JP6789042B2 - How to identify the location of the leak - Google Patents

Description

The present invention relates to a method for creating analysis data, a noise filter, a method for determining the presence or absence of water leakage, a method for identifying a water leakage location, and a method for measuring vibration data. In particular, it is a method of creating analysis data related to abnormal sound, a noise filter related to abnormal sound, a method of determining the presence or absence of water leakage related to abnormal sound, a method of identifying a leak location related to abnormal sound, and a method of measuring vibration data related to abnormal sound.

Conventionally, as a method of determining the position of leakage in a pipe, there is a method of detecting vibration with a sensor, generating a cross-correlation function from the detected signal, and specifying the position of abnormal sound generation using the propagation speed of sound. ..

For example, in Patent Document 1 (Japanese Unexamined Patent Publication No. 8-226856), in a noisy environment where excavation is not easy, an obstructive noise source is eliminated by a non-intrusive method, and the leakage of the conduit is accurately performed. Determining Positioning A method of locating a leak in a conduit is disclosed.

The method of determining the leak position of the conduit described in Patent Document 1 (Japanese Unexamined Patent Publication No. 8-226856) is as follows: a) A first sensor arranged apart along the conduit in order to obtain a raw plot of the first time difference. From the step of calculating the cross-correlation function from the leak noise data obtained from the pair and b) from the leak noise data obtained from the second sensor pair spaced apart along the conduit to obtain a raw plot of the second time difference. The step of calculating the cross-correlation function, c) the step of smoothing each raw plot of the time difference to obtain the time difference peak of each plot, d) the first time difference peak, and the known interval between the first sensor pairs. From the step of determining the propagation velocity for leakage noise of the conduit by using, and from the step of determining the position of the leakage by using e) the propagation velocity, the second time difference peak, and the interval between the second sensor pairs. It determines the location of the leak in the conduit, which is characterized by

Further, Patent Document 2 (Japanese Patent Laid-Open No. 2003-502678) describes a method and an apparatus for detecting and locating a leak in a fluid transport pipe by using a technique based on correlation.

The method of detecting and locating a common signal described in Patent Document 2 (Japanese Patent Laid-Open No. 2003-502678) is a method of detecting and locating a common signal of two input signals by using a technique based on correlation. , A step of preparing at least one filter by analyzing the phase of the input signal in the frequency domain, a step of filtering the input signal in the frequency domain using at least one of the above filters, and a filtered signal. It is the detection of a common signal consisting of the steps of executing the mutual correlation of.

Further, in Patent Document 3 (Japanese Unexamined Patent Publication No. 11-117356), when detecting a leak in a water pipe of a water supply by measuring a leak sound, the conventional method is easily affected by noise and the detection is insufficient. It is possible to detect water leaks with higher accuracy than the conventional method, which is resistant to noise, and can centrally monitor water leaks in water pipes that can accurately identify the location of water leaks and water leaks in multiple water pipes using this detection method. A leak detection system is described.

In the water leakage detection system described in Patent Document 3 (Japanese Unexamined Patent Publication No. 11-117356), it is a method for detecting a water leakage position within a predetermined section of a water distribution pipe, and both ends of a water leakage detection section L set in the water distribution pipe. in part, by disposing the leak noise detection sensor S _1, S ₂ for detecting the leak noise generated from the water leakage points in between the compartment respectively, each sensor S ₁ is leak noise by simultaneous measurement of the leak noise, S The time difference τ until reaching ₂ is obtained, and the leakage position d from one of the water leakage sound detection sensors is set from the distance L between the sensors, the propagation time difference τ of the leak sound, and the sound velocity C in the water, and d = (L−). It is characterized in that the leak position is detected by calculating from Cτ) / 2.

Japanese Unexamined Patent Publication No. 8-226856 Special Table 2003-502678 Japanese Unexamined Patent Publication No. 11-117356

In this way, the water supply or gas pipes are aging, and fluid leakage from defects has become a problem. Therefore, it is conceivable to apply the method described in Patent Document 1 (Japanese Patent Laid-Open No. 8-226856) or Patent Document 2 (Japanese Patent Laid-Open No. 2003-502678) to identify the defect position.

However, at the actual leakage site, there is a problem that external noise such as automobile traffic noise and other noise are input in addition to the abnormal noise.
Further, when the amount of leaking fluid is small and the abnormal noise is small, there is a problem that the leaking position and the vibration sensor position are separated from each other and the detected abnormal noise is small.
Therefore, the method described in Patent Document 2 attempts to detect abnormal sounds by enhancing the peak of cross-correlation by removing or blocking frequencies that do not exhibit sufficient coherence.

However, in the method described in Patent Document 2, noise having an extremely high correlation is included as a result of incomplete digitization, and therefore the noise is deleted by using an automatic band filter in combination.
As a result of the deletion, there arises a problem that necessary waveform components are removed when an abnormal sound smaller than noise is input, such as a minute water leak in a synthetic resin pipe.

Further, in the method described in Patent Document 3, the calculation section i in FIG. 3 is divided at the distance, and the waveforms of each frequency are synthesized by using a plurality of filters that correlate the underwater sounds generated in each section, and this synthesis is performed. By analyzing the characteristics of the generated waveform, it is determined whether or not the synthesized waveform is the waveform of the leaking sound.

