A precise positioning system for pipeline leaks

Abstract

A system for accurately locating pipeline leaks belongs to the technical field of pipeline leak monitoring. It aims to solve the technical problems of inaccurate monitoring and positioning, and relatively slow leak location judgment. The present invention uses evenly distributed acoustic emission sensors to monitor pipeline status in real time, capture burst and continuous acoustic wave signals, transmit the signals to a data processing module, perform parameter analysis and waveform analysis to preliminarily identify leak characteristics. At the same time, the data processing module denoises the signals to improve the signal-to-noise ratio. The calculation module uses a time difference method to determine the suspected leak location by comparing the time difference between the acoustic wave signals reaching different sensors and combining the acoustic wave propagation speed. The judgment module further analyzes the acoustic wave curve, compares the suspected leak location with the standard acoustic wave curve, and makes a comprehensive judgment based on a database of past leaks. If the characteristics of the non-overlapping area meet the preset standards and are determined to be a leak, the location is accurately marked on a map to facilitate timely repair and treatment.

Description

Technical Field

[0001] The invention relates to the technical field of pipeline leakage monitoring, and in particular to a pipeline leakage precise positioning system. Background Art

[0002] In the process of transporting fluids through long-distance pipelines, pipeline leakage accidents often occur due to the influence of factors such as corrosion, geographical environment and third-party damage. In actual pipeline operation, pipeline leakage detection and positioning system has become one of the effective means to ensure the safe operation of pipelines.

[0003] Among the current methods for pipeline leak detection and positioning, buried gas management, oil transportation pipelines, water pipes and other pressure fluid pipelines have a wide laying area and complex lines. When a pipeline leaks, if a missed alarm occurs or the positioning is inaccurate, the leak point cannot be discovered in time, resulting in loss and waste of resources, and may bring safety hazards and environmental pollution. Summary of the invention

[0004] The purpose of the present invention is to provide a pipeline leakage accurate positioning system, which solves the problem that the existing monitoring methods in the background technology are inaccurate in monitoring positioning and prone to underreporting.

[0005] To achieve the above object, the present invention provides the following technical solution: a pipeline leakage accurate positioning system, comprising:

[0006] Data acquisition module: The data acquisition module is used to monitor the status of the pipeline in real time and capture the sound wave signal generated by leakage in the pipeline;

[0007] Data processing module: The data processing module is used to process the signals collected by the data acquisition module. The processing process includes parameter analysis and waveform analysis;

[0008] Feature extraction module: The feature extraction module is used to extract leakage features from the processed acoustic wave signal;

[0009] Calculation module: The calculation module uses the features extracted by the feature extraction module to determine the location of the suspected leakage;

[0010] Judgment module: used to further judge whether leakage has actually occurred according to the result of the calculation module;

[0011] Positioning module: The positioning module uses GIS to determine the specific coordinates of the leak location and mark it on the map.

[0012] Furthermore, the data acquisition module is composed of acoustic emission sensors uniformly arranged on the pipeline, and the acoustic emission sensors can capture burst signals and continuous signals in the pipeline;

[0013] The burst signal is a burst acoustic emission signal generated during the pipeline damage stage, including pipeline corrosion, cracks and fractures. No acoustic emission signal will be generated before the crack expands. By detecting the burst signal, the signal of the leakage position and leakage aperture can be carried in the process of pipeline leakage.

[0014] The continuous signal is the signal generated after a pipeline leak occurs. The internal and external pressure difference at the leak point causes the fluid in the pipeline to form a multiphase turbulent jet at the leak point. The jet interacts with the pipeline and the surrounding medium to radiate energy outward, generating high-frequency stress waves on the pipe wall.

[0015] Furthermore, parameter analysis during the processing of the data processing module includes analyzing the frequency, amplitude, and duration parameters of the acoustic signal to extract features related to the leakage; waveform analysis during the processing of the data processing module is used to further reveal the characteristics of the leakage.

