CN115681831A - Water leakage positioning method based on cross-spectrum information - Google Patents
Water leakage positioning method based on cross-spectrum information Download PDFInfo
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Abstract
The invention relates to a water leakage positioning method based on cross-spectrum information, which comprises the steps of collecting a first receiving signal and a second receiving signal; carrying out time-frequency transformation on the signals, then calculating a coherence function value, and dividing the signals into a plurality of frequency bands according to the maximum value of the coherence function; calculating cross power spectrums, mutual position spectrums and coherent function characteristic values of the first receiving signals and the second receiving signals in each frequency band, and voting the selected water leakage sound frequency band; and calculating the sound source position of the water leakage sound according to the water leakage sound frequency band. The method provided by the invention is characterized in that cross power spectrums corresponding to multiple sections of frequency bands and the amplitude and width of a coherent function are extracted as characteristic quantities, phase change linearity characteristics of the frequency bands corresponding to the cross phase spectrums are combined, each frequency band is scored by using an expert voting model, and the optimal frequency band of the water leakage sound is selected according to the grade, so that noise interference is eliminated, and the frequency band most beneficial to water leakage positioning is used for positioning and resolving.
Description
Technical Field
The invention belongs to the technical field of water leakage positioning, and particularly relates to a water leakage positioning method based on cross-spectrum information.
Background
The existing method for detecting water leakage judges the water leakage position by positioning the sound source of the water leakage sound, because the propagation speed of the water leakage sound of the pipeline is irrelevant to the distance of the water leakage point, and the sound wave propagates to the two probes from the water leakage point with time difference, the positioning calculation can be carried out by the time delay difference of a plurality of sound acquisition points, and the sound source position of the water leakage sound can be indirectly obtained by combining the pipeline length between the two probes and the sound wave propagation speed. At present, two vibration sensor probes are generally adopted to be adsorbed on exposed points of pipelines such as fire hydrants, valves and the like through magnetic seats, and then water leakage sound is collected so as to calculate time delay.
However, continuous and sporadic noise exists in the pipeline, and the noise sound waves interfere with the positioning calculation of the water leakage sound, so that the positioning of the water leakage point is deviated, and therefore a water leakage positioning method capable of reducing the influence of the noise is needed.
Disclosure of Invention
Based on the above-mentioned shortcomings and drawbacks of the prior art, an object of the present invention is to solve at least one or more of the above-mentioned problems of the prior art, in other words, to provide a method for positioning a water leakage based on cross-spectrum information, which satisfies one or more of the above-mentioned needs.
In order to achieve the purpose, the invention adopts the following technical scheme:
a water leakage positioning method based on cross-spectrum information comprises the following steps:
s1, collecting acoustic signals at two different positions to respectively obtain a first receiving signal and a second receiving signal;
s2, performing time-frequency transformation on the first receiving signal and the second receiving signal to obtain frequency band data of the first receiving signal and the second receiving signal;
s3, calculating a coherence function value according to the frequency band data of the first receiving signal and the second receiving signal, selecting a plurality of maximum values of the coherence function value, and dividing the frequency band data of the first receiving signal and the second receiving signal into a plurality of frequency bands according to the plurality of maximum values;
s4, calculating cross-power spectrums and cross-bit spectrums of the first receiving signal and the second receiving signal in each frequency band;
s5, voting by using an expert system according to the cross-power spectrum, the cross-location spectrum and the coherence function value to select the water leakage sound frequency band in the first receiving signal and the second receiving signal;
and S6, calculating the sound source position of the water leakage sound according to the water leakage sound frequency bands in the first receiving signal and the second receiving signal.
Preferably, step S6 specifically includes the following steps:
s61, setting a cut-off frequency according to the water leakage sound frequency band, and filtering the first receiving signal and the second receiving signal to obtain a first water leakage sound signal and a second water leakage sound signal;
s62, performing fast Fourier transform and multiplication on the first water leakage sound signal and the second water leakage sound signal to obtain a cross-correlation function of the water leakage sound signals;
and S63, calculating the time delay of the first water leakage acoustic signal and the second water leakage acoustic signal according to the cross-correlation function.