However, in the method described in Patent Document 3, the filter according to the generation position of the sound source is not set, and the pipeline is uniformly determined. As a result, it is not easy to separate the abnormal sound reduction from the noise, and it is difficult to reliably identify the generation position of the abnormal sound causing water leakage.

In addition, there is a water supply branch in a general water pipe, and water is used. When water is continuously used from a faucet or the like, the difference between water leakage and running water cannot be determined, and it may be determined that there is an abnormality in the pipeline. Therefore, it was the mainstream to measure at night when water usage is low.

That is, since water use and water leakage are the same water ejection, it is difficult to uniquely distinguish them in a predetermined frequency band. Therefore, when the water supply branch position is determined to be abnormal, it is difficult to determine whether or not there is a water leak, and the determination accuracy is inferior.
Specifically, by immersing the vibration sensor in the water in the pipe and measuring the vibration transmitted to the water, it is possible to detect minute water leakage vibration, but there is a problem that the influence of the water used is also large. It was.

Purpose of the invention

A main object of the present invention is to provide a method for creating analysis data, a noise filter, a method for determining the presence or absence of water leakage, a method for identifying a water leakage location, and a method for measuring vibration data, which can improve the determination accuracy of water leakage detection. is there.
Another object of the present invention is a method for creating analysis data, a noise filter, a method for determining the presence or absence of water leakage, a method for identifying a water leakage location, and a method for identifying a water leakage location in order to improve the determination accuracy that enables water leakage detection during a time when water is frequently used. It is to provide a measurement method of vibration data.

(1) The method of creating analysis data according to one aspect is to install two vibration sensors at at least two places, measure a plurality of vibration data for a predetermined time from the installed vibration sensors, and acquire the plurality of vibration data. Includes a vibration data creation step and a sorting step of sorting the vibration data obtained by the vibration data creation step using at least one of a predetermined ratio to the number of vibration data and a predetermined ratio to the size of the vibration data. By the sorting process, the analysis data of the first group whose vibration level of the vibration data is larger than the first threshold value and the analysis data of the second group whose vibration level of the vibration data is smaller than the second threshold value are acquired.

When the vibration for this predetermined time is measured, the vibration becomes relatively large when water is used, and becomes relatively small when water is not used. Therefore, the group with a high vibration level is more likely to include water use, and the group with a low vibration level is less likely to include water use. This makes it possible to obtain analysis data on the presence or absence of water use.

(2)
In the noise filter according to the other aspects, two vibration sensors are installed at least in two places, a plurality of vibration data for a predetermined time are measured from the installed vibration sensors, the plurality of vibration data are acquired, and the number of vibration data is obtained. The acquired vibration data is sorted by using at least one of a predetermined ratio with respect to the vibration data or a predetermined ratio with respect to the magnitude of the vibration data, and the vibration level of the vibration data is larger than the first threshold value. The frequency of the waveform is calculated, and the calculated frequency band is excluded from the vibration data.

In this case, it can be estimated that the analysis data of the first group is the data including many possibilities of water use. It is possible to design a frequency filter (band cut filter) that distinguishes between vibrations caused by water leakage and vibrations caused by the use of water, depending on the survey site.

(3)
The method of identifying the leak location according to the other aspects is to install two vibration sensors at at least two places, measure a plurality of vibration data for a predetermined time from the installed vibration sensors, acquire the plurality of vibration data, and vibrate. Sort the acquired vibration data using at least one of a predetermined ratio to the number of data or a predetermined ratio to the size of the vibration data, and analyze the second group in which the vibration level of the vibration data is smaller than the second threshold. The time difference is calculated from the data based on the peak of the cross-correlation function of the vibration waveform, and the location is specified from the time difference.

In this case, the analytical data of Group 2 is likely not to include the effects of water use. Therefore, by using the cross-correlation of the analysis data of the second group, it is possible to identify the leak location with high accuracy.

(4)
In the method for determining the presence or absence of water leakage according to the other aspect, two vibration sensors are installed at at least two places, a plurality of vibration data for a predetermined time are measured from the installed vibration sensors, the plurality of vibration data are acquired, and vibration is performed. The vibration data acquired by using at least one of a predetermined ratio to the number of data and a predetermined ratio to the size of the vibration data is sorted, and the vibration level of the vibration data is smaller than the second threshold. The frequency of peaks of the cross-correlation function of the vibration waveform of the vibration data is calculated from the above, and when the frequency is equal to or higher than a predetermined value, it is determined to be water leakage.

In the present invention, the number of peaks is determined, and the frequency is determined to determine water leakage. For example, when excessive noise is introduced due to the passage of a car or the like, the peak of the cross-correlation function at that location becomes high. In the case of simple integration, this peak may be higher than the peak due to water leakage.
Since vibration due to water leakage is constantly generated, it is possible to reduce the influence of the temporarily increased peak of the cross-correlation function by counting the peak due to the passage of a vehicle as one time.