[0016] Furthermore, the data processing module is also used to denoise the extracted sound wave signal to improve the signal-to-noise ratio, and the specific steps are as follows:

[0017] S41. Noise identification: The data processing module analyzes the audio signal based on the differences in frequency and amplitude characteristics between the noise and the useful signal, and identifies the noise component therein.

[0018] S42. Filtering: The data processing module eliminates or weakens the identified noise through adaptive filtering. The adaptive filtering analyzes the correlation between the audio signal and the noise signal and dynamically adjusts the parameters of the filter to eliminate the noise more accurately.

[0019] S43. Signal reconstruction: After removing the noise, the data processing module will reconstruct the processed signal to restore or improve the quality of the audio signal, retain the important information in the audio signal, and minimize the interference of noise.

[0020] Furthermore, the feature extraction module extracts the acoustic wave signals of all sensors within the monitoring range at one time, and lists each sensor signal into a data group.

[0021] Furthermore, the calculation module calculates the distance between the leakage position and two adjacent sensor groups by using the time difference method, and the calculation formula is:

[0022]

[0023] Where D is the distance between the two sensors, d is the distance from the leakage point to sensor 1, the time between the leakage sound emission signal to sensor 1 and sensor 2 is t1 and t2 respectively, v is the propagation speed of the sound wave in the pipeline, and Δt is the difference between t2 and t1.

[0024] Furthermore, the judging steps of the judging module are:

[0025] S71. Determine the suspected leakage location: by receiving the original sound wave signal as input, using the feature extraction module to extract the features of the sound wave signal, including the key features of frequency, amplitude and waveform, based on the extracted features, determine the suspected leakage location through algorithm analysis, and output the suspected leakage location information;

[0026] S72. Acoustic wave curve drawing: receiving the acoustic wave signal of the suspected leakage area and the standard acoustic wave signal of the non-leakage position as input, using drawing software, drawing an acoustic wave curve according to the acoustic wave signal, including the acoustic wave curve of the suspected leakage position and the standard acoustic wave curve of the non-leakage position, and outputting the acoustic wave curve;

[0027] S73. Sound wave curve comparison: receiving the sound wave curve of the suspected leakage location and the standard sound wave curve as input, comparing the two sound wave curves point by point, finding the differences and similarities between them, marking the non-overlapping area between the two curves, before determining whether it is the leakage location, the non-overlapping area represents the specific sound wave characteristics generated by the leakage, and outputting the non-overlapping area information;

[0028] S74. Retrieving past leakage acoustic wave curves: accessing the acoustic wave curve database of past leakage locations, retrieving past leakage acoustic wave curves similar to the current suspected leakage location from the database, and outputting past leakage acoustic wave curves;

[0029] S75. Overlapping area analysis: receiving the past leakage acoustic wave curve and the standard acoustic wave curve as input, comparing and analyzing the past leakage acoustic wave curve and the standard acoustic wave curve, finding the overlapping area between them, analyzing the shape, size and acoustic wave characteristics of the overlapping area, associating it with the information of the non-overlapping area, and outputting the overlapping area analysis result;

[0030] S76. Leakage judgment: receiving non-overlapping area information and overlapping area analysis results as input, comprehensively analyzing the shape and area of ​​the non-overlapping area, analyzing the overlapping area result factors, and determining whether a leakage occurs based on a preset threshold.