As a further preferable scheme, after step S62 and before step S63, step S621 is further included:
the cross-correlation function is weighted with a phase-shift weighting function to make it smoother.
As a further preferable scheme, the step S6 specifically includes the following steps:
s61, setting a cut-off frequency according to the water leakage sound frequency band, and filtering the first receiving signal and the second receiving signal to obtain a first water leakage sound signal and a second water leakage sound signal;
s611, segmenting the first water leakage sound signal and the second water leakage sound signal through a sliding window to obtain a plurality of first water leakage sound signal segments and second water leakage sound signal segments;
s62, selecting a first water leakage sound signal section and a second water leakage sound signal section corresponding to one section, and performing fast Fourier transform and multiplication on the first water leakage sound signal section and the second water leakage sound signal section to obtain a cross-correlation function of the water leakage sound signal sections;
s63, calculating time delay of the first water leakage sound signal section and the second water leakage sound signal section according to the cross-correlation function;
s64, returning to the step S62, selecting another segment, obtaining a plurality of time delays after all the segments are selected, and entering a step S65;
and S65, classifying the plurality of time delays to obtain the optimal value of the time delay.
As a further preferable scheme, the step S65 specifically includes:
s651, clustering a plurality of time delays by using a DBSCAN clustering algorithm;
and S652, selecting the maximum set class, and calculating the arithmetic mean value of all time delays in the maximum set class as the optimal value of the time delay.
Preferably, step S4 specifically includes the following steps:
s41, calculating mutual position spectrums of the first receiving signal and the second receiving signal by using a Welch average periodogram method, and calculating phase change linearity of the mutual phase spectrums in each frequency band;
s42, extracting upper and lower limit values, amplitude and width of a coherent function in each frequency band;
and S43, calculating cross-power spectrums of the first received signal and the second received signal, and extracting a spectrum peak of each cross-power spectrum at the center of each frequency band.
As a further preferable scheme, the expert system votes and selects the water leakage sound frequency band according to the phase change linearity of each frequency band, the upper and lower limit values, the amplitude, the width and the spectrum peak at the center of the coherent function.
Compared with the prior art, the invention has the beneficial effects that:
according to the method, the cross power spectrums corresponding to multiple sections of frequency bands and the amplitude and width of a coherent function are extracted as characteristic quantities, phase change linearity characteristics of the frequency bands corresponding to the cross phase spectrums are combined, an expert voting model is used for scoring each frequency band, the optimal frequency band of water leakage sound is selected according to the degree of scoring, so that noise interference is eliminated, and positioning calculation is performed by using the frequency band which is most beneficial to water leakage positioning;
and classifying and aggregating the positioning results, eliminating the influence of abnormal values on the final position calculation, and further improving the accuracy of water leakage positioning.
Drawings
Fig. 1 is a flowchart of a method for positioning a water leak based on cross-spectrum information according to an embodiment of the present invention;
FIG. 2 is a mutual position spectrum of an embodiment of the present invention;
FIG. 3 is a schematic diagram of the lateral distribution of the mutual displacement spectra of an embodiment of the present invention;
FIG. 4 is a flow chart of the calculation of the generalized cross-correlation function of an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention, the following description will explain the embodiments of the present invention with reference to the accompanying drawings. It is obvious that the drawings in the following description are only some examples of the invention, and that for a person skilled in the art, other drawings and embodiments can be derived from them without inventive effort.
Example (b): the present embodiment provides a water leakage positioning method based on cross-spectrum information, a flowchart of which is shown in fig. 1, and the method specifically includes the following steps:
firstly, step S1, taking a vibration sensor probe as acquisition equipment, respectively attaching two probes to pipeline exposed points at different positions in the same pipeline, so as to acquire acoustic signals in the pipeline at two different positions, wherein the acoustic signals acquired by a first vibration sensor probe and a second vibration sensor probe are named as a first receiving signal and a second receiving signal respectively.
Because the acoustic signals collected by the two probes contain noise, the key for ensuring the positioning accuracy of the leakage point is to correctly select the frequency band corresponding to the leakage sound and eliminate the interference of irrelevant frequency bands. Therefore, after the signals are collected, the step S2 is performed, and the time-frequency transformation is performed on the first receiving signal and the second receiving signal to obtain frequency band data of the first receiving signal and the second receiving signal with the frequency as the abscissa.