(5)
In the method for identifying a leak location according to the present invention, the frequency of the vibration waveform of the vibration data is calculated from the analysis data of the first group in which the vibration level of the vibration data is larger than the first threshold in the method for determining the presence or absence of water leakage according to another aspect. , A noise filter that excludes the calculated frequency band from the vibration data may be applied to the analysis data of the second group.

In this case, the possibility of water use can be eliminated more accurately and the leak location can be identified accurately. In particular, reliability is improved when the leak location is specified.

(6)
The method for determining the presence or absence of water leakage according to the present invention calculates the frequency of the vibration waveform from the analysis data of the first group in which the vibration level is larger than the first threshold value in the method for determining the presence or absence of water leakage according to another aspect, and excludes the calculated frequency. The noise filter to be used may be applied to the analysis data of the second group.

In this case, the possibility of water use can be more accurately excluded, and the presence or absence of water leakage can be accurately determined. In particular, the reliability of water leakage determination is improved.

(7)
In the vibration data measurement method according to the other aspect, two vibration sensors are installed at least in two places, a plurality of vibration data for a predetermined time are measured from the installed vibration sensors, and the plurality of vibration data are acquired. Sorting the acquired vibration data using at least one of a predetermined ratio to the number of vibration data and a predetermined ratio to the size of the vibration data, and analyzing the second group in which the vibration level of the vibration data is smaller than the second threshold value. The measurement is continued until the number of data reaches a predetermined number.

In this case, the presence or absence of water leakage or the reliability of the water leakage location can be improved by collecting a predetermined number of analysis data that are less affected by water use.
The number of vibration data belonging to the second group is preferably 10 or more and 80 or less, and more preferably 20 or more and 60 or less.
Specifically, it is desirable to evaluate the magnitude of vibration during on-site measurement and perform measurement until the number of analysis data in the second group reaches a predetermined number.

The data obtained from the vibration sensor is called vibration data. The vibration data also includes the vibration level, the vibration waveform, and the magnitude of the vibration. The vibration level of the vibration data includes the level of frequency, vibration, etc. included in the vibration data, the vibration waveform means the waveform of the vibration data, and the magnitude of the vibration is the amplitude waveform of the vibration data. Means size.

It is a schematic diagram for demonstrating the situation of the method of specifying the abnormal sound generation position. It is a schematic diagram which shows an example of the generation position identification apparatus of an abnormal sound including a vibration sensor. It is a schematic diagram which shows an example of the feature of the vibration sensor of FIG. It is a flowchart which shows an example of the method of specifying the abnormal sound generation position which concerns on this Embodiment. It is a flowchart which shows another example of the method of specifying the abnormal sound generation position which concerns on this Embodiment. It is a figure which shows an example of the result of Example 1. FIG. It is a figure which shows an example of the result of the comparative example 1. FIG. It is a schematic diagram for demonstrating the situation of the method of specifying the abnormal sound generation position of Example 2 and Comparative Example 2. It is a figure based on the amplitude of the Fourier spectrum of the vibration sensor at the point A. It is a figure based on the amplitude of the Fourier spectrum of the vibration sensor at the point B. It is a figure which shows an example of the cross spectrum of the first group. It is a figure which shows an example of the result of Example 2. FIG. It is a figure which shows an example of the result of the comparative example 2.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following description, the same parts are designated by the same reference numerals. Their names and functions are the same. Therefore, the detailed description of them will not be repeated.

<Situation explanation of how to identify the abnormal sound generation position>
FIG. 1 is a schematic diagram for explaining the situation of the method of specifying the abnormal sound generation position.

As shown in FIG. 1, a pipe network 110 is provided underground. The pipe network 110 is provided with vertical holes (manholes) 120 made of fire hydrants at regular intervals.
In the present embodiment, vertical holes 120 made of fire hydrants are provided at intervals between points A and B. In this case, vibration sensors 200 are provided in the vertical holes 120 formed by the fire hydrants at points A and B in FIG. 1, respectively.
Further, the pipe network 110 according to the present embodiment is made of a ductile cast iron pipe. The pipe network 110 has a diameter of 300 (φ300) mm. Further, a commercial facility A, a commercial facility B, and a commercial facility C are provided between the points A and B in the present embodiment, and three water supply branch SBs are provided for each of the pipe network 100. Has been done.
That is, water flows from the tube net 110 into one or more of the commercial facility A, the commercial facility B, and the commercial facility C.

<Explanation of vibration sensor>
FIG. 2 is a schematic diagram showing an example of an abnormal sound generation position specifying device including a vibration sensor, and FIG. 3 is a schematic diagram showing an example of the features of the vibration sensor of FIG.

As shown in FIG. 2, the abnormal sound generation position specifying device 100 according to the present embodiment includes an arithmetic unit 300 and at least a pair of vibration sensors 200. The pair of vibration sensors 200 are resonance type vibration sensors 200.
The vibration sensor 200 of FIG. 2 includes a pedestal 210, a support column 220, thin film electrodes 230, 240, lead wires 231,241, a piezoelectric element 250, a weight 260, and a GPS device 262.
The arithmetic unit 300 includes a generation unit 310 that generates a filter, which will be described later, and an arithmetic unit 320.