[0031] Furthermore, the leakage location module determines the leakage location, indexes the corresponding longitude and latitude coordinate information (X, Y) from the database module according to the leakage location, imports the coordinate information (X, Y) into the HTML file using the offline tile map algorithm, automatically calls the local tile map, and displays the location and longitude and latitude coordinates of the leakage point on the offline map interface;

[0032] Furthermore, the extracting features of the sound wave signal by using a feature extraction module by receiving the original sound wave signal as input includes:

[0033] The frequency characteristics of the sound wave signal are extracted from the original sound wave signal by using the Fourier transform formula, and the Fourier transform formula is:

[0034]

[0035] Among them, X(f) is the frequency feature, x(t) is the original sound wave signal, f is the frequency, and j is the imaginary unit;

[0036] The amplitude feature of the sound wave signal is extracted from the original sound wave signal by using the Hilbert transform formula, and the Hilbert transform formula is:

[0037]

[0038] Among them, x e (t) is the amplitude characteristic, H(x(t)) is the Hilbert transform;

[0039] The time domain features of the original sound wave signal are extracted, wherein the time domain features include the start time, duration and waveform shape of the signal, and the waveform features of the sound wave signal are generated according to the start time, duration and waveform shape of the signal.

[0040] Furthermore, the method of determining the location of the suspected leakage through algorithm analysis based on the extracted features includes:

[0041] The filtered signal is obtained by performing matched filtering on the extracted features. The filtering formula is:

[0042]

[0043] Among them, y(t) is the filtered signal, s is the known waveform signal of the leakage sound wave, x is the extracted feature, t is time, τ is the integral variable, indicating the time offset, and * indicates the convolution operation;

[0044] The location of the suspected leak is determined based on the peak value of the filtered signal.

[0045] The map module workflow is as follows:

[0046] S81.KML file generation: Create a KML file and use markup language for programming configuration, edit the pipeline and station coordinate information provided by the user through code, and edit the color and size attributes of the pipeline;

[0047] S82. Draw pipelines by file import method: Use dedicated map software to import the KML file into the map. At this time, a pipeline and station will be displayed on the map, and the pipeline contains coordinate information;

[0048] S83. Offline tile map generation: Select a map of the corresponding area in the map software and generate a tile map;

[0049] S84. Tile map storage: store the generated tile map data in the local disk and specify the corresponding path;

[0050] The specific steps of the offline tile map algorithm are as follows:

[0051] S831. Initialization preparation: In the HTML file, introduce the JavaScript library to support the display and interaction of the map;

[0052] S832. Map settings: Write JavaScript code to set the longitude and latitude of the center point of the map, define the display range, and define the zoom level; define the display icon style and call path; define the interface display range, and automatically jump back to the center point map when the range is exceeded; set the longitude and latitude coordinates of the mouse position to be displayed when the mouse moves, and set the zoom level to be displayed on the screen;

[0053] S833. Add tile map: Use JavaScript code to specify the offline tile map path, and add the offline tile map to the map from the path, and finally display the complete map on the client screen;

[0054] S834. Adjust style and interaction: Display the imported latitude and longitude coordinate information on the screen, and mark and provide tooltips at the leak location.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] The present invention provides a pipeline leakage accurate positioning system. The pipeline leakage map positioning display system monitors the pipeline status in real time through evenly arranged acoustic emission sensors, captures burst and continuous acoustic wave signals, and transmits the signals to a data processing module for parameter analysis and waveform analysis to preliminarily identify leakage characteristics. At the same time, the data processing module performs denoising on the signal to improve the signal-to-noise ratio. The feature extraction module integrates all sensor data, extracts the frequency characteristics, amplitude characteristics and time domain characteristics of the acoustic wave signal, and performs filtering and matching. The calculation module uses the time difference method to determine the suspected leakage position by comparing the time difference between the acoustic wave signals reaching different sensors and combining the sound wave propagation speed. The judgment module further analyzes the acoustic wave curve, compares the difference between the suspected leakage position and the standard acoustic wave curve, and makes a comprehensive judgment in combination with the past leakage database. If the characteristics of the non-overlapping area meet the preset standards, it is determined to be a leak, and the position is accurately marked on the map, so that users can repair it in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a schematic diagram of a module of the present invention;

[0058] Figure 2 This is a diagram of the leakage detection process using the acoustic emission method of the present invention;

