Positioning method and system for pipeline leak detection

Abstract

The application discloses a positioning method and system for pipeline leakage detection, and the positioning method comprises the following steps: a lower computer module receives a diagnosis instruction of a cloud server; the lower computer module synchronizes an acceleration acquisition module by using a satellite positioning module; the synchronized acceleration acquisition module collects acceleration signals according to a preset range of collection frequency; a communication module is used to upload the acceleration signals to the cloud server; the cloud server obtains a cross-correlation graph of the acceleration signals collected at two ends of a target pipe section; and the cross-correlation graph is used to locate a leakage position on the target pipe section. The positioning method and system for pipeline leakage detection can not only quickly and efficiently detect pipeline leakage, but also accurately locate the specific position of the leakage point on the pipeline, are suitable for large-scale pipeline operation, and the detection result is more accurate.

Description

Technical Field

[0001] This invention relates to a method and system for locating pipeline leaks. Background Technology

[0002] A heating system refers to the general term encompassing boilers in boiler rooms, heat exchange units, outdoor heating pipe networks, and radiators. Heating systems are beginning to shift towards intelligent and low-carbon development.

[0003] In older urban areas, directly buried heating pipes often leak due to corrosion and other reasons, leading to a decline in heating quality during winter. Outdoor heating pipes are buried several meters below the surface, making it difficult to locate leaks visually or by sound in their early stages.

[0004] In existing technologies, leak location through excavation is quite difficult. Leak detection is usually carried out by listening or using robots inside the pipeline. However, both of these methods have drawbacks. The accuracy of leak location by listening is low, and the long pipeline makes the location efficiency low, making it impossible to achieve large-scale real-time monitoring. Locating leaks using robots inside the pipeline has the problem of high usage and maintenance costs. If a large number of robots inside the pipeline are needed to quickly locate a large area of ​​thermal pipelines, a large number of robots are required.

[0005] Moreover, existing technologies cannot quickly and accurately pinpoint the exact location of a pipeline leak. Summary of the Invention

[0006] The technical problem to be solved by this invention is to overcome the shortcomings of existing pipeline leak detection technologies, which cannot quickly and accurately locate the specific leak location. This invention provides a method and system for pipeline leak detection that can not only detect pipeline leaks quickly and efficiently, but also accurately locate the specific location of the leak point on the pipeline. This method is suitable for large-scale pipeline operations and provides more accurate detection results.

[0007] The present invention solves the above-mentioned technical problems through the following technical solution: A method for locating pipeline leaks, the method comprising: The lower-level module receives diagnostic commands from the cloud server; The lower-level module uses a satellite positioning module to synchronize with the acceleration acquisition module; Acceleration signals are acquired using the synchronized acceleration acquisition module at a preset acquisition frequency. The acceleration signal is uploaded to the cloud server using a communication module; The cloud server acquires the cross-correlation spectrum of the acceleration signals collected at both ends of the target pipe segment; The location of the leak on the target pipe section is located using cross-correlation maps.

[0008] Preferably, the preset range is 4000Hz to 15000Hz, the duration of acceleration signal acquisition is 8 minutes to 20 minutes, and the method of locating the leak location on the target pipe section using cross-correlation maps includes: The cloud server acquires the acquisition time of the acceleration signal and the environmental data of the target pipe section; The location of the leak on the target pipe section is located using cross-correlation maps, acquisition time, and the environmental data.

[0009] Preferably, the environmental data includes road condition information at the time of acquisition, the acquisition time of the acceleration signal obtained by the cloud server, and environmental data of the target pipe section, including: Obtain the surveillance video of the target pipe section during the specified acquisition time; Identify the vehicle positions in the surveillance video and the road surface positions of the acceleration acquisition module; The vehicle positions within the area of ​​the road surface location are correlated with acceleration signals; The data on the vehicle's elapsed time in the acceleration signal is deleted, and the acceleration signal after deleting the data is used to generate the cross-correlation map.

