A precise pipeline leak location system

Abstract

This invention discloses a precise pipeline leak location system, belonging to the field of pipeline leak monitoring technology. It addresses the problems of inaccurate monitoring and location, and slow leak location determination. The system uses uniformly deployed acoustic emission sensors to monitor the pipeline status in real time, capturing both sudden and continuous acoustic signals. These signals are transmitted to a data processing module for parameter and waveform analysis to initially identify leak characteristics. Simultaneously, the data processing module performs noise reduction to improve the signal-to-noise ratio. The calculation module uses a time-difference method, comparing the time difference of acoustic signals arriving at different sensors and combining this with the sound wave propagation speed to determine suspected leak locations. The judgment module further analyzes the acoustic wave curve, comparing the suspected leak location with a standard acoustic wave curve, and combining this with a historical leak database for comprehensive judgment. If the characteristics of a non-overlapping area meet preset standards, it is determined to be a leak, and the location is precisely marked on a map for timely repair.

Description

Technical Field

[0001] This invention relates to the field of pipeline leak monitoring technology, and in particular to a precise pipeline leak location system. Background Technology

[0002] During the process of transporting fluids through long-distance pipelines, leaks often occur due to factors such as corrosion, geographical environment, and damage from third parties. In actual pipeline operation, pipeline leak detection and location systems have become one of the effective means to ensure the safe operation of pipelines.

[0003] Currently, among the methods for detecting and locating pipeline leaks, underground pressurized fluid pipelines such as gas management, oil transportation pipelines, and water pipes are prone to leaks due to their wide coverage and complex routes. If a leak alarm is triggered or the location is inaccurate, the leak point cannot be detected in time, resulting in resource waste and potential safety hazards and environmental pollution. Summary of the Invention

[0004] The purpose of this invention is to provide a precise pipeline leak location system, which solves the problems of inaccurate monitoring and location and the tendency for missed detections in existing monitoring methods.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a pipeline leak precise location 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 acoustic signals generated in the pipeline due to leakage;

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

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

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

[0010] Judgment module: Used to further determine whether a leak has actually occurred based on the results of the calculation module;

[0011] Location module: The location module uses GIS to determine the specific coordinates of the leak location and marks it on a map.

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

[0013] Sudden signals are acoustic emission signals generated during the pipeline damage stage, including pipeline corrosion, cracks and fractures. No acoustic emission signals are generated before the cracks expand further. By detecting sudden signals, signals carrying the location and diameter of the leak can be obtained as the pipeline begins to leak.

[0014] The continuous signal is the signal generated after a pipeline leak occurs. The pressure difference between the inside and outside of 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 and generate high-frequency stress waves on the pipe wall.

[0015] Furthermore, the parameter analysis in the data processing module includes analyzing the frequency, amplitude, and duration parameters of the acoustic signal to extract features related to the leakage; the waveform analysis in 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 acoustic signal to improve the signal-to-noise ratio. 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 noise and useful signals to identify the noise components.

[0018] S42. Filtering: The data processing module uses adaptive filtering to eliminate or reduce identified noise. Adaptive filtering dynamically adjusts the filter parameters by analyzing the correlation between the audio signal and the noise signal to eliminate noise more accurately.

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

[0020] Furthermore, the feature extraction module extracts the acoustic signals of all sensors within the monitoring range at once and includes each sensor signal in a data group.

[0021] Furthermore, the calculation module calculates the distance between the leak location and the two adjacent sets of sensors using the time difference method. The calculation formula is as follows:

[0022]

[0023] Where D is the distance between the two sensors, d is the distance from the leak point to sensor 1, and the time between the sound emission signal from the leak and the arrival times of sensor 1 and sensor 2 are respectively... and v is the speed at which sound waves propagate in the pipe. for and The difference between them.

[0024] Furthermore, the judgment steps of the judgment module are as follows:

[0025] S71. Determine the suspected leak location: By receiving the original acoustic signal as input, the feature extraction module extracts features from the acoustic signal, including frequency, amplitude and key waveform features. Based on the extracted features, the algorithm analyzes and determines the suspected leak location, and outputs the suspected leak location information.

[0026] S72. Acoustic Wave Curve Plotting: Receives acoustic wave signals from suspected leak areas and standard acoustic wave signals from leak-free locations as inputs. Using plotting software, plots acoustic wave curves based on the acoustic wave signals, including acoustic wave curves from suspected leak locations and standard acoustic wave curves from leak-free locations, and outputs the acoustic wave curve plot.