[0059] Figure 3 It is the principle diagram of leak location positioning of the present invention;

[0060] Figure 4 Schematic diagram of the feature extraction module of the present invention. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] In order to solve the technical problems of inaccurate monitoring positioning and slow leakage location judgment, such as Figure 1-Figure 4 As shown, the following preferred technical solutions are provided:

[0063] A pipeline leakage accurate positioning system, comprising:

[0064] Data acquisition module: The data acquisition module is used to monitor the status of the pipeline in real time and capture the sound wave signal generated by leakage in the pipeline;

[0065] Data processing module: The data processing module is used to process the signals collected by the data acquisition module. The processing process includes parameter analysis and waveform analysis;

[0066] Feature extraction module: The feature extraction module is used to extract leakage features from the processed acoustic wave signal;

[0067] Calculation module: The calculation module uses the features extracted by the feature extraction module to determine the location of the suspected leakage;

[0068] Judgment module: used to further judge whether leakage has actually occurred according to the result of the calculation module;

[0069] Positioning module: The positioning module uses GIS to determine the specific coordinates of the leak location and mark it on the map.

[0070] The data acquisition module is composed of acoustic emission sensors evenly arranged on the pipeline, which can capture burst signals and continuous signals in the pipeline;

[0071] The burst signal is a burst acoustic emission signal generated during the pipeline damage stage, including pipeline corrosion, cracks and fractures. No acoustic emission signal will be generated before the crack expands. By detecting the burst signal, the signal of the leakage position and leakage aperture can be carried in the process of pipeline leakage.

[0072] The continuous signal is the signal generated after a pipeline leak occurs. The internal and external pressure difference at the leak point causes the fluid in the pipeline to form a multiphase turbulent jet at the leak point. The jet interacts with the pipeline and the surrounding medium to radiate energy outward, generating high-frequency stress waves on the pipe wall.

[0073] The parameter analysis during the processing of the data processing module includes analyzing the frequency, amplitude, and duration parameters of the acoustic signal to extract features related to the leak; the waveform analysis during the processing of the data processing module is used to further reveal the characteristics of the leak.

[0074] The data processing module is also used to denoise the extracted sound wave signal to improve the signal-to-noise ratio. The specific steps are as follows:

[0075] S41. Noise identification: The data processing module analyzes the audio signal based on the differences in frequency and amplitude characteristics between the noise and the useful signal, and identifies the noise component therein.

[0076] S42. Filtering: The data processing module eliminates or weakens the identified noise through adaptive filtering. The adaptive filtering analyzes the correlation between the audio signal and the noise signal and dynamically adjusts the parameters of the filter to eliminate the noise more accurately.

[0077] S43. Signal reconstruction: After removing the noise, the data processing module will reconstruct the processed signal to restore or improve the quality of the audio signal, retain the important information in the audio signal, and minimize the interference of noise.

[0078] The feature extraction module extracts the acoustic wave signals of all sensors within the monitoring range at one time and lists each sensor signal into a data group.

[0079] The calculation module calculates the distance between the leakage position and two adjacent sensor groups by using the time difference method, and the calculation formula is:

[0080]

[0081] like Figure 3 As shown, D is the distance between the two sensors, d is the distance from the leakage point to sensor 1, the time between the leakage sound emission signal to sensor 1 and sensor 2 is t1 and t2 respectively, v is the propagation speed of the sound wave in the pipeline, and Δt is the difference between t2 and t1.