As shown in FIG. 2, in the vibration sensor 200, the support column 220 is fixed on the iron pedestal 210. A piezoelectric element 250 is provided at the upper end of the support column 220. One end of the piezoelectric element 250 is cantilevered and supported by the upper end of the support column 220.

A pair of upper and lower thin film electrodes 230 and 240 formed by applying silver paste to both surfaces of the piezoelectric element 250 are provided. Insulation is provided between the support column 220 and the pair of thin film electrodes 230, 240.
Further, a weight 260 is placed at the other end of the piezoelectric element 250 and on the thin film electrode 230.

A lead wire 231 is connected to the thin film electrode 230, a lead wire 241 is connected to the thin film electrode 240, and the lead wires 231 and 241 are connected to the arithmetic unit 300, respectively.
The potential difference output from the lead wires 231 and 241 is output as a vibration waveform by a processing device such as a computer.
In the present embodiment, the lead wires 231 and 241 are used, but the present invention is not limited to this, and a functional unit capable of transmitting and receiving to and from the arithmetic unit 300 may be provided.

Further, the piezoelectric element 250 is formed of a stretched film (PVDF film) of polyvinylidene fluoride, which is a polymer piezoelectric material.

When the specific parameters are the elasticity E of the piezoelectric material, the moment of inertia of area J, the length L, the width b, and the height h, the spring constant k is shown as follows.

^{k = 3EJ / L 3 (J} = bh 3/12) ··· (1)

The resonance frequency fo of the system including the piezoelectric element 250 and the weight 260 is shown as follows.

fo = √ (k / M) / 2π ... (2)

Further, the resonance type vibration sensor 200 is formed so that at least one resonance frequency fo exists in the range of 60 Hz or more and less than 1000 Hz.
As shown in FIG. 3, the resonance type vibration sensor 200 according to the present embodiment is formed so that four resonance frequencies fo exist between 100 Hz and 500 Hz. The reason is that the abnormal sound transmitted through the pipe network 110, particularly the water leakage sound, has many audible sounds, especially less than 1000 Hz.
Specifically, as shown in FIG. 3, the resonance frequency fo has four peaks: a peak P1 near 260 Hz, a peak P2 near 310 Hz, a peak P3 near 350 Hz, and a peak P4 near 480 Hz.
In the present embodiment, the difference between the adjacent peak P1 and the peak P2 is 50 Hz, the difference between the peak P2 and the peak P3 is 40 Hz, and the difference between the peak P3 and the peak P4 is 130 Hz. is there.
That is, in the present embodiment, there are two sets in which the difference between adjacent resonance points is 50 Hz or less. The maximum distance between adjacent resonance points is 130 Hz.
Further, it may have a plurality of resonance points in the range of 0 Hz or more and 500 Hz or less, preferably a plurality of resonance points in a range of 100 Hz or more and 500 Hz or less, and more preferably a plurality of resonance points in a range of 200 Hz or more and 350 Hz or less. You may have a point.
Further, the minimum separation of the resonance points may be 1 Hz or more, and preferably 10 Hz or more from the viewpoint of cost.
On the other hand, the broken line in FIG. 3 shows an example of a conventional vibration sensor. In this case, no peak is formed.

<Flowchart of how to identify the abnormal sound generation position>
Subsequently, a method for specifying the abnormal sound generation position will be described with reference to specific examples.

In the method of specifying the abnormal sound generation position according to the present embodiment, vibration sensors 200 are installed at at least two places (point A and point B) of the pipe network 110, and the abnormal sound or vibration generated by a defect of the pipe network 110 or the like is installed. Is detected by the vibration sensor 200.
This is a method of obtaining the vibration transmission time difference Td from the cross-correlation function of each vibration sensor 200 and specifying the abnormal sound generation position from the transmission time difference Td and the vibration propagation speed V.

In FIG. 1, it is assumed that a fluid leak occurs at a distance L from the vibration sensor 200 at point B. That is, the position of the distance L is the position where the abnormal sound is generated (fluid leakage position). In this case, the leaked sound propagates a distance (L + N) longer than the distance L of the vibration sensor 200 at the point B by the distance N before reaching the vibration sensor 200 at the point A.

Therefore, assuming that the distance between the vibration sensor 200 at point A and the vibration sensor 200 at point B is D, assuming that the transmission time difference Td at which the leaked sound arrives at the vibration sensor 200 at point A and the vibration sensor 200 at point B is assumed. The propagation speed V of the leaked sound and the distance between the two vibration sensors can be calculated by the following equation as D.

Td = N / V ... (3)
Also,
N = D-2L ... (4)
Can be indicated by.

By substituting equation (4) into equation (3),
L = (DV · Td) / 2 ... (5)
It can be expressed as.
The distance L can be obtained as described above.

Hereinafter, a specific example of the method for specifying the abnormal sound generation position according to the present embodiment will be described. FIG. 4 is a flowchart showing an example of a method for specifying an abnormal sound generation position according to the present embodiment.

First, as shown in FIG. 4, the vibration waveform of the leaked sound is acquired from the vibration sensor 200 at the point A of the pipe network 110 at a predetermined time (step S11). Similarly, the vibration waveform of the leaked sound is acquired from the vibration sensor 200 at the point B of the pipe network 110 at a predetermined time (step S21).