And then, selecting an initial water leakage sound frequency band according to the coherence between the two signals by the frequency band through the step S3, and calculating a coherence function value according to the frequency band data of the first receiving signal and the second receiving signal.
Specifically, the following method is used for calculating the coherence function value:
assuming that the first received signal and the second received signal are x (n) and y (n), respectively, spectral estimation is performed by using a Welch mean periodogram method, wherein x (n) and y (n) are divided into K segments, and the overlapping rate between each segment is 50%. Then adding a hamming window on each segment, and performing fast Fourier transform on each segment of data to obtain a cross spectrum (X) of each segment of data i (f)Y i * (f) And finally, calculating cross-power spectrum estimated values of the two signals:
wherein denotes a complex conjugate, G xx (f) The source signal is the self-power spectrum of the source signal, and since both the received signals contain the leakage acoustic signal, the reflection on the cross-power spectrum is the spectrum peak with a certain width formed on the common frequency band.
As shown in the above formula, there is a delay difference τ between x (n) and y (n) o And the following relation exists with the mutual phase spectrum:
θ xy (f)＝2πfτ o ；
calculating theta xy (f) From two side spectra G xy (f) Conversion to a single-sided spectrum S xy (f) I.e. by
S xy (f)＝I xy (f)+jQ xy (f)。
The single-side spectrum S of two paths of signals can be obtained by calculation by using a similar process xx (f) And S yy (f) After the single-edge spectrum of the two paths of signals is obtained, the coherent function is calculated by the following formula:
the correlation function represents the correlation degree of the two paths of signals on the frequency domain, if the two signals contain the water leakage sound, the correlation function value of the corresponding frequency band is larger, and therefore the frequency band where the water leakage signal is located is estimated according to the amplitude of the correlation function value.
The vertical axis of the coherence function is a numerical value between 0 and 1, and the horizontal axis is frequency; theoretically if x (n) and y (n) are pure water leakage acoustic signals, then γ 2 xy (f) =1, i.e. strong correlation; if x (n) and y (n) are completely uncorrelated, i.e. neither contains a leaky acoustic signal or a leaky applicator cannot be sensed by its weak device, then γ 2 xy (f) =0; if x (n) and y (n) contain the water leakage sound signal and the environmental noise exists, 0 < gamma 2 xy (f) < 1 and the correlation function exhibits a spectral peak of a certain width.
Because the larger the coherent function is, the higher the degree of correlation is, the first N maxima with the largest amplitude are selected from the coherent function, and the frequency bands are separated by using the frequency of the maxima as the separation point, so as to obtain a plurality of frequency bands with the largest coherent function.
After the frequency band separation is finished, step S4 is performed to calculate scoring factors for determining the water leakage sound signal in each frequency band, where the scoring factors include cross power spectra, mutual position spectra, and values or characteristic values of the coherence function in each frequency band, and here, step S4 calculates the cross phase spectra, the coherence function characteristic values, and the cross power spectra respectively with three parts. Firstly, step S41 and step S3 are performed to calculate the linearity of the phase change of the mutual phase spectrum in each frequency band, and the linearity is calculated by the following method:
firstly, the mutual phase spectrum of the signals is calculated, and on the basis of the above formula, I is used xy (f) And jQ xy (f) The real part and the imaginary part of the cross spectrum respectively, then the cross-phase spectrum:
because at a certain signal-to-noise ratio, theta xy (f) As shown in fig. 2Approximately linearly varying with frequency and having a slope of 2 π τ o Thus the cross-spectral phase spectrum theta xy (f) The correlation of the phase relation between the two signals with the change of frequency can be characterized, and the change trend does not change with time. The phase spectrums of the frequency bands corresponding to other noises in the signal have obvious difference along with the change of time. Therefore, whether the frequency band is the water leakage sound frequency band can be judged by comparing whether the phases of the mutual phase spectrums of different frequency bands are linearly changed and have consistent trend. If the phase changes linearly as shown in the target frequency band outlined in fig. 2, the probability of the leaking sound frequency band is high, and there is no fixed phase relationship among other noises, and there is no stable trend of phase change in the frequency bands of these noises.
