peak are shown in order from the shallowest within the range of the vertex grouping. In FIG. 21B, 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. 21 (c), only black peaks are shown within the range of vertex grouping.

In this case, in FIG. 21A, the position of the shallowest white peak (shown as P20) is registered as the position of the buried object. Further, in FIG. 21B, 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. 21 (c), since there is only one peak in the vertex group range, it is not registered as the position of the buried object.

(Judgment of chevron waveform by interpolation)
An example of determining a chevron waveform by performing interpolation by the interpolation unit 53 will be described.
FIG. 22A is a diagram showing an example of data in which the middle of the chevron waveform is missing.
The upper part of FIG. 22A is a table showing data. The middle row is a diagram showing a graph of data in the upper row (horizontal axis x, vertical axis f (x)), and is divided into group G11 and group G12. The lower row is a diagram showing a graph of data in the upper row (horizontal axis x, vertical axis f'(x)). The graph of the data in the lower row is a derivative of the graph of the data in the middle row. In the lower graph of FIG. 22A, the derivative of the group G11 is shown as G11'and the derivative of the group G12 is shown as G12'.

In this way, since it is divided into two, the graph of the differential value does not pass through zero, does not correspond to the first condition, and is not recognized as a chevron waveform.
However, as shown in the upper table of FIG. 22 (b), by performing interpolation, the group G11 and the group G12 are combined into one group as shown in the middle graph of FIG. 22 (b). Is detected by the chevron waveform apex detection unit 56. As a result, as shown in the lower graph of FIG. 22B, the differential value (G13') becomes negative from plus through zero, so that the first condition is satisfied and the other second condition is satisfied. And the third condition are satisfied, the chevron waveform apex detection unit 56 can detect the chevron waveform with the group G11 and the group G12 as one group G13.

The deeper the depth of the buried object, the obtuse angle (flatter) the chevron waveform tends to be, and the shallower the depth, the sharper the angle (steeper). Since it is created based on the differential value of, the deeper the depth of the buried object, the narrower the range of the upper and lower limit values, and the shallower the depth, the wider the range of the upper and lower limit values. Therefore, the predetermined range F, which is the predicted range in which the waveform is expected to grow when the waveform is assumed to continue, can be changed according to the depth of the buried object, that is, according to the shape of the chevron waveform.

(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. 10, 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.

<Operation>
Next, the operation of the buried object detection device 1 according to the embodiment of the present invention will be described.
(Impulse control module processing)
FIG. 23 is a flow chart showing the impulse control process.
When the impulse control module processing is started, in step S1, when the input is input from the encoder 7, the impulse output control is started in step S2, and the impulse output control is started from the transmitting antenna 11 based on the pulse from the pulse generating unit 13 ( For example, an electromagnetic pulse is output at 1 MHz).

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 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.
Next, when the buried object detection device 1 is moved in the moving direction A by the operator, there is an input from the encoder 7, control of steps S2 to S7 is performed, and data for the next one line is acquired. It is transmitted to the main control module 6.

(Main control module processing)
FIG. 24 is a flow chart showing the processing of the main control module 6.
First, when the receiving unit 21 receives RF data for one line from the impulse control module 5 in step S11, the preprocessing unit 23 performs preprocessing before determining the buried object in step S12.
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.

(Preprocessing)
FIG. 25 is a flow chart showing the preprocessing in step S12 of FIG. 24.
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. 25 will be described. FIG. 26 is a flow chart showing the moving average processing.
When the moving average processing is disclosed, 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. 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. 25 will be described. FIG. 27 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. 6 (b).

(First derivative processing of difference result)
Next, the first derivative processing of the difference result in step S24 of FIG. 25 will be described. FIG. 28 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. 9 is calculated.

(Chattering removal process)
Next, the chattering removal process in step S25 of FIG. 25 will be described. FIG. 29 is a flow chart showing a 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. 9 can be obtained.

(Peak detection processing)
Next, the peak detection process in step S26 of FIG. 25 will be described. FIG. 30 is a flow chart showing a 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 the data of sequence number 1 in steps S72, S73, and S74, 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. 9 can be detected as peaks.

