CN107907279B - Multi-phase flow pipeline leakage sound wave signal analysis method based on wavelet coefficient amplitude - Google Patents

Multi-phase flow pipeline leakage sound wave signal analysis method based on wavelet coefficient amplitude Download PDF

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CN107907279B
CN107907279B CN201711158817.1A CN201711158817A CN107907279B CN 107907279 B CN107907279 B CN 107907279B CN 201711158817 A CN201711158817 A CN 201711158817A CN 107907279 B CN107907279 B CN 107907279B
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coefficient
wavelet
amplitude
leakage
detail
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CN107907279A (en
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方丽萍
李玉星
刘翠伟
胡其会
王武昌
敬华飞
王雅真
梁杰
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China University of Petroleum UPC East China
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01MTESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M3/00Investigating fluid-tightness of structures
    • G01M3/02Investigating fluid-tightness of structures by using fluid or vacuum
    • G01M3/04Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
    • G01M3/24Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations
    • G01M3/243Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations for pipes

Abstract

The invention discloses a multi-phase flow pipeline leakage sound wave signal analysis method based on wavelet coefficient amplitude, and belongs to the technical field of pipeline detection. The method comprises the following steps: decomposing the leaked sound wave signals into wavelets with different scales respectively; obtaining the amplitude values of wavelet decomposition detail coefficients and approximation coefficients of all scales; calculating the amplitude ratio of the approximation coefficient to the detail coefficient; and comparing the amplitude ratio of the approximate coefficient and the detail coefficient to judge leakage. The method has the advantages that the leakage is identified through the amplitude ratio of the wavelet approximation coefficient and the detail coefficient of the two-phase flow leakage signal, the limitation that the leakage cannot be identified only through frequency spectrum analysis is solved, the applicability to the leakage sound wave characteristic in the method for extracting the multi-phase flow pipeline leakage detection and positioning by the sound wave method is strong, and the applicability of the sound wave method multi-phase flow pipeline leakage detection is improved.