For the above reasons, the linearity of the mutual position spectrum may be used as a condition for scoring the leakage sound, and after obtaining the mutual position spectrum, the mutual position spectrum is subjected to gradient calculation, that is, the oblique distribution shown in fig. 2 of the original mutual position spectrum is converted into the transverse distribution shown in fig. 3, and the linearity of the phase curve in each frequency band is represented by the fluctuation degree, that is, the standard deviation, in the frequency band. After the calculation is finished, the linearity of each frequency band is stored and reserved as one of the scoring conditions of the subsequent water leakage sound frequency band.
Step S4 further includes step S42, extracting upper and lower limits, amplitudes and widths of the coherence function in each frequency band on the basis of obtaining each frequency band according to the maximum separation of the coherence function in step S3, and similarly reserving the upper and lower limits, the amplitudes and the widths as scoring conditions for each frequency band.
In addition, the method also comprises a step S43 of using the cross-power spectrum G calculated in the step S3 xy (f) Will cross power spectrum G xy (f) And dividing the frequency bands into a plurality of bands according to the separation of the frequency bands, extracting a spectrum peak value corresponding to the center frequency of each band, and storing the spectrum peak value as a scoring condition of each band.
And (5) after the calculation of the grading condition is finished, generating a total grading table of each frequency band by using an expert system according to the mutual spectrum linearity, the amplitude and the width of the coherence function and the central spectrum peak value of the cross power spectrum calculated in the step (4) as a grading characteristic value, and selecting the frequency band with the highest score, namely the frequency band which best meets the water leakage sound characteristic as the water leakage sound frequency band. Wherein the evaluation algorithm model of the expert system is based on the existing data and cases.
After the water leakage sound frequency band is selected, step S6 may be performed to calculate the sound source position of the water leakage sound according to the water leakage sound frequency bands in the first receiving signal and the second receiving signal.
Specifically, step S6 is implemented as follows:
s61, performing band-pass filtering on the first receiving signal and the second receiving signal by using the water leakage sound frequency band, and only retaining the signals belonging to the water leakage sound frequency band to obtain a first water leakage sound signal and a second water leakage sound signal.
S62, solving a cross-correlation function of the first water leakage sound signal and the second water leakage sound signal, wherein the calculated amount is large by adopting a method of solving the cross-correlation function according to a time domain convolution mode, and the water leakage sound signal is converted into a frequency domain for operation according to a theorem that the time domain convolution is a frequency domain product. Namely, X (n) and Y (n-m) are respectively subjected to fast Fourier transform to obtain X (omega) and Y (omega), so that the frequency domain R of the cross-correlation function of the first water leakage sound signal and the second water leakage sound signal xy (m) is equal to X (ω) Y * (ω)。
Further, R may be caused by the presence of reverberation and noise effects xy (m) the peak value is not obvious, and the time delay estimation precision is reduced; to sharpen R xy (m) the peak value makes the cross-correlation function smoother to keep the noise and reverberation interference constant, and after step S62, step S621 is further included to weight the cross-power spectrum in the frequency domain by using a phase transformation weighting function-a PHAT weight function, and make the cross-power spectrum between signals smoother by the action of a whitening filter, thereby sharpening the generalized cross-correlation function.
The above operations are performed by the flow shown in fig. 4, and the specific formula obtained finally is as follows:
wherein
I.e. the phase-shifting weighting function,
the above generalized cross-correlation function R is then used xy (m) calculating a time delay between the first water leakage acoustic signal and the second water leakage acoustic signal. In the original signals x (n) and y (n-m), m is time delay, y (n-m) represents that the second water leakage sound signal is subjected to time shift, and then when the generalized cross-correlation function obtains the maximum value, the shifted second water leakage sound signal is aligned with the first water leakage sound signal to reach the maximum similarity. Therefore, the m value when the generalized cross-correlation function obtains the maximum value is the time delay between the first water leakage acoustic signal and the second water leakage acoustic signal.