[0027] S73. Acoustic curve comparison: Receives the acoustic curve of the suspected leak location and the standard acoustic curve as input, compares the two acoustic curves point by point, finds the differences and similarities between them, marks the non-overlapping area between the two curves, and before determining whether it is a leak location, the non-overlapping area represents the specific acoustic characteristics generated by the leak, and outputs the non-overlapping area information.

[0028] S74. Retrieve past leakage acoustic curves: Access the acoustic curve database of past leakage locations, retrieve past leakage acoustic curves similar to the current suspected leakage location from the database, and output the past leakage acoustic curves.

[0029] S75. Overlapping Region Analysis: Receives past leakage acoustic wave curves and standard acoustic wave curves as input, compares and analyzes the past leakage acoustic wave curves and standard acoustic wave curves, finds the overlapping regions between them, analyzes the shape, size and acoustic wave characteristics of the overlapping regions, correlates them with the information of non-overlapping regions, and outputs the overlapping region analysis results.

[0030] S76. Leakage Detection: Receive non-overlapping area information and overlapping area analysis results as input, comprehensively analyze the shape and area of ​​non-overlapping areas, analyze overlapping area result factors, and determine whether leakage has occurred based on preset thresholds.

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

[0032] Further, the step of extracting features from the acoustic signal using a feature extraction module by receiving the original acoustic signal as input includes:

[0033] The frequency characteristics of the acoustic signal are extracted from the original acoustic signal using the Fourier transform formula, which is:

[0034]

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

[0036] The amplitude characteristics of the acoustic signal are extracted from the original acoustic signal using the Hilbert transform formula;

[0037] The time-domain features of the original acoustic signal are extracted, including the signal's start time, duration, and waveform shape. The waveform features of the acoustic signal are generated based on the signal's start time, duration, and waveform shape.

[0038] Furthermore, the step of determining the suspected location of a leak based on extracted features and algorithmic analysis includes:

[0039] The filtered signal is obtained by filtering the extracted features. The filtering formula is as follows:

[0040]

[0041] Where y(t) is the filtered signal, s is the known waveform of the leaking sound wave, x is the extracted feature, t is time, and τ is the integration variable, representing the time offset. Indicates the convolution operation;

[0042] The location of the suspected leak is determined based on the peak value of the filtered signal.

[0043] The map module works as follows:

[0044] S81.KML file generation: Create a KML file and use markup language for programming configuration. Edit the user-provided pipeline and station coordinate information through code, and edit the pipeline's color and size attributes.

[0045] S82. Drawing pipelines by importing files: Using specialized map software, import the KML file into the map. At this time, a pipeline and station will be displayed on the map. This pipeline contains coordinate information.

[0046] S83. Offline Tile Map Generation: Select the map of the corresponding area in the map software to generate a tile map;

[0047] S84. Tile Map Storage: Store the generated tile map data to the local disk and specify the corresponding path;

[0048] The specific steps of the offline tile map algorithm are as follows:

[0049] S831. Initialization Preparation: In the HTML file, include the JavaScript library to support map display and interaction;

[0050] S832. Map Settings: Write JavaScript code to set the latitude and longitude of the map center point, define the display range, 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 latitude and longitude coordinates of the mouse position to be displayed when the mouse moves, and set the zoom level displayed on the screen;

[0051] S833. Add Tile Map: Use JavaScript code to specify the path of the offline tile map and add the offline tile map from that path to the map. The complete map will then be displayed on the client screen.

[0052] S834. Adjust style and interaction: Display the imported latitude and longitude coordinates on the screen, and mark and tooltip the location of the leak.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] This invention provides a precise pipeline leak location system. This pipeline leak map location and display system monitors the pipeline status in real time using uniformly deployed acoustic emission sensors, capturing both sudden and continuous acoustic signals. These signals are transmitted to a data processing module for parameter and waveform analysis to initially identify leak characteristics. Simultaneously, the data processing module performs noise reduction to improve the signal-to-noise ratio. A feature extraction module integrates all sensor data, extracting the frequency, amplitude, and time-domain characteristics of the acoustic signals and performing filtering. A calculation module uses the time difference method, comparing the time difference of acoustic signals arriving at different sensors and combining this with the sound wave propagation speed to determine suspected leak locations. A judgment module further analyzes the acoustic wave curve, comparing the suspected leak location with a standard acoustic wave curve and combining this with a historical leak database for comprehensive judgment. If the characteristics of a non-overlapping area meet preset standards, it is determined to be a leak, and the location is precisely marked on the map for timely repair by the user. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the modules of the present invention;

[0056] Figure 2 This is a diagram illustrating the process of detecting leaks using the acoustic emission method of this invention.