The predetermined time is preferably 1 minute or more and less than 60 minutes, more preferably 10 minutes or more and less than 20 minutes. If it is too short, water may be used all the time during a predetermined time, and if it is too long, workability is poor.
Further, a plurality of vibration data may be obtained or intermittently measured by continuously collecting and then subdividing the waveform for a predetermined time.
It is preferable that the number of vibration data is 50 or more and less than 3600 per vibration sensor. Too little data can be unreliable. If it is more than necessary, it will take a long time to calculate.
The length of vibration data is determined by the distance between vibration sensors and the transmission speed of vibration. Assuming that the distance between the vibration sensors is 100 m and the vibration transmission speed is 350 m / sec, the time required for vibration transmission is 100/350 = 0.286 seconds. At this time, the length may be 0.286 seconds or more.

Further, as shown in FIG. 3, the vibration measuring device 200 according to the present invention has four resonance frequencies fo between 60 Hz and more and less than 1000 Hz, so that it is sensitive to vibration waveforms such as leaks with a small flow rate. It can be detected well. In particular, the sensitivity of the vibration waveform in the low frequency band can be maintained high. That is, the vibration measuring device 200 can have extremely low sensitivity when the frequency of the target sound is significantly different from the resonance frequency, and can increase the sensitivity as it approaches the resonance frequency.

It is desirable that at least one resonance frequency fo exists at 100 Hz or more and 500 Hz or less.
In particular, the resonance frequency fo of the vibration measuring device 200 is preferably 2 or more and 6 or less, preferably at predetermined intervals, between 60 Hz and less than 1000 Hz.

Next, the waveform of the leaked sound is subjected to a Fourier transform process (step S12) to acquire the Fourier spectrum A (step S13). Next, the waveform of the leaked sound is subjected to a Fourier transform process (step S22) to acquire the Fourier spectrum B (step S23).

<Fourier transform processing (step S12 and step S22)>
In the Fourier transform processing, a waveform for a certain period of time starting from the same time is extracted from the waveforms obtained by the vibration measuring device 200 at the point A and the vibration measuring device 200 at the point B, and the waveform is subjected to the Fourier transform processing. Assuming that the Fourier spectrum is X (f), X (f) is expressed as a complex function as shown in the following equation (6).

X (f) = ∫ _-∞ ^∞ x (t) e ^-j2πft dt ... (6)
Equation (6) can be expressed by dividing it into a real part and an imaginary part, as in the following equation (7).

X (f) = XR (f) + jX _I (f) = | X (f) | e ^{jθ (f)} ... (7)

In the equation (7), | X (f) | represents the amplitude of the Fourier spectrum, and θ (f) represents the phase. The amplitude | X (f) | of the Fourier spectrum can be obtained by the following equation (8).

| X (f) | = √ {X _R (f) ² + X _I (f) ² } ... (8)

(Sorting process)
Next, in the present embodiment, the sorting step is carried out based on the Fourier spectrum A and the Fourier spectrum B.
In the present embodiment, the maximum value and the minimum value of the amplitude of the Fourier spectrum A are obtained (step S14), and the maximum value and the minimum value of the amplitude of the Fourier spectrum B are obtained (step S24).
Next, the threshold value is set using the obtained maximum value and minimum value (steps S15 and S25).

The threshold value in the present embodiment is calculated by the minimum value + (maximum value-minimum value) × 30%.
Next, from the Fourier spectrum A and the Fourier spectrum B, the Fourier spectrum A and the Fourier spectrum B having a size equal to or larger than the threshold value are set as the analysis data of the first group (step S31), and the Fourier spectrum A having a size smaller than the threshold value is set. And the Fourier spectrum B is set as the analysis data of the second group (step S32).

In the sorting step in the present embodiment, a predetermined ratio can be appropriately determined from the number of Fourier spectra A and Fourier spectra B according to the number of water supply branches and / or the measurement time.
As the number of water supply branches increases, the first group is set at a higher rate. In addition, the higher the water usage is expected in the morning and evening, the higher the first group is set. In the case of a residential area during the daytime, the first group is preferably in the range of 30% or more and 60% or less.
For example, when 50 vibration data are acquired for each vibration sensor, when the ratio is set to 50%, the first group of N (N is a natural number) and the second group of (50-N) are selected. Can be made.

As an example of the threshold value in this embodiment, it is calculated by the following method.
As described above, parameters representing the magnitude of the vibration waveform in the Fourier spectrum A and the Fourier spectrum B, specifically, the average amplitude and / or the vibration level and the like.
Sort at a fixed rate from the minimum value of all vibration data. For example, when the minimum value is set to 20%, the following procedure is taken.
First, the minimum value and the maximum value of the vibration data are obtained, then the threshold value is obtained, and then the threshold value is calculated by a predetermined formula, specifically, the threshold value = minimum value + (maximum value-minimum value) x 20%. Is calculated, and finally, a method of setting a value equal to or greater than the above value as the first group and a value less than the above value as the second group.