And (5) after the time delay is obtained, step S64 is carried out, and the distance between the leakage point and the two probes is calculated by combining the length D of the pipeline between the probes, the sound wave propagation speed v and the time delay tau.
Specifically, the distance calculation formulas of the leak point and the two probes are respectively as follows:
L1＝(D-v.τ)/2 L2＝D-L1。
although the foregoing steps have been performed with frequency band filtering, the time delay calculated in the foregoing steps S61-S64 is still interfered by noise. As an improvement, in order to further improve the accuracy of the position calculation, the embodiment further provides another specific implementation manner of step S6, and the step S6 is implemented by the following steps:
after the same step S61 as described above, step S611 of segmenting the first and second leakage acoustic signals in the form of sliding windows of a specified width with an overlap ratio of 50% between the segments is additionally performed. Therefore, the time delay is respectively calculated on each section, the time delay results of the sections are finally integrated, and abnormal values in the time delay results are eliminated.
After step S611, one of the segments is selected, and the above steps S62 to S63 are executed to calculate the time delay of the segment. After step S63 is executed, an uncalculated segment is selected in step S64, and the process returns to step S62 to obtain the time delay of a segment again until the time delays of all segments are calculated.
And then, step S65 is executed, all time delays are counted, classified, abnormal values in the time delays are eliminated, and the optimal value of the time delays is obtained to optimize the sound source position calculation.
Specifically, step S65 may select a suitable delay cluster by using a DBSCAN clustering algorithm, and is specifically implemented by the following method:
s651, first, a neighborhood distance threshold Eps and a sample number threshold min _ samples required for the sample point to become a core object are set. And randomly selecting a time delay point, finding all shops with the distance of the point being less than or equal to Eps, and if the number of time delay points with the distance within Eps from the starting point is less than min _ samples, marking the point as noise. If the number of delay points within Eps is greater than min samples, then this point is marked as a core sample and assigned a new cluster label.
The delay points within all distances Eps of the core sample are accessed and if they have not already been assigned a cluster, the new cluster label just created is assigned to them. If they are core samples, then their neighbors are visited in turn, and so on; the cluster is gradually increased until there are no more core samples within the eps distance of the cluster.
Another delay point is then selected that has not been visited and the same process is repeated until all points are in a cluster.
By the above DBSCAN algorithm, a region having a sufficient density is divided into clusters, and a cluster of an arbitrary shape is found in a spatial data set having noise, the cluster is defined as a maximum set of points connected in density, the separated high-density region is set as an independent class, and the low-density region data is set as an abnormal value.
After all the clusters of the time delay results are completed in step S651, step S652 is executed to select the largest one of the clusters, and the cluster is taken as the optimal time delay cluster, while the time delays in other clusters are abnormal values.
And (4) taking the arithmetic mean value of all the time delays in the maximum cluster to obtain the optimal value of the time delay.
And then, step S66 is carried out by using the optimal value of the time delay, and the distance between the water leakage point and the two probes is calculated by using the optimal value of the time delay, so that the sound source position of the water leakage sound is determined.
The method of the embodiment starts from the correlation characteristics of two paths of water leakage signals, selects an initial water leakage sound frequency band based on the amplitude and the width value of a coherent function, combines the cross power spectrum peak value and the linearity of cross spectrum phase change, adopts an expert voting algorithm to select a target filtering frequency band, and then improves the signal to noise ratio of the signals in a band-pass filtering mode. In the time delay estimation process, the time delay is calculated by adopting data segmentation, and the abnormal time delay value caused by the environmental influence is eliminated by using a DBSCAN clustering algorithm, so that the positioning precision of the water leakage point is further improved. Therefore, high-precision water leakage related positioning is realized on the basis of self-adaptive filtering frequency band selection.
It should be noted that the above-mentioned embodiments are merely illustrative of the preferred embodiments and principles of the present invention, and those skilled in the art will appreciate that there are variations in the specific embodiments based on the ideas provided by the present invention, and these variations should be considered as the scope of the present invention.