[0082] The judgment steps of the judgment module are:

[0083] S71. Determine the suspected leakage location: by receiving the original sound wave signal as input, using the feature extraction module to extract the features of the sound wave signal, including the key features of frequency, amplitude and waveform, based on the extracted features, determine the suspected leakage location through algorithm analysis, and output the suspected leakage location information;

[0084] The process of extracting features of the sound wave signal by receiving the original sound wave signal as input and using the feature extraction module includes:

[0085] The frequency characteristics of the sound wave signal are extracted from the original sound wave signal through the Fourier transform formula. The Fourier transform formula is:

[0086]

[0087] Among them, X(f) is the frequency feature, x(t) is the original sound wave signal, f is the frequency, and j is the imaginary unit;

[0088] The amplitude characteristics of the sound wave signal are extracted from the original sound wave signal through the Hilbert transform formula. The Hilbert transform formula is:

[0089]

[0090] Among them, x e (t) is the amplitude characteristic, H(x(t)) is the Hilbert transform;

[0091] Extracting the time domain features of the original sound wave signal, the time domain features include the start time, duration and waveform shape of the signal, and generating the waveform features of the sound wave signal according to the start time, duration and waveform shape of the signal;

[0092] Among them, based on the extracted features, the location of the suspected leakage is determined through algorithm analysis, including:

[0093] The filtered signal is obtained by performing matched filtering on the extracted features. The filtering formula is:

[0094]

[0095] Among them, y(t) is the filtered signal, s is the known waveform signal of the leakage sound wave, x is the extracted feature, t is time, τ is the integral variable, indicating the time offset, and * indicates the convolution operation;

[0096] Determine the location of the suspected leakage based on the peak value of the filtered signal; it should be noted that the filtered signal is the convolution result y(t), and the peak position of y(t) usually corresponds to the potential position of the leakage sound wave;

[0097] S72. Acoustic wave curve drawing: receiving the acoustic wave signal of the suspected leakage area and the standard acoustic wave signal of the non-leakage position as input, using drawing software, drawing an acoustic wave curve according to the acoustic wave signal, including the acoustic wave curve of the suspected leakage position and the standard acoustic wave curve of the non-leakage position, and outputting the acoustic wave curve;

[0098] S73. Sound wave curve comparison: receiving the sound wave curve of the suspected leakage location and the standard sound wave curve as input, comparing the two sound wave curves point by point, finding the differences and similarities between them, marking the non-overlapping area between the two curves, before determining whether it is the leakage location, the non-overlapping area represents the specific sound wave characteristics generated by the leakage, and outputting the non-overlapping area information;

[0099] S74. Retrieving past leakage acoustic wave curves: accessing the acoustic wave curve database of past leakage locations, retrieving past leakage acoustic wave curves similar to the current suspected leakage location from the database, and outputting past leakage acoustic wave curves;

[0100] S75. Overlapping area analysis: receiving the past leakage acoustic wave curve and the standard acoustic wave curve as input, comparing and analyzing the past leakage acoustic wave curve and the standard acoustic wave curve, finding the overlapping area between them, analyzing the shape, size and acoustic wave characteristics of the overlapping area, associating it with the information of the non-overlapping area, and outputting the overlapping area analysis result;

[0101] S76. Leakage judgment: receiving non-overlapping area information and overlapping area analysis results as input, comprehensively analyzing the shape and area of ​​the non-overlapping area, analyzing the overlapping area result factors, and determining whether a leakage occurs based on a preset threshold.

[0102] The leakage location module determines the leakage location, indexes the corresponding longitude and latitude coordinate information (X, Y) from the database module according to the leakage location, imports the coordinate information (X, Y) into the HTML file using the offline tile map algorithm, automatically calls the local tile map, and displays the location and longitude and latitude coordinates of the leakage point on the offline map interface;

[0103] The map module workflow is as follows:

[0104] S81.KML file generation: Create a KML file and use markup language for programming configuration, edit the pipeline and station coordinate information provided by the user through code, and edit the color and size attributes of the pipeline;

[0105] S82. Draw pipelines by file import method: Use dedicated map software to import the KML file into the map. At this time, a pipeline and station will be displayed on the map, and the pipeline contains coordinate information;

[0106] S83. Offline tile map generation: Select a map of the corresponding area in the map software and generate a tile map;