[0057] Figure 3 This is a schematic diagram illustrating the principle of leak location positioning in this invention.

[0058] Figure 4 This is a schematic diagram of the feature extraction module of the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] To address the technical problems of inaccurate monitoring and location, and the slow speed of determining the leak location, such as Figures 1-4 As shown, the following preferred technical solutions are provided:

[0061] A precise pipeline leak location system, comprising:

[0062] Data acquisition module: The data acquisition module is used to monitor the status of the pipeline in real time and capture the acoustic signals generated in the pipeline due to leakage;

[0063] Data processing module: The data processing module is used to process the signals acquired by the data acquisition module. The processing includes parameter analysis and waveform analysis.

[0064] Feature extraction module: The feature extraction module is used to extract leakage features from the processed acoustic signal;

[0065] Calculation module: The calculation module uses the features extracted by the feature extraction module to determine the location of suspected leaks;

[0066] Judgment module: Used to further determine whether a leak has actually occurred based on the results of the calculation module;

[0067] Location module: The location module uses GIS to determine the specific coordinates of the leak location and marks it on a map.

[0068] The data acquisition module consists of acoustic emission sensors evenly arranged on the pipeline. The acoustic emission sensors can capture both burst and continuous signals in the pipeline.

[0069] Sudden signals are acoustic emission signals generated during the pipeline damage stage, including pipeline corrosion, cracks and fractures. No acoustic emission signals are generated before the cracks expand further. By detecting sudden signals, signals carrying the location and diameter of the leak can be obtained as the pipeline begins to leak.

[0070] The continuous signal is the signal generated after a pipeline leak occurs. The pressure difference between the inside and outside of 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 and generate high-frequency stress waves on the pipe wall.

[0071] The parameter analysis in the data processing module includes analyzing the frequency, amplitude, and duration parameters of the acoustic signal to extract features related to leakage; the waveform analysis in the data processing module is used to further reveal the characteristics of the leakage.

[0072] The data processing module is also used to denoise the extracted acoustic signals to improve the signal-to-noise ratio. The specific steps are as follows:

[0073] S41. Noise Identification: The data processing module analyzes the audio signal based on the differences in frequency and amplitude characteristics between noise and useful signals to identify the noise components.

[0074] S42. Filtering: The data processing module uses adaptive filtering to eliminate or reduce identified noise. Adaptive filtering dynamically adjusts the filter parameters by analyzing the correlation between the audio signal and the noise signal to eliminate noise more accurately.

[0075] S43. Signal Reconstruction: After noise removal, the data processing module reconstructs the processed signal to restore or improve the quality of the audio signal, retain important information in the audio signal, and minimize noise interference.

[0076] The feature extraction module extracts the acoustic signals of all sensors within the monitoring range at once and includes each sensor signal in a data group.

[0077] The calculation module uses the time difference method to calculate the distance between the leak location and the two adjacent sets of sensors. The calculation formula is as follows:

[0078]

[0079] like Figure 3 As shown, where D is the distance between the two sensors, d is the distance from the leak point to sensor 1, and the time between the leak sound emission signal reaching sensor 1 and sensor 2 are respectively... and v is the speed at which sound waves propagate in the pipe. for and The difference between them.

[0080] The judgment steps of the judgment module are as follows:

[0081] S71. Determine the suspected leak location: By receiving the original acoustic signal as input, the feature extraction module extracts features from the acoustic signal, including frequency, amplitude and key waveform features. Based on the extracted features, the algorithm analyzes and determines the suspected leak location, and outputs the suspected leak location information.