(Buried object judgment process)
Next, the buried object determination process shown in step S13 of FIG. 24 will be described. FIG. 31 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 pretreatment 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 interpolation unit 53 performs the chevron waveform interpolation processing by connecting the groups when a predetermined condition is satisfied, such as when the chevron waveform is interrupted in the middle. This step S83 corresponds to an example of the interpolation step.
Next, in step S84, the chevron waveform apex detection unit 56 detects the apex of the chevron waveform when the group after the chevron waveform interpolation processing satisfies a predetermined chevron waveform.

Next, in step S85, a process of determining the buried object is performed based on the vertices of the plurality of chevron waveforms. Steps S84 and S85 correspond to an example of the buried object detection step.
Next, in step S86, the display control unit 26 marks the position of the peak detected by the chevron waveform apex detection unit 56 (for example, a cross mark, a circle mark, etc.) and causes the display unit 8 to display the mark.

(Grouping process of peak detection results)
The grouping process of the peak detection result in step S81 of FIG. 31 will be described. FIG. 32 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. 11 (a) to 11 (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. 31 will be described. FIG. 33 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 other selected groups.
In this way, the flow is repeated until the processing of step S112 is performed for all the grouped results.

(Yamagata waveform interpolation processing)
Next, the chevron waveform interpolation processing shown in step S83 of FIG. 31 will be described. FIG. 34 is a flow chart showing the chevron waveform interpolation processing.
When the chevron waveform interpolation process is started, in step S121, the interpolation unit 53 selects one from a plurality of grouped groups.

Then, in step S122, the interpolation unit 53 reads out one of the selected chattering removal processing groups stored in the RF data management unit 22.
Next, in step S123, the range calculation unit 54 differentiates the data of the selected group, and sets the value obtained by merging the maximum value of the differential values of the past eight points as the upper limit differential value (FIG. 15 (c)). (Refer to the upper limit differential value UL), and the lower limit differential value (see the lower limit differential value LL in FIG. 15 (c)) is the value obtained by merging the minimum values of the past eight differential values. Then, the range calculation unit 54 sets a range of 10 pixels in the moving direction A1 from the end point Qe sandwiched between the upper limit differential value and the lower limit differential value as the predetermined range F.

Next, in step S124, the interpolation determination unit 55 confirms whether or not the end points of other groups exist within the predetermined range F. When the end points of other groups exist in the predetermined range F, in step S125, the interpolation determination unit 55 groups the selected group and the group having the end points in the predetermined range F.
Then, in step S126, the interpolation unit 53 confirms whether or not the chevron waveform interpolation processing has been performed for all the groups, and if the processing has not been performed for all the groups, the control step. Returning to S121, another group is selected. Then, the chevron waveform interpolation processing is performed on the other selected groups.
If the end points of the other groups do not exist within the predetermined range F in step S124, the selected group remains as it is, and the control proceeds to step S126.

(Yamagata waveform vertex detection processing)
Next, the chevron waveform vertex detection process shown in step S84 of FIG. 31 will be described. FIG. 35 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 after the chevron waveform interpolation process.
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 S85 of FIG. 31 will be described. FIG. 36 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. 31, regarding the position of the buried object registered by the determination result registration process, the display control unit 26 controls the display unit 8 in step S86 to display the buried object (marks such as × and ○). 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, as a control method of the buried object detection device 1 and the main control module 6 (an example of the data processing device), an example of carrying out according to the flowcharts shown in FIGS. 23 to 36 has been described. Not limited.

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. 23 to 36.
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 usage mode 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 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.

(C)
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.
(D)
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 detect buried objects even from reflected waves having an incomplete shape, and are useful for detecting buried objects in concrete. be.