Description

Multi-phase flow pipeline leakage sound wave signal analysis method based on wavelet coefficient amplitude
Technical Field
The invention relates to the technical field of pipeline detection, in particular to a multi-phase flow pipeline leakage acoustic signal analysis method based on wavelet coefficient amplitude.
Background
In the field of pipeline inspection technology, the acoustic method measures the amount of dynamic pressure change in the pipeline fluid flow, independent of the pressure at which the pipeline is operating. At present, the technology is mostly applied to the leakage detection of oil and gas single-phase pipelines, and the research on the detection of multiphase flow pipelines is still few. Because the medium in the multiphase pipe flow has mass transfer between phases in the flow, the flow presents different flow shapes under different pressures, flow rates and gas-liquid ratios, and the gas, liquid and solid phases at the leakage hole are mutually coupled to form a sound source when the leakage occurs. In the existing two-phase flow leakage acoustic wave signal analysis, a first peak value and a second peak value appear in the frequency spectrum of the leakage acoustic wave signal of the multiphase flow pipeline, the frequency spectrums of the conventional signal and the leakage signal are mutually overlapped, and the conventional signal and the leakage signal cannot be identified only through the frequency spectrum analysis. Wavelet analysis has the characteristic of multi-time scale analysis, and can decompose a time domain signal into a multi-layer wavelet decomposition signal. In order to identify the leakage acoustic wave signal and the conventional signal of the multiphase flow pipeline, wavelet coefficient amplitude values based on detail coefficients and approximation coefficients are processed. According to a lot of research, the patents of signal analysis based on wavelet coefficient amplitude at present stage mainly include:
chinese patent 201610032607.7 discloses a method for enhancing detection signals of an array type simultaneous transmission and reception ultrasonic probe. The method performs wavelet threshold processing on ultrasonic detection signals of the array type simultaneous-transmitting and simultaneous-receiving ultrasonic probes, and performs linear superposition processing on defect echo signals of two adjacent channels after the wavelet threshold processing, so that the detection sensitivity and the signal-to-noise ratio of the overlapped parts of the sound fields of the array type simultaneous-transmitting and simultaneous-receiving ultrasonic probes are improved.
Chinese patent 201510975052.5 discloses a short-circuit fault data detection method based on wavelet analysis, which utilizes wavelet analysis to perform singular point detection, extracts fault points, performs noise reduction processing on signals to be detected, obtains a fault point neighborhood waveform based on wavelet analysis, and utilizes waveform data to perform short-circuit fault judgment and positioning, thereby judging whether a short-circuit fault occurs and the level and phase of the short-circuit fault.
Chinese patent 201510697304.2 discloses an ultrasonic detection method of defects in a thick-walled composite tubular structure. The method comprises the steps of firstly obtaining original signal data, obtaining final signal data through signal processing methods such as noise reduction, fast Fourier transform, continuous wavelet transform and the like, generating a wavelet coefficient amplitude-time curve graph, extracting the positions and the sizes of internal damage of a composite material layer and debonding of the composite material layer and a metal layer interface according to the generated wavelet coefficient amplitude-time curve graph, and calculating to obtain the distribution of the thickness of a metal layer.
Chinese patent 201310520959.3 discloses a voltage sag detection device based on wavelet analysis and a control method of the device. When voltage sag occurs, the wavelet coefficient obtained by wavelet analysis is changed greatly under a set scale, so that the occurrence moment of the voltage sag and the sag voltage amplitude are accurately positioned, and then a signal is sent to a control part of the voltage sag compensation device to enable the control part to work to compensate the sag voltage, or a signal is sent to a protection system of a load to enable the protection system to perform corresponding protection action.
Chinese patent 201210224871.2 discloses a cable early fault detection method based on complex wavelet singularity detection, which collects current signals of cables to be detected in a power distribution network, and performs N-layer discrete wavelet transform on the current signals by using complex wavelets to obtain wavelet transform coefficients on each decomposition layer; extracting the amplitude information of the wavelet coefficient on each decomposition layer, tracking the modulus maximum value of the wavelet coefficient amplitude on each decomposition layer, and recording the point of the modulus maximum value on each decomposition layer: and recording the corresponding occurrence time of the first module maximum value point as the occurrence time of the early fault, and recording the corresponding occurrence time of the last module maximum value point as the end time of the early fault, so as to detect the early fault of the cable.
In summary, the existing patents only extract the wavelet coefficient of a certain frequency band for processing to realize fault diagnosis, but do not describe the correlation between the wavelet approximation coefficient and the amplitude of the detail coefficient, and the existing technologies are circuit fault identification and image processing, and do not describe the technology for identifying the acoustic wave leakage signal of the multiphase flow pipeline.
Disclosure of Invention
The invention provides a multi-phase flow pipeline leakage sound wave signal analysis method based on wavelet coefficient amplitude, which is used for analyzing a leakage signal by judging the amplitude ratio of a wavelet approximation coefficient and a detail coefficient, identifying leakage and improving the applicability of multi-phase flow pipeline leakage detection by a sound wave method.
In order to achieve the purpose, the invention adopts the following technical scheme:
a multi-phase flow pipeline leakage acoustic signal analysis method based on wavelet coefficient amplitude comprises the following steps:
1) performing wavelet decomposition on the leaked sound wave signals to obtain wavelets with different scales;
2) obtaining the amplitude values of wavelet decomposition detail coefficients and approximation coefficients of all scales;
3) calculating the amplitude ratio of the approximation coefficient to the detail coefficient;
4) and comparing the amplitude ratio of the approximate coefficient and the detail coefficient to judge whether leakage occurs.
Further, in step 1), the specific method for performing wavelet decomposition on the leaked acoustic wave signal is as follows:
step s 101: selecting a wavelet basis function and a decomposition scale;
step s 102: wavelet decomposition is performed on the leaked acoustic wave signal.
Preferably, in step s101, the syss wavelet basis function is selected with a decomposition scale of 8.
Further, in step 2), a specific formula for obtaining the amplitudes of the wavelet decomposition detail coefficients and the approximation coefficients of each scale is as follows:
A(i)=|a(i)|,D(i)=|d(i)| (1)
in the formula, a (i), d (i) are the approximate coefficient and detail coefficient of wavelet decomposition, respectively.
Further, in step 3), the amplitude ratio is calculated as follows:
wherein i is a coefficient data point; r (i) is the amplitude ratio of the i points, A (i) is the approximate coefficient amplitude sequence of the i points, and D (i) is the detail coefficient amplitude sequence of the i points.
Further, in step 4), the specific method for determining whether leakage occurs is as follows:
step S401: setting a threshold value K according to the amplitude ratio of the wavelet approximation coefficient and the detail coefficient of the conventional signal;
step S402: if max (R (i)) is greater than 2K, judging that leakage occurs; if max (R (i)) is less than or equal to 2K, it is judged that no leakage occurs.
Further, in step S401, a specific method for setting the threshold K according to the amplitude ratio of the wavelet approximation coefficient and the detail coefficient of the conventional signal is as follows:
(1) deleting the maximum value in R (i) to obtain a sequence R1(i)。
(2) Calculating the sequence R1(i) The average value of (c) is the threshold K.
Compared with the prior art, the invention has the beneficial effects that:
(1) the method for analyzing the multiphase flow leakage sound wave signal provided by the invention identifies leakage by combining amplitude change according to obvious change of the amplitude of the multiphase flow leakage sound wave signal, analyzes the leakage signal by judging the amplitude ratio of the wavelet approximation coefficient and the detail coefficient, identifies whether leakage exists, solves the limitation that the leakage cannot be identified only by frequency spectrum analysis, and improves the applicability of the sound wave method for detecting the leakage of the multiphase flow pipeline.
(2) The method is simple, convenient to operate and high in applicability to the extraction of the leakage acoustic wave characteristics in the multiphase flow pipeline acoustic wave method leakage detection and positioning method.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
FIG. 1 is a schematic diagram of a method for analyzing a multi-phase flow leakage acoustic signal according to an embodiment of the present invention;
fig. 2 is a flow chart of analyzing a multi-phase flow leakage acoustic signal according to an embodiment of the present invention.
The specific implementation mode is as follows:
the invention is further described with reference to the following figures and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The following example is an exemplary embodiment of the present application,
as shown in fig. 1, the method for analyzing the multi-phase flow pipeline leakage acoustic signal based on the wavelet coefficient amplitude comprises the following steps:
1) performing wavelet decomposition on the leaked sound wave signals to obtain wavelets with different scales; specifically, the method comprises the following steps:
step s 101: the syss wavelet basis functions are selected and the decomposition scale is set to 8.
Step s 102: wavelet decomposition is performed on the leaked acoustic wave signal.
2) Obtaining the amplitude values of wavelet decomposition detail coefficients and approximation coefficients of all scales;
specifically, the method comprises the following steps: the specific formula for obtaining the amplitude values of the wavelet decomposition detail coefficients and the approximation coefficients of each scale is as follows:
A(i)=|a(i)|,D(i)=|d(i)| (1)
wherein, a (i), d (i) are the approximate coefficient and detail coefficient of wavelet decomposition, respectively.
3) Calculating the amplitude ratio of the approximation coefficient to the detail coefficient;
wherein i is a coefficient data point; r is the amplitude ratio, A is the approximate coefficient amplitude sequence, and D is the detail coefficient amplitude sequence.
4) And comparing the amplitude ratio of the approximate coefficient and the detail coefficient to judge whether leakage occurs.
As shown in fig. 2, after wavelet packet decomposition is performed on the leaked sound wave signal, the amplitudes of the high-frequency detail signal and the low-frequency approximate signal of each scale are obtained. The ratio R of the approximation signal to the detail signal is calculated from equation (2). Determining a threshold value K according to the ratio of the conventional signals, comparing R (i) with K, and if R (i) > K, considering that leakage occurs; otherwise the leak is deemed not to have occurred.
In summary, the method provided by the present invention analyzes the high frequency coefficient and the low frequency coefficient by wavelet decomposition, and determines the leakage by determining that the amplitude ratio of the high frequency coefficient and the low frequency coefficient of the given signal is greater than the threshold.
If leakage occurs in the pipeline, the amplitude of the signal at the moment of leakage is obviously changed, so that the leakage signal is identified. The problem that the two-phase flow leakage signal and the conventional signal cannot be distinguished only by researching the frequency spectrum is effectively improved.
Therefore, the method can effectively identify the leaked sound wave signal, and further provides a basis for extracting the signal characteristics. The practicability of the multi-phase flow acoustic wave method for detecting and positioning the leakage is improved.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.