In the present embodiment, the threshold value is calculated from the parameters representing the magnitude of the vibration waveform in the Fourier spectrum A and the Fourier spectrum B, but the present invention is not limited to this and is acquired by the processing of steps S11 and S21. The threshold value may be calculated from the generated vibration data.

The ratio from the minimum value of the threshold value is preferably 10% or more and 50% or less, and more preferably 20% or more and 40% or less. If the ratio is too small, more vibration data will be required, and if it is too large, the possibility of water use cannot be ruled out.

Further, in the present embodiment, the case where the threshold value is one is described, but the present invention is not limited to this, and the threshold value may be set to the first threshold value and the second threshold value.
That is, the first threshold value may be used to extract the analysis data of the first group, and the second threshold value may be used to extract the analysis data of the second group.
For example, the first threshold value may be a value of 40% from the minimum value of the threshold value, the second threshold value may be a value of 30% from the minimum value of the threshold value, and the first threshold value may be a value of 30% from the minimum value of the threshold value. 2 The threshold value may be a value 40% from the minimum value of the threshold value.
Further, the calculation method of the first threshold value and the second threshold value may be different.

Next, of the two normalized Fourier spectra A1 and the normalized Fourier spectrum B1, the cross spectrum of the first group Fourier spectrum A and the Fourier spectrum B is calculated (step S31).
Here, the cross spectrum is obtained by multiplying the frequency components of the normalized Fourier spectrum A1 and the normalized Fourier spectrum B1 and averaging them.

When this cross spectrum shows a large value, it means that the correlation between the frequency components of the two spectra is large and the magnitude of the frequency components of both is large in the frequency band.

Here, the frequency band of the cross spectrum of the Fourier spectrum A and the Fourier spectrum B of the first group is extracted, and a band cut filter of the frequency band is created (step S32).
In the present embodiment, since the frequency included in the analysis data of the first group is 25 Hz or more and 50 Hz or less, a band cut filter for removing the frequency of 25 Hz or more and 50 Hz or less was created.

The production of the band cut filter is not limited to the method using the cross spectrum as described above. For example, it is possible to calculate a frequency band having a large amplitude of the Fourier spectrum A and a frequency band having a large amplitude of the Fourier spectrum B, respectively, and create a band cut filter that removes both of them.

Next, the created band cut filter is applied to the Fourier spectrum A and the Fourier spectrum B of the second group, and the cross spectrum of the second group is created from the applied Fourier spectrum A and the Fourier spectrum B (step S41).

Subsequently, the cross-correlation function (step S43) is obtained by Fourier inverse transforming the cross spectrum of the second group (step S42).

Next, on the time axis of the cross-correlation waveform, the time difference in which the cross-correlation waveform is the largest, the time difference in which the cross-correlation waveform is the second largest, and the time difference in which the cross-correlation waveform is the third largest are each counted as one time, and the frequency of the predetermined time is calculated. (Step S44).
The frequency of the predetermined times according to this embodiment corresponds to the number of analysis data of the second group. Finally, the position where the abnormal sound is generated is specified from the transmission time difference Td and the propagation speed of the vibration (step S45).

Here, when determining the presence or absence of water leakage from the cross-correlation function, it may be specifically obtained based on the following indexes.
For example, it may be based on the peak height when a plurality of cross-correlation functions are simply integrated, or based on the ratio between the peak height when a plurality of cross-correlation functions are simply integrated and the average amplitude of the cross-correlation functions. Often, it may be based on the sharpness of the peak when a plurality of cross-correlation functions are simply integrated, or it may be based on any other feature of the cross-correlation function.

That is, in the present invention, the number of times the peak is taken is obtained, and the water leakage is determined by taking the frequency.
As described above, by using the band cut filter for noise such as water use or vehicle passing, it is possible to remove the noise and reliably identify the position where the abnormal sound is generated.

(Other examples)
FIG. 5 is a flowchart showing another example of the method of specifying the abnormal sound generation position according to the present embodiment. Hereinafter, the points that the flowchart of FIG. 5 differs from the flowchart of FIG. 4 will be described.

The method for identifying the abnormal sound generation position shown in FIG. 5 does not carry out the processes of steps S31 and S32 shown in FIG. 4, and instead of the process of step S41, the Fourier spectra A and Fourier of the second group in the sorting step The cross spectrum is calculated from the spectrum B (step S41a).

Since other processes are the same as the flowchart of FIG. 4, the description thereof will be omitted.

As described above, in the method for creating analysis data, the noise filter, the method for determining the presence or absence of water leakage, the method for specifying the location of water leakage, and the method for measuring vibration data according to the present invention, the determination accuracy for water leakage detection can be improved.
In the method of creating analysis data, when the vibration for a predetermined time is measured, the vibration becomes relatively large when water is used, and becomes relatively small when water is not used. Therefore, the group with a high vibration level is more likely to include water use, and the group with a low vibration level is less likely to include water use. This makes it possible to obtain analysis data on the presence or absence of water use.