1 Buried object detection device 36 Peak detection unit 51 Grouping unit 53 Interpolation unit 58 Buried object detection unit 61 Receiver unit

Claims (11)

A buried object detection device for detecting an embedded object in the object by using data on reflected waves of electromagnetic waves radiated toward the object while moving on the surface of the object.
A receiver that receives data related to reflected waves at each timing associated with movement,
A signal strength peak detection unit that detects the peak of the signal strength in the depth direction of the object at each timing based on the signal strength in the depth direction of the object at the timing.
Of the depth positions at the peaks of the signal strength detected at each of the timings, a grouping unit that groups the depth positions at a plurality of peaks of the signal strength continuous within a predetermined interval in the moving direction. When,
An interpolation unit that interpolates between the groups to form one group when a predetermined interpolation condition is satisfied for the plurality of groups detected by the grouping unit.
A buried object detection unit for detecting the buried object based on the group.
Buried object detector. The predetermined interpolation condition is that the second end of the other group on the opposite side of the moving direction exists in the predetermined region from the first end of the predetermined group in the moving direction.
When the predetermined interpolation condition is satisfied, the interpolation unit sets the predetermined group and the other group into one group.
The buried object detection device according to claim 1. The interpolation unit is
A range calculation unit that calculates the upper and lower limits of the slope based on the slope in the predetermined range from the first end of the predetermined group.
An interpolation determination unit for determining whether or not the second end exists in the predetermined region which is within a predetermined range from the first end in the moving direction and is within the range of the upper limit of the inclination and the lower limit of the inclination. , Have,
The buried object detection device according to claim 2. The buried object detection unit is
A depth position peak detection unit that detects a peak at the depth position of the group,
It has a determination unit for determining the presence of the buried object from the detected peak at the depth position.
The buried object detection device according to claim 1. The depth position peak detecting unit determines whether or not the group satisfies a predetermined condition in a plane in the moving direction and the depth direction, and determines whether or not the group satisfies a predetermined condition.
When the determination unit determines that the group satisfies the predetermined condition, the determination unit determines the existence of the buried object.
The buried object detection device according to claim 4. The predetermined condition is
The first condition that the differential value changes from a positive value to a negative value through zero when the group is differentiated in the planes in the moving direction and the depth direction.
A second condition in which the group exists in a predetermined range or more in each of the moving direction and the opposite direction from the zero depth position in the first condition, and
The third condition is that the area of the differential value in a predetermined range in the moving direction and the opposite direction from the zero depth position is equal to or larger than a predetermined threshold value.
The depth position peak detection unit determines whether or not the group satisfies the first condition, the second condition, and the third condition, and determines the first condition, the second condition, and the third condition. When satisfied, the zero depth position is detected as the peak of the depth position of the group.
The buried object detection device according to claim 5. When a plurality of peaks at the depth position exist in the depth direction within a predetermined range in the movement direction, the determination unit determines that the shallower peak at the depth position is the position of the buried object.
The buried object detection device according to claim 6. When the determination unit has only one peak at the depth position within the predetermined range, the determination unit does not determine the detected peak at the depth position as the position of the buried object.
The buried object detection device according to claim 7. Further provided with a first-order differential processing unit for detecting the difference in the change in the signal strength at the predetermined depth position from the signal strength at the previous depth position in the depth direction or the surface direction vice versa. ,
The buried object detection device according to any one of claims 1 to 8. The signal strength peak detection unit is
At least one of the depth position where the difference changes from decrease to increase and the depth position where the difference changes from increase to decrease is detected as the peak of the signal strength.
The buried object detection device according to claim 9. It is a buried object detection method for detecting an embedded object in the object by using data on reflected waves of electromagnetic waves radiated toward the object while moving on the surface of the object.
A reception step that receives data related to reflected waves at each timing associated with movement,
A signal strength peak detection step for detecting the peak of the signal strength in the depth direction of the object at each timing based on the signal strength in the depth direction of the object at the timing.
Of the depth positions at the peaks of the signal strength detected at each of the timings, a grouping step in which the depth positions at a plurality of peaks of the signal strength continuous within a predetermined interval in the moving direction are grouped. When,
An interpolation step of interpolating between the groups to form one group when a predetermined interpolation condition is satisfied for the plurality of groups detected by the grouping step.
A buried object detection step for detecting the buried object based on the group.
Buried object detection method.

Images