[0107] S84. Tile map storage: store the generated tile map data in the local disk and specify the corresponding path;

[0108] The specific steps of the offline tile map algorithm are as follows:

[0109] S831. Initialization preparation: In the HTML file, introduce the JavaScript library to support the display and interaction of the map;

[0110] S832. Map settings: Write JavaScript code to set the longitude and latitude of the center point of the map, define the display range, and define the zoom level; define the display icon style and call path; define the interface display range, and automatically jump back to the center point map when the range is exceeded; set the longitude and latitude coordinates of the mouse position to be displayed when the mouse moves, and set the zoom level to be displayed on the screen;

[0111] S833. Add tile map: Use JavaScript code to specify the offline tile map path, and add the offline tile map to the map from the path, and finally display the complete map on the client screen;

[0112] S834. Adjust style and interaction: Display the imported latitude and longitude coordinate information on the screen, and mark and provide tooltips at the leak location.

[0113] Specifically, the data acquisition module monitors the status of the pipeline in real time through acoustic emission sensors evenly arranged on the pipeline. The sensors can capture burst signals and continuous signals in the pipeline. Burst signals mainly appear in the early stages of pipeline damage, such as corrosion, cracks and fractures. These signals carry important information about the leakage location and leakage aperture. Continuous signals are generated after the pipeline leaks, mainly caused by the interaction between the multiphase turbulent jet caused by the internal and external pressure difference at the leakage point and the pipeline and the surrounding medium. The data acquisition module transmits the captured sound wave signal to the data processing module. The data processing module first performs parameter analysis on the signal, including frequency, amplitude and duration, to preliminarily extract features related to the leakage, and then performs waveform analysis to further reveal the characteristics of the leakage. The data processing module also performs denoising on the signal to improve the signal-to-noise ratio. The feature extraction module extracts the leakage features from the processed sound wave signal. This module extracts the sound wave signals of all sensors within the monitoring range at one time and lists the signals of each sensor in a data group. The calculation module uses the time difference method to determine the suspected leakage location. It compares the leakage sound emission. The time difference between the radio signal reaching the two adjacent groups of sensors is combined with the propagation speed of the sound wave in the pipeline to calculate the distance between the leakage position and the sensor. The judgment module starts to work, determines the suspected leakage position according to the features extracted by the feature extraction module, draws the sound wave curve diagram, including the sound wave curve of the suspected leakage position and the standard sound wave curve of the non-leakage position, and compares and analyzes it. By comparing the two sound wave curves, the non-overlapping areas are found. These areas usually represent the specific sound wave characteristics generated by the leakage. In order to further verify the existence of the leakage, the judgment module will call the sound wave curve database of the past leakage position and compare it with the sound wave curve of the current suspected leakage position. By analyzing the shape, size and sound wave characteristics of the overlapping area and the non-overlapping area, the leakage situation can be judged more accurately. Finally, according to the results of the comprehensive analysis, the judgment module will give a judgment on whether a leakage occurs. If the shape, area of ​​the non-overlapping area and the analysis results of the overlapping area meet the preset leakage judgment standard, the system will determine that a leakage has occurred and mark the specific coordinates of the leakage position on the map. The user can take corresponding measures to repair and handle it in time according to the information provided by the system.