In addition, based on the analysis data of the first group, which is presumed to be data that includes a lot of possibility of water use, a frequency filter (band) that distinguishes vibration due to water leakage from vibration due to water use according to the survey site. Cut filter) can be designed.
In addition, since the analysis data of the second group is likely not to include the influence of water use, it is possible to identify the leak location with high accuracy by obtaining the cross-correlation function of the analysis data of the second group. ..

Further, in the present invention, the number of times the peak is taken is obtained, and the water leakage is determined by taking the frequency. For example, when excessive noise is introduced due to the passage of a car or the like, the peak of the cross-correlation function at that location becomes high. In the case of simple integration, this peak may be higher than the peak due to water leakage.
In the method of identifying the leakage location of the present invention, vibration due to water leakage always continues to occur. Therefore, the peak of the cross-correlation function that is temporarily increased by counting the peak due to the passage of a vehicle as one time is taken frequently. The influence of can be reduced. In addition, by performing the sorting process, the possibility of water use can be eliminated more accurately, and the leak location can be identified accurately. In particular, reliability is improved when the leak location is specified.

In addition, the method for determining the presence or absence of water leakage of the present invention can more accurately eliminate the possibility of water utilization and accurately determine the presence or absence of water leakage. In particular, the reliability of water leakage determination is improved.

The vibration data measuring method according to the present invention can improve the reliability of the presence or absence of water leakage or the water leakage location by collecting a predetermined number of analysis data that are less affected by the use of water.

<Example 1 and Comparative Example 1>
Hereinafter, as shown in FIG. 1, vibration sensors 200 are attached to two fire hydrants connected to a ductile cast iron pipe diameter of 300 (Φ300) mm, which is a water pipe, and underwater sound is measured. 1 was carried out.
The distance between the vibration sensor 200 and the vibration sensor 200 is 411 m, and there are three water supply branch SBs between the vibration sensor 200 and the vibration sensor 200, and water is used at one of them. It was.
In Example 1, the process was performed based on the flowchart of FIG.

<Example 1>
In Example 1, vibration data for one second was intermittently measured 50 times from vibration sensors 200 installed at two locations. In Example 1, the threshold was set to a vibration level of 30%.
Next, for 50 vibration data, the vibration data above the threshold value was set as the vibration data of the first group, and the vibration data below the threshold value was set as the vibration data of the second group. In Example 1, the number of vibration data in the first group was 30, and the number of vibration data in the second group was 20.
Next, for the vibration data of the second group, the cross-correlation function is calculated, and the time difference in which the cross-correlation function is the largest is counted as one time, the time difference in which it is the second largest, and the time difference in which it is the third largest. , The frequency of 20 times was calculated.

FIG. 6 is a diagram showing an example of the result of the first embodiment.
The result is shown in FIG. The vertical axis of FIG. 6 indicates the number of times, and the horizontal axis of FIG. 6 indicates the distance. The horizontal axis of FIG. 6 is converted from the time difference axis to the distance axis based on the pipeline length and the vibration transmission speed in order to collate with the water leakage position.

<Comparative example 1>
In Comparative Example 1, the vibration data for 1 second was intermittently measured 50 times as in Example 1.
Next, the cross-correlation function is calculated for 50 vibration data, and the time difference in which the cross-correlation function is the largest, the time difference in which the cross-correlation function is the second largest, and the time difference in which the cross-correlation function is the third largest are counted as one time each. , The frequency of 50 times was calculated.
FIG. 7 is a diagram showing an example of the result of Comparative Example 1.

<Evaluation>
As shown in FIGS. 6 and 7, in FIG. 6 of the first embodiment, water leakage clearly appeared at the position P1. However, in FIG. 7 of Comparative Example 1, the influence of water use appeared at the position Q1, and the water leakage could not be determined.

<Example 2 and Comparative Example 2>
FIG. 8 is a schematic diagram for explaining the situation of the method of specifying the abnormal sound generation position of Example 2 and Comparative Example 2.
As shown in FIG. 8, vibration sensors 200 are attached to two locations of a fire hydrant 120 connected to a steel pipe diameter of 700 (Φ700) mm, which is a water pipe, and underwater sound is measured, and Example 2 and Comparative Example 2 are shown. Carried out.
The distance between the vibration sensor 200 and the vibration sensor 200 is 288.1 m, and there is one water supply branch SB between the vibration sensor and the vibration sensor, and water can be used at that one location. went.
In the second embodiment, the processing was performed based on the flowchart of FIG.

<Example 2>
FIG. 9 is a diagram based on the amplitude of the Fourier spectrum of the vibration sensor 200 at the point A, and FIG. 10 is a diagram based on the amplitude of the Fourier spectrum of the vibration sensor 200 at the point B.
In the second embodiment, vibration data for one second was intermittently measured 50 times from vibration sensors 200 installed at two locations. In Example 2, the threshold was set to a vibration level of 20%.

Next, for 50 vibration data, the vibration data above the threshold value was set as the vibration data of the first group, and the vibration data below the threshold value was set as the vibration data of the second group. In Example 1, the number of vibration data in the first group was 30, and the number of vibration data in the second group was 20.

FIG. 11 is a diagram showing an example of the cross spectrum of the first group.
Next, frequency analysis was performed based on the vibration data of the first group. The frequencies included in the vibration data of the first group were mainly 25 Hz or more and 50 Hz or less. As a result, a band cut filter of 25 Hz or more and 50 Hz or less was created.