[0082] The process involves receiving the raw acoustic signal as input and using a feature extraction module to extract features from the acoustic signal, including:

[0083] The frequency characteristics of a sound wave signal can be extracted from the original sound wave signal using the Fourier transform formula. The Fourier transform formula is as follows:

[0084]

[0085] Where X(f) is the frequency characteristic, x(t) is the original sound wave signal, f is the frequency, and j is the imaginary unit;

[0086] The amplitude characteristics of the acoustic signal are extracted from the original acoustic signal using the Hilbert transform formula.

[0087] Extract the time-domain features of the original acoustic signal. The time-domain features include the signal's start time, duration, and waveform shape. Generate the waveform features of the acoustic signal based on the signal's start time, duration, and waveform shape.

[0088] Among these, based on the extracted features, algorithmic analysis is used to determine the suspected location of the leak, including:

[0089] The filtered signal is obtained by filtering the extracted features. The filtering formula is as follows:

[0090]

[0091] Where y(t) is the filtered signal, s is the known waveform of the leaking sound wave, x is the extracted feature, t is time, and τ is the integration variable, representing the time offset. Indicates the convolution operation;

[0092] The location of a suspected leak is determined 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 value of y(t) usually corresponds to the potential location of the leaking sound wave.

[0093] S72. Acoustic Wave Curve Plotting: Receives acoustic wave signals from suspected leak areas and standard acoustic wave signals from leak-free locations as inputs. Using plotting software, plots acoustic wave curves based on the acoustic wave signals, including acoustic wave curves from suspected leak locations and standard acoustic wave curves from leak-free locations, and outputs the acoustic wave curve plot.

[0094] S73. Acoustic curve comparison: Receives the acoustic curve of the suspected leak location and the standard acoustic curve as input, compares the two acoustic curves point by point, finds the differences and similarities between them, marks the non-overlapping area between the two curves, and before determining whether it is a leak location, the non-overlapping area represents the specific acoustic characteristics generated by the leak, and outputs the non-overlapping area information.

[0095] S74. Retrieve past leakage acoustic curves: Access the acoustic curve database of past leakage locations, retrieve past leakage acoustic curves similar to the current suspected leakage location from the database, and output the past leakage acoustic curves.

[0096] S75. Overlapping Region Analysis: Receives past leakage acoustic wave curves and standard acoustic wave curves as input, compares and analyzes the past leakage acoustic wave curves and standard acoustic wave curves, finds the overlapping regions between them, analyzes the shape, size and acoustic wave characteristics of the overlapping regions, correlates them with the information of non-overlapping regions, and outputs the overlapping region analysis results.

[0097] S76. Leakage Detection: Receive non-overlapping area information and overlapping area analysis results as input, comprehensively analyze the shape and area of ​​non-overlapping areas, analyze overlapping area result factors, and determine whether leakage has occurred based on preset thresholds.

[0098] The leak location module determines the leak location, indexes the corresponding latitude and longitude coordinates (X,Y) from the database module based on the leak location, imports the coordinate information (X,Y) into an HTML file using an offline tile map algorithm, automatically calls the local tile map, and displays the location and latitude and longitude coordinates of the leak point on the offline map interface;

[0099] The map module workflow is as follows:

[0100] S81.KML file generation: Create a KML file and use markup language for programming configuration. Edit the user-provided pipeline and station coordinate information through code, and edit the pipeline's color and size attributes.

[0101] S82. Drawing pipelines by importing files: Using specialized map software, import the KML file into the map. At this time, a pipeline and station will be displayed on the map. This pipeline contains coordinate information.

[0102] S83. Offline Tile Map Generation: Select the map of the corresponding area in the map software to generate a tile map;

[0103] S84. Tile Map Storage: Store the generated tile map data to the local disk and specify the corresponding path;

[0104] The specific steps of the offline tile map algorithm are as follows:

[0105] S831. Initialization Preparation: In the HTML file, include the JavaScript library to support map display and interaction;

[0106] S832. Map Settings: Write JavaScript code to set the latitude and longitude of the map center point, define the display range, 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 latitude and longitude coordinates of the mouse position to be displayed when the mouse moves, and set the zoom level displayed on the screen;

[0107] S833. Add Tile Map: Use JavaScript code to specify the path of the offline tile map and add the offline tile map from that path to the map. The complete map will then be displayed on the client screen.

[0108] S834. Adjust style and interaction: Display the imported latitude and longitude coordinates on the screen, and mark and tooltip the location of the leak.