[0114] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0115] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A pipeline leakage accurate positioning system, characterized in that: include: Data acquisition module: The data acquisition module is used to monitor the status of the pipeline in real time and capture the sound wave signal generated by leakage in the pipeline; Data processing module: The data processing module is used to process the signals collected by the data acquisition module. The processing process includes parameter analysis and waveform analysis; Feature extraction module: The feature extraction module is used to extract leakage features from the processed acoustic wave signal, including frequency and amplitude feature extraction of the acoustic wave signal, time domain feature extraction of the acoustic wave signal, and filter matching; Calculation module: The calculation module uses the features extracted by the feature extraction module to determine the location of the suspected leakage; Judgment module: used to further judge whether leakage has actually occurred according to the result of the calculation module; Positioning module: The positioning module uses GIS to determine the specific coordinates of the leak location and mark it on the map; The judging steps of the judging module are: S71. Determine the suspected leakage location: by receiving the original sound wave signal as input, using the feature extraction module to extract the features of the sound wave signal, including the key features of frequency, amplitude and waveform, based on the extracted features, determine the suspected leakage location through algorithm analysis, and output the suspected leakage location information; S72. Acoustic wave curve drawing: receiving the acoustic wave signal of the suspected leakage area and the standard acoustic wave signal of the non-leakage position as input, using drawing software, drawing an acoustic wave curve according to the acoustic wave signal, including the acoustic wave curve of the suspected leakage position and the standard acoustic wave curve of the non-leakage position, and outputting the acoustic wave curve; S73. Sound wave curve comparison: receiving the sound wave curve of the suspected leakage location and the standard sound wave curve as input, comparing the two sound wave curves point by point, finding the differences and similarities between them, marking the non-overlapping area between the two curves, before determining whether it is the leakage location, the non-overlapping area represents the specific sound wave characteristics generated by the leakage, and outputting the non-overlapping area information; S74. Retrieving past leakage acoustic wave curves: accessing the acoustic wave curve database of past leakage locations, retrieving past leakage acoustic wave curves similar to the current suspected leakage location from the database, and outputting past leakage acoustic wave curves; S75. Overlapping area analysis: receiving the past leakage acoustic wave curve and the standard acoustic wave curve as input, comparing and analyzing the past leakage acoustic wave curve and the standard acoustic wave curve, finding the overlapping area between them, analyzing the shape, size and acoustic wave characteristics of the overlapping area, associating it with the information of the non-overlapping area, and outputting the overlapping area analysis result; S76. Leakage judgment: receiving non-overlapping area information and overlapping area analysis results as input, comprehensively analyzing the shape and area of ​​the non-overlapping area, analyzing the overlapping area result factors, and determining whether a leakage occurs according to a preset threshold; The method of extracting features of the sound wave signal by receiving the original sound wave signal as input and using the feature extraction module comprises: The frequency characteristics of the sound wave signal are extracted from the original sound wave signal by using the Fourier transform formula, and the Fourier transform formula is: Among them, X(f) is the frequency feature, x(t) is the original sound wave signal, f is the frequency, and j is the imaginary unit; The amplitude feature of the sound wave signal is extracted from the original sound wave signal by using the Hilbert transform formula, and the Hilbert transform formula is: Among them, x e (t) is the amplitude characteristic, H(x(t)) is the Hilbert transform; Extracting time domain features of the original sound wave signal, wherein the time domain features include the start time, duration and waveform shape of the signal, and generating waveform features of the sound wave signal according to the start time, duration and waveform shape of the signal; The method of determining the location of the suspected leakage through algorithm analysis based on the extracted features includes: The filtered signal is obtained by performing matched filtering on the extracted features, and the filtering formula is: Among them, y(t) is the filtered signal, s is the known waveform signal of the leakage sound wave, x is the extracted feature, t is time, τ is the integral variable, indicating the time offset, and * indicates the convolution operation; The location of the suspected leak is determined based on the peak value of the filtered signal.

2. A pipeline leakage accurate positioning system as claimed in claim 1, characterized in that: The data acquisition module is composed of acoustic emission sensors evenly arranged on the pipeline, and the acoustic emission sensors can capture burst signals and continuous signals in the pipeline; The burst signal is a burst acoustic emission signal generated during the pipeline damage stage, including pipeline corrosion, cracks and fractures. No acoustic emission signal will be generated before the crack expands. By detecting the burst signal, the signal of the leakage position and leakage aperture can be carried in the process of pipeline leakage. The continuous signal is the signal generated after a pipeline leak occurs. The internal and external pressure difference at the leak point causes the fluid in the pipeline to form a multiphase turbulent jet at the leak point. The jet interacts with the pipeline and the surrounding medium to radiate energy outward, generating high-frequency stress waves on the pipe wall.