[0010] Preferably, the positioning method includes: The satellite positioning module is used to synchronize the acceleration acquisition module and the monitoring camera device; Record the data content of the acceleration signal at the moment the vehicle passes by; The data content is used to perform artificial intelligence training to obtain the data change patterns of the vehicle's acceleration signal at the moment of passage; The cloud server uses the data change patterns to delete the data on the vehicle's passing time from the acceleration signal; The cloud server uses the acceleration signal from the deleted vehicle passage time data to obtain the cross-correlation map.

[0011] Preferably, the positioning method further includes: For the target pipe segment, obtain the pressure value of the pressure gauge closest to the target pipe segment, and the pipe measured by the pressure gauge is connected to the pipe where the target pipe segment is located; If the pressure value is greater than a preset value, the cloud server sends a diagnostic command to the lower-level module; otherwise, it sends a diagnostic command to the lower-level module at a preset time.

[0012] Preferably, the positioning method further includes: For a test pipe section, a satellite positioning module is used to synchronize two acceleration acquisition modules, which are respectively located at both ends of the test pipe section; Acceleration signals are acquired using the synchronized acceleration acquisition module; The acceleration signal is uploaded to the cloud server using a communication module; The system determines whether the detected pipe section is leaking based on the acceleration signal and the preset reference value of the pipeline under normal operating conditions. If so, it outputs the leak detection result and uses the detected pipe section as the target pipe section.

[0013] Preferably, the acceleration acquisition module and the lower-level machine module are connected in a one-to-one correspondence. Each lower-level machine module is also used to connect to a digital-to-analog conversion module, a satellite positioning module, and a wireless communication module. The positioning method includes: For a detection tube segment, the lower-level module notifies the acceleration acquisition module to acquire the acceleration signal at a preset time. The digital acceleration signal is acquired using a digital-to-analog converter module, and the digital acceleration signal is stored in the lower-level computer module. The acceleration digital signal is uploaded to the cloud server using the wireless communication module. The cloud server acquires the average power spectral density of the acceleration digital signal within a preset frequency range; The cloud server obtains the measured length of the detection pipe segment; The cloud server obtains the preset reference value of the pipe under the measured length under normal working conditions; The cloud server determines whether the detection pipe section is leaking based on the average power spectral density and the preset reference value of the pipeline under normal operating conditions.

[0014] Preferably, the cloud server obtains the measured length of the detection pipe segment, including: The positioning signal from the acceleration acquisition module is obtained using the satellite positioning module; The cloud server determines whether the database contains the pipe drawing corresponding to the tested pipe section. If so, the shortest pipe length at the location recorded by the two positioning signals in the pipe drawing corresponding to the detected pipe section shall be used as the measurement length. Preferably, the pipeline drawing is initialized and calibrated using initial image points and their actual locations. The calibration results are then used to calculate the positioning coordinates of the pipeline image points obtained through image recognition in the pipeline drawing. The cloud server obtains the measured length of the inspected pipe segment, including: The positioning signal from the acceleration acquisition module is obtained using the satellite positioning module; The cloud server determines whether there is a pipeline drawing corresponding to the detected pipe section in the database. If so, it uses the positioning coordinates to obtain the pipeline image point closest to the location recorded by the positioning signal. The pipe length between the two nearest pipe image points is obtained as the measurement length.

[0015] The present invention also provides a positioning system for implementing the positioning method described above.

[0016] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of the present invention.

[0017] The positive and progressive effects of this invention are as follows: The method and system for locating pipeline leaks of the present invention can not only detect pipeline leaks quickly and efficiently, but also accurately locate the specific location of the leak point on the pipeline. It is suitable for large-scale pipeline operations, and the detection results are more accurate. Attached Figure Description

[0018] Figure 1 This is a partial structural diagram of the heating system of Embodiment 1 of the present invention.

[0019] Figure 2 This is a flowchart of the positioning method in Embodiment 1 of the present invention. Detailed Implementation

[0020] The present invention will be further illustrated by way of embodiments below, but the present invention is not limited to the scope of the embodiments described herein. Example

[0021] See Figure 1 This embodiment provides a positioning system for detecting pipeline leaks in a heating system. The positioning system includes several acceleration acquisition modules, several analog-to-digital conversion modules, several lower-level machine modules, several wireless communication modules, several satellite positioning modules, a cloud server backend, a cloud server frontend, and several power supply modules.