Claims (3)

1. A multi-phase flow pipeline leakage sound wave signal analysis method based on wavelet coefficient amplitude is characterized in that: the method comprises the following steps:
1) decomposing the leaked sound wave signals into wavelets with different scales respectively;
2) obtaining the amplitude values of wavelet decomposition detail coefficients and approximation coefficients of all scales;
3) calculating the amplitude ratio of the approximation coefficient to the detail coefficient;
4) comparing the amplitude ratio of the approximate coefficient and the detail coefficient to judge whether leakage occurs;
in step 2), the specific formula for obtaining the amplitudes of the wavelet decomposition detail coefficients and the approximation coefficients of each scale is as follows:
A(i)=|a(i),D(i)=|d(i)|
wherein, a (i) and d (i) are the approximate coefficient and detail coefficient of wavelet decomposition respectively;
in step 3), the amplitude ratio calculation formula is as follows:
wherein i is a coefficient data point; r (i) is the amplitude ratio of the i points, A (i) is the approximate coefficient amplitude sequence of the i points, and D (i) is the detail coefficient amplitude sequence of the i points;
in step 4), the specific method for judging whether leakage occurs is as follows:
step S401: setting a threshold value K according to the amplitude ratio of the wavelet approximation coefficient and the detail coefficient of the conventional signal;
step S402: if R (i) > K, judging that leakage occurs; if R (i) ≦ K, determining that no leakage occurs;
in step S401, the specific method for setting the threshold K according to the amplitude ratio of the wavelet approximation coefficient and the detail coefficient of the conventional signal is as follows:
1) deleting the maximum value in R (i) to obtain a sequence R1 (i);
2) the average value of the calculated sequence R1(i) is the threshold K.
2. The method for analyzing the multiphase flow pipeline leakage acoustic signal based on the wavelet coefficient amplitude as recited in claim 1, wherein: in the step 1), a specific method for performing wavelet packet decomposition on the leaked sound wave signal comprises the following steps:
step s 101: selecting a wavelet basis function and a decomposition scale;
step s 102: wavelet decomposition is performed on the leaked acoustic wave signal.
3. The method for analyzing the multiphase flow pipeline leakage acoustic signal based on the wavelet coefficient amplitude as recited in claim 2, wherein: in step s101, the syss wavelet basis function is selected and the decomposition scale is set to 8.
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CN109387731B (en) * 2018-12-21 2021-02-02 云南电网有限责任公司电力科学研究院 High-resistance grounding fault identification method based on wavelet analysis and amplitude comparison

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101968162A (en) * 2010-09-30 2011-02-09 东北大学 Pipeline leakage positioning system and method based on collaborative detection with negative pressure wave and sound wave
CN106290578A (en) * 2016-07-27 2017-01-04 常州大学 The detection of a kind of pressure pipeline Small leak source and accurate positioning method
CN106644302A (en) * 2017-02-20 2017-05-10 广东工业大学 Pipeline leak detection method and device and spherical system

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH10221197A (en) * 1997-02-07 1998-08-21 Hitachi Ltd Method and device for detecting leakage
JP2004245618A (en) * 2003-02-12 2004-09-02 Toshiba Mitsubishi-Electric Industrial System Corp Water leakage detection device
CN104595729B (en) * 2015-01-15 2015-08-12 中国石油大学(华东) A kind of oil and gas pipeline leakage localization method based on magnitudes of acoustic waves
CN105546361A (en) * 2016-03-08 2016-05-04 钱昊铖 Acoustic-wave-method gas pipeline leakage monitoring method based on ANN (Artificial Neural Network)
CN105927861B (en) * 2016-04-20 2018-12-07 中国石油大学(华东) Leakage acoustic characteristic extracting method based on Wavelet Transform Fusion blind source separation algorithm
CN105909979B (en) * 2016-04-20 2018-07-03 中国石油大学(华东) Leakage acoustic characteristic extracting method based on Wavelet Transform Fusion blind source separation algorithm
CN106018561B (en) * 2016-05-13 2018-11-20 中国石油大学(华东) The measuring system and method for magnitudes of acoustic waves attenuation coefficient in different pipeline configurations

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101968162A (en) * 2010-09-30 2011-02-09 东北大学 Pipeline leakage positioning system and method based on collaborative detection with negative pressure wave and sound wave
CN106290578A (en) * 2016-07-27 2017-01-04 常州大学 The detection of a kind of pressure pipeline Small leak source and accurate positioning method
CN106644302A (en) * 2017-02-20 2017-05-10 广东工业大学 Pipeline leak detection method and device and spherical system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
A new leak location method based on leakage acoustic waves for oil and gas pipelines;Cui-wei Liu 等;《Journal of Loss Prevention in the Process Industries》;20150504;第35卷;第236-246页 *
Gas leak locating in steel pipe using wavelet transform and cross-correlation method;Saman Davoodi 等;《The International Journal of Advanced Manufacturing Technology volume》;20131010;第1125-1135页 *

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