3. A pipeline leakage accurate positioning system as claimed in claim 1, characterized in that: The parameter analysis during the processing of the data processing module includes analyzing the frequency, amplitude, and duration parameters of the acoustic signal to extract features related to the leak; the waveform analysis during the processing of the data processing module is used to further reveal the characteristics of the leak.

4. A pipeline leakage accurate positioning system as claimed in claim 1, characterized in that: The data processing module is also used to denoise the extracted sound wave signal to improve the signal-to-noise ratio. The specific steps are as follows: S41. Noise identification: The data processing module analyzes the audio signal based on the differences in frequency and amplitude characteristics between the noise and the useful signal, and identifies the noise component therein. S42. Filtering: The data processing module eliminates or weakens the identified noise through adaptive filtering. The adaptive filtering analyzes the correlation between the audio signal and the noise signal and dynamically adjusts the parameters of the filter to eliminate the noise more accurately. S43. Signal reconstruction: After removing the noise, the data processing module will reconstruct the processed signal to restore or improve the quality of the audio signal, retain the important information in the audio signal, and minimize the interference of noise.

5. A pipeline leakage accurate positioning system as claimed in claim 1, characterized in that: The feature extraction module extracts the acoustic wave signals of all sensors within the monitoring range at one time, and lists each sensor signal into a data group.

6. A pipeline leakage accurate positioning system as claimed in claim 1, characterized in that: The calculation module calculates the distance between the leakage position and two adjacent sensor groups by using the time difference method, and the calculation formula is: Where D is the distance between the two sensors, d is the distance from the leakage point to sensor 1, the time between the leakage sound emission signal to sensor 1 and sensor 2 is t1 and t2 respectively, v is the propagation speed of the sound wave in the pipeline, and Δt is the difference between t2 and t1.

7. A pipeline leakage accurate positioning system as claimed in claim 1, characterized in that: The leakage location module determines the leakage location, indexes the corresponding longitude and latitude coordinate information (X, Y) from the database module according to the leakage location, imports the coordinate information (X, Y) into the HTML file using the offline tile map algorithm, automatically calls the local tile map, and displays the location and longitude and latitude coordinates of the leakage point on the offline map interface.

8. A pipeline leakage accurate positioning system as claimed in claim 7, characterized in that: The map module workflow is as follows: S81.KML file generation: Create a KML file and use markup language for programming configuration, edit the pipeline and station coordinate information provided by the user through code, and edit the color and size attributes of the pipeline; S82. Draw pipelines by file import method: Use dedicated map software to import the KML file into the map. At this time, a pipeline and station will be displayed on the map, and the pipeline contains coordinate information; S83. Offline tile map generation: Select a map of the corresponding area in the map software and generate a tile map; S84. Tile map storage: Store the generated tile map data in the local disk and specify the corresponding path.

9. A pipeline leakage accurate positioning system as claimed in claim 8, characterized in that: The specific steps of the offline tile map algorithm are as follows: S831. Initialization preparation: In the HTML file, introduce the JavaScript library to support the display and interaction of the map; S832. Map settings: Write JavaScript code to set the latitude and longitude of the center point of the map, define the display range, and define the zoom level; define the display icon style and call path; define the interface display range, and automatically jump back to the center point map when the range is exceeded; Set the longitude and latitude coordinates of the mouse position to be displayed when the mouse moves, and set the zoom level to be displayed on the screen; S833. Add tile map: Use JavaScript code to specify the offline tile map path, and add the offline tile map to the map from the path, and finally display the complete map on the client screen; S834. Adjust style and interaction: Display the imported latitude and longitude coordinate information on the screen, and mark and provide tooltips at the leak location.

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