[0109] Specifically, the data acquisition module monitors the pipeline's status in real time using acoustic emission sensors uniformly distributed along the pipeline. These sensors can capture both sudden and continuous signals within the pipeline. Sudden signals primarily appear in the early stages of pipeline damage, such as corrosion, cracks, and fractures. These signals carry crucial information about the leak location and orifice size. Continuous signals are generated after a leak occurs, mainly due to the interaction between multiphase turbulent jets caused by the internal and external pressure difference at the leak point and the pipeline and surrounding medium. The data acquisition module transmits the captured acoustic signals to the data processing module. The data processing module first performs parameter analysis on the signals, including frequency, amplitude, and duration, to initially extract leak-related features. Then, waveform analysis is performed to further reveal the characteristics of the leak. The data processing module also performs noise reduction processing to improve the signal-to-noise ratio. The feature extraction module extracts leak characteristics from the processed acoustic signals. This module extracts acoustic signals from all sensors within the monitoring range at once and groups the signals from each sensor into a data set. The calculation module uses a time-difference method to determine the suspected leak location by comparing the leak sound emission... The system calculates the distance between the leak location and the sensor by combining the time difference of the emitted signal arriving at two adjacent sets of sensors with the speed of sound propagation in the pipe. The judgment module then begins operation, identifying suspected leak locations based on features extracted by the feature extraction module. It plots acoustic curves, including those for the suspected leak location and a standard acoustic curve for a non-leaking location, and compares them. By comparing the two acoustic curves, it identifies non-overlapping areas, which typically represent specific acoustic characteristics of a leak. To further verify the existence of a leak, the judgment module retrieves acoustic curves from a database of past leak locations and compares them with the current suspected leak location. By analyzing the shape, size, and acoustic characteristics of overlapping and non-overlapping areas, it can more accurately determine the leak situation. Finally, based on the comprehensive analysis results, the judgment module determines whether a leak has occurred. If the shape and area of ​​the non-overlapping area and the analysis results of the overlapping area meet the preset leak judgment criteria, the system determines that a leak has occurred and marks the specific coordinates of the leak location on the map. Users can then take appropriate measures for repair and handling based on the information provided by the system.

[0110] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0111] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A precise pipeline leak location 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 acoustic signals generated in the pipeline due to leakage; Data processing module: The data processing module is used to process the signals acquired by the data acquisition module. The processing includes parameter analysis and waveform analysis. Feature extraction module: The feature extraction module is used to extract leakage features from the processed acoustic signal, including frequency and amplitude feature extraction, time domain feature extraction, and filtering of the acoustic signal; Calculation module: The calculation module uses the features extracted by the feature extraction module to determine the location of suspected leaks; Judgment module: Used to further determine whether a leak has actually occurred based on the results of the calculation module; Location module: The location module uses GIS to determine the specific coordinates of the leak location and marks it on a map; The judgment steps of the judgment module are as follows: S71. Determine the suspected leak location: By receiving the original acoustic signal as input, the feature extraction module extracts features from the acoustic signal, including frequency, amplitude and key waveform features. Based on the extracted features, the algorithm analyzes and determines the suspected leak location, and outputs the suspected leak location information. S72. Acoustic Wave Curve Plotting: Receives acoustic wave signals from suspected leak areas and standard acoustic wave signals from leak-free locations as inputs. Using plotting software, plots acoustic wave curves based on the acoustic wave signals, including acoustic wave curves from suspected leak locations and standard acoustic wave curves from leak-free locations, and outputs the acoustic wave curve plot. S73. Acoustic curve comparison: Receives the acoustic curve of the suspected leak location and the standard acoustic curve as input, compares the two acoustic curves point by point, finds the differences and similarities between them, marks the non-overlapping area between the two curves, and before determining whether it is a leak location, the non-overlapping area represents the specific acoustic characteristics generated by the leak, and outputs the non-overlapping area information. S74. Retrieve past leakage acoustic curves: Access the acoustic curve database of past leakage locations, retrieve past leakage acoustic curves similar to the current suspected leakage location from the database, and output the past leakage acoustic curves. S75. Overlapping Region Analysis: Receives past leakage acoustic waveforms and standard acoustic waveforms as input, compares and analyzes the past leakage acoustic waveforms and standard acoustic waveforms, finds the overlapping regions between them, analyzes the shape, size and acoustic characteristics of the overlapping regions, correlates them with the information of non-overlapping regions, and outputs the overlapping region analysis results. S76. Leakage Detection: Receive non-overlapping area information and overlapping area analysis results as input, comprehensively analyze the shape and area of ​​non-overlapping areas, analyze overlapping area result factors, and determine whether leakage has occurred based on preset thresholds; The step of receiving the original acoustic signal as input and using a feature extraction module to extract features from the acoustic signal includes: The frequency characteristics of the acoustic signal are extracted from the original acoustic signal using the Fourier transform formula, which is: Where X(f) is the frequency characteristic, x(t) is the original sound wave signal, f is the frequency, and j is the imaginary unit; The amplitude characteristics of the acoustic signal are extracted from the original acoustic signal using the Hilbert transform formula; Extract the time-domain features of the original acoustic signal, the time-domain features including the signal's start time, duration, and waveform shape, and generate the waveform features of the acoustic signal based on the signal's start time, duration, and waveform shape; The method of determining the suspected location of a leak based on extracted features and algorithmic analysis includes: The filtered signal is obtained by filtering the extracted features. The filtering formula is as follows: Where y(t) is the filtered signal, s is the known waveform of the leaking sound wave, x is the extracted feature, t is time, and τ is the integration variable, representing the time offset. Indicates the convolution operation; The location of the suspected leak is determined based on the peak value of the filtered signal.