Claims (7)
1. A water leakage positioning method based on cross-spectrum information is characterized by comprising the following steps:
s1, collecting acoustic signals at two different positions to respectively obtain a first receiving signal and a second receiving signal;
s2, performing time-frequency transformation on the first receiving signal and the second receiving signal to obtain frequency band data of the first receiving signal and the second receiving signal;
s3, calculating a coherence function value according to the frequency band data of the first receiving signal and the second receiving signal, selecting a plurality of maximum values of the coherence function value, and dividing the frequency band data of the first receiving signal and the second receiving signal into a plurality of frequency bands according to the maximum values;
s4, calculating a cross-power spectrum, a cross-bit spectrum and a coherence function characteristic value of the first receiving signal and the second receiving signal in each frequency band;
s5, voting and selecting the water leakage sound frequency band in the first receiving signal and the second receiving signal by using an expert system according to the cross power spectrum, the mutual position spectrum and the characteristic value of the coherence function;
and S6, calculating the sound source position of the water leakage sound according to the water leakage sound frequency bands in the first receiving signal and the second receiving signal.
2. The method for positioning water leakage based on cross-spectral information as claimed in claim 1, wherein said step S6 specifically comprises the steps of:
s61, setting a cut-off frequency according to the water leakage sound frequency band, and filtering the first receiving signal and the second receiving signal to obtain a first water leakage sound signal and a second water leakage sound signal;
s62, performing fast Fourier transform and multiplication on the first water leakage sound signal and the second water leakage sound signal to obtain a cross-correlation function of the water leakage sound signals;
s63, calculating time delays of the first water leakage acoustic signal and the second water leakage acoustic signal according to the cross-correlation function;
and S64, calculating the sound source position of the water leakage sound according to the time delay.
3. The method for positioning water leakage based on cross-spectral information as claimed in claim 2, further comprising, after step S62 and before step S63, step S621:
the cross-correlation function is weighted with a phase shift weighting function to make it smoother.
4. The method for positioning water leakage based on cross-spectral information as claimed in claim 3, wherein the step S6 specifically comprises the steps of:
s61, setting a cut-off frequency according to the water leakage sound frequency band, and filtering the first receiving signal and the second receiving signal to obtain a first water leakage sound signal and a second water leakage sound signal;
s611, segmenting the first water leakage sound signal and the second water leakage sound signal through a sliding window to obtain a plurality of first water leakage sound signal segments and second water leakage sound signal segments;
s62, selecting the corresponding first water leakage sound signal segment and the second water leakage sound signal segment in one segment, and performing fast Fourier transform and multiplication on the first water leakage sound signal segment and the second water leakage sound signal segment to obtain a cross-correlation function of the water leakage sound signal segments;
s63, calculating time delay of the first water leakage sound signal section and the second water leakage sound signal section according to the cross-correlation function;
s64, returning to the step S62, selecting another segment, obtaining a plurality of time delays after all the segments are selected, and entering a step S65;
s65, classifying the plurality of time delays to obtain an optimal value of the time delay;
and S66, calculating the sound source position of the water leakage sound according to the time delay.
5. The method for positioning water leakage based on cross-spectral information as claimed in claim 4, wherein said step S65 specifically comprises:
s651, clustering the plurality of time delays by using a DBSCAN clustering algorithm;
s652, selecting the maximum set class, and calculating the arithmetic mean value of all time delays in the maximum set class as the optimal value of the time delay.
6. The method for positioning water leakage based on cross-spectral information as claimed in claim 1, wherein the step S4 specifically comprises the steps of:
s41, calculating mutual phase spectrums of the first receiving signal and the second receiving signal by using a Welch average periodogram method, and calculating phase change linearity of the mutual phase spectrums in each frequency band;
s42, extracting upper and lower limit values, amplitude and width of a coherent function in each frequency band;
s43, calculating cross-power spectrums of the first receiving signal and the second receiving signal, and extracting a spectrum peak of each cross-power spectrum at the center of each frequency band.
7. The method as claimed in claim 6, wherein the expert system votes the selected leaking sound frequency band according to the linearity of the phase change of each frequency band, the upper and lower limits of the coherence function, the amplitude, the width and the spectrum peak at the center.
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| CN116499920B (en) * | 2023-06-30 | 2023-09-12 | 青岛冠宝林活性炭有限公司 | Online monitoring method for adsorption state of tail gas activated carbon |
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