In Example 2, the created band cut filter was applied to the vibration data of the second group. The cross-correlation function was calculated for the vibration data of the second group to which the band cut filter was applied, and the time difference with the largest cross-correlation function, the time difference with the second largest, and the time difference with the third largest were once each. It was counted and the frequency of 20 times was calculated. FIG. 12 is a diagram showing an example of the result of the second embodiment.

<Comparative example 2>
In Comparative Example 2, the vibration data for 1 second was intermittently measured 50 times as in Comparative Example 1.
Next, the cross-correlation function is calculated for 50 vibration data, and the time difference in which the cross-correlation function is the largest, the time difference in which the cross-correlation function is the second largest, and the time difference in which the cross-correlation function is the third largest are counted as one time each. , The frequency of 50 times was calculated.
FIG. 13 is a diagram showing an example of the results of Comparative Example 2.

<Evaluation>
As shown in FIGS. 12 and 13, in FIG. 12 of the second embodiment, water leakage clearly appeared at the position P2. However, in FIG. 13 of Comparative Example 2, the influence of water use appears at the position Q2, and the determination of water leakage could not be performed.

In the present invention, the points A and B correspond to "at least two places", the vibration sensor 200 corresponds to the "vibration sensor", and the processing of steps S11 and S21S corresponds to the "vibration data creation process, vibration data measurement". The process of steps S14, S15, S24, S25 corresponds to the "method", the threshold corresponds to the "first threshold, the second threshold", and steps S11, ~, S15 and S21, The processes of ~ and 25 correspond to the “method for creating analysis data”, the band cut filter in step S32 corresponds to the “noise filter”, the flowchart of FIG. 4 corresponds to the “method for identifying the leak location”, and step S44. This process corresponds to "a method of calculating the peak frequency of the cross-correlation function of the vibration waveform from the analysis data of the second group and determining the presence or absence of water leakage".

A preferred embodiment of the present invention is as described above, but the present invention is not limited thereto. It will be appreciated that various embodiments are made that do not deviate from the spirit and scope of the invention. Further, in the present embodiment, the actions and effects according to the constitution of the present invention are described, but these actions and effects are examples, and do not limit the present invention.

100 Abnormal sound generation position identification device 110 Pipe network 200 Vibration sensor 231,241 Lead wire 262 GPS device 300 Arithmetic logic unit

Claims (6)

Two vibration sensors installed in at least two positions, a plurality measure the set of vibration data for a predetermined time using the installed set of vibration sensors, creating vibration data to obtain the set of the plurality of the vibration data Process and
Among the sets of vibration data, the set of vibration data whose vibration level of the vibration data is equal to or higher than the first threshold is classified into the first group, and the set of vibration data whose vibration level of the vibration data is less than the second threshold. To the second group, or
Among the sets of vibration data, the set of vibration data having a larger vibration level is selected by a predetermined ratio and sorted into the first group, and the set of the vibration data having a smaller vibration level is selected by a second predetermined ratio. And then sort into the second group, the sorting process and
The step of identifying the leak location, which calculates the cross-correlation function of the vibration waveform of the set of the vibration data of the second group and identifies the leak location from the time difference of the peak of the cross-correlation function, is included.
A method for identifying a leak location, wherein the first threshold value and the second threshold value are determined based on the magnitude of the maximum vibration level and the magnitude of the minimum vibration level among the respective vibration levels of the set of vibration data. The method for identifying a leak location according to claim 1, wherein in the sorting step, the vibration level of the vibration data corresponds to a parameter representing the magnitude of the vibration waveform in the Fourier spectrum obtained by Fourier transforming the vibration data. In the sorting process
The first threshold and the second threshold are the same or are
The method for identifying a leak location according to claim 1 or 2, wherein the sum of the predetermined ratio and the second predetermined ratio is 1 . In the case where the sorting step sorts the set of vibration data whose vibration level is less than the second threshold value into the second group.
When the number of the vibration data sets of the second group sorted in the sorting step is less than the predetermined number, the measurement of the vibration data sets for the predetermined time is continued until the predetermined number is reached. , The method for identifying a leak location according to any one of claims 1 to 3. In the leak location identification step, the frequency band of the vibration waveform of the vibration data is calculated from the set of the vibration data of the first group, and the noise filter excluding the calculated frequency band is used as the vibration of the second group. Claim that after applying to a set of data, the cross-correlation function of the vibration waveform of the set of vibration data of the second group after being applied is calculated, and the leak location is specified from the time difference of the peak of the cross-correlation function. The method for identifying a leak location according to any one of 1 to 4 . In the leak location identification step, the time difference of the peak of the cross-correlation function of the vibration waveform of the vibration data set of the second group is detected for each set of the vibration data of the second group, and the peak of the specific time difference is detected. Any one of claims 1 to 5, which determines that there is a water leak when the frequency is equal to or more than a predetermined number of times in the entire vibration data of the second group, and specifies a place corresponding to the specific time difference as a water leak place. The method of identifying the leak location described in the section.