2. The pipeline leak precise location system as described in claim 1, characterized in that: The data acquisition module consists of acoustic emission sensors evenly arranged on the pipeline. The acoustic emission sensors can capture burst signals and continuous signals in the pipeline. Sudden signals are acoustic emission signals generated during the pipeline damage stage, including pipeline corrosion, cracks and fractures. No acoustic emission signals are generated before the cracks expand further. By detecting sudden signals, signals carrying the location and diameter of the leak can be obtained as the pipeline begins to leak. The continuous signal is the signal generated after a pipeline leak occurs. The pressure difference between the inside and outside of 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 and generate high-frequency stress waves on the pipe wall.

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

4. The pipeline leak precise location system as described in claim 1, characterized in that: The data processing module is also used to denoise the extracted acoustic signals 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 noise and useful signals to identify the noise components; S42. Filtering: The data processing module uses adaptive filtering to eliminate or reduce identified noise. Adaptive filtering dynamically adjusts the filter parameters by analyzing the correlation between the audio signal and the noise signal to eliminate noise more accurately. S43. Signal Reconstruction: After noise removal, the data processing module reconstructs the processed signal to restore or improve the quality of the audio signal, retain important information in the audio signal, and minimize noise interference.

5. The pipeline leak precise location system as described in claim 1, characterized in that: The feature extraction module extracts the acoustic signals of all sensors within the monitoring range at once and includes each sensor signal in a data group.

6. The pipeline leak precise location system as described in claim 1, characterized in that: The calculation module calculates the distance between the leak location and two adjacent sets of sensors using the time difference method. The calculation formula is as follows: Where D is the distance between the two sensors, d is the distance from the leak point to sensor 1, and the time between the sound emission signal from the leak and the arrival times of sensor 1 and sensor 2 are respectively... and v is the speed at which sound waves propagate in the pipe. for and The difference between them.

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

8. The pipeline leak precise location system as described 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 user-provided pipeline and station coordinate information through code, and edit the pipeline's color and size attributes. S82. Importing and Drawing Pipelines: Using map software, import the KML file into the map. At this time, a pipeline and station will be displayed on the map. This pipeline contains coordinate information. S83. Offline Tile Map Generation: Select the map of the corresponding area in the map software to generate a tile map; S84. Tile Map Storage: Store the generated tile map data to the local disk and specify the corresponding path.

9. A pipeline leak precise location system as described 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, include the JavaScript library to support map display and interaction; S832. Map Settings: Write JavaScript code to set the latitude and longitude of the map center point, define the display range, 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 display range is exceeded; Set the display to show the latitude and longitude coordinates of the mouse position when the mouse moves, and set the zoom level to be displayed in the screen; S833. Add Tile Map: Use JavaScript code to specify the path of the offline tile map and add the offline tile map from that path to the map. The complete map will then be displayed on the client screen. S834. Adjust style and interaction: Display the imported latitude and longitude coordinates on the screen, and mark and tooltip the location of the leak.

Images