[0022] The acceleration acquisition module is located on the outer wall of the pipe and can be installed using a magnet.

[0023] An installation position 11 on the outer wall of the pipeline includes an acceleration acquisition module 111, an analog-to-digital conversion module 112, a lower-level computer module 113, a wireless communication module 114, a power supply module 115, and a satellite positioning module 116.

[0024] The lower-level module is used to receive diagnostic commands from the cloud server; The lower-level module is used to synchronize the acceleration acquisition module with the satellite positioning module; The lower-level module is used to acquire acceleration signals at a preset range of acquisition frequency using the synchronized acceleration acquisition module; The lower-level module is used to upload the acceleration signal to the cloud server using the communication module; The cloud server is used to obtain the cross-correlation spectrum of the acceleration signals collected at both ends of the target pipe segment; The cloud server is used to locate the leak location on the target pipe section using cross-correlation maps.

[0025] Furthermore, the preset range is 4000Hz to 15000Hz, and the duration of acquiring acceleration signals is 8 minutes to 20 minutes.

[0026] The cloud server is used to acquire the acquisition time of the acceleration signal and the environmental data of the target pipe section; The cloud server is used to locate the leak location on the target pipe section using cross-correlation maps, acquisition time, and environmental data.

[0027] In pipeline leak diagnosis mode, pipeline leak diagnosis is real-time. After the backend issues the command, the lower-level machine receives the command via the wireless WIFI module. Then, after the GPS module synchronizes the time, the vibration acceleration acquisition module enters a rapid acquisition state, with an acquisition frequency range of 4000:15000Hz, mainly selecting the 8000Hz acquisition frequency, collecting 10 minutes of data, and storing the collected data in the lower-level machine module. After the data acquisition is completed, the acquired data is uploaded to the cloud server backend via the wireless WIFI module. The backend server performs data noise reduction processing and calculation analysis to obtain the cross-correlation spectrum of the data obtained from the two vibration acceleration acquisition modules. The cross-correlation spectrum will give the pipeline leak location, and then the pipeline leak location result is displayed on the front end.

[0028] Meanwhile, on the cloud server's front-end interface, the pipeline leak location results can be combined with a button press to perform another timely pipeline leak diagnosis. However, it should be noted that the background environment for pipeline leak diagnosis has changed. For example, during the monitoring period, urban traffic may be relatively simple, the environment relatively quiet, and there may be very few cars passing by. If the background conditions change when performing button diagnosis at the front end, such as during the day, construction, or broadcasting, the results should be reasonably interpreted.

[0029] The power module mainly consists of a lithium battery, a renewable power source, and a transformer and voltage regulator module. The lithium battery powers the lower-level computer module, the vibration acceleration acquisition module, the analog-to-digital converter module, the wireless antenna module, and the GPS module. The renewable energy sources are small micro-wind generators, small photovoltaic panels, or semiconductor thermoelectric generators. If it is a semiconductor thermoelectric generator, it will utilize the temperature difference between the wall temperature of the thermal pipe (approximately 90°C) and the ambient temperature (approximately 20-30°C) to generate a certain amount of electricity.

[0030] In monitoring mode, data was collected and transmitted centrally between 3 and 4 a.m. every day, which effectively saved power consumption of the WIFI antenna and GPS and improved the standby time of the device.

[0031] Furthermore, the environmental data includes road condition information at the time of collection.

[0032] The cloud server is used to acquire the monitoring video of the target pipe segment during the acquisition time; The cloud server is used to identify the vehicle positions in the surveillance video and the road surface positions of the acceleration acquisition module. The cloud server is used to associate the vehicle positions within the area of ​​the road surface location with acceleration signals; The cloud server is used to delete data on the vehicle's passage time from the acceleration signal, and the acceleration signal after data deletion is used to generate the cross-correlation map.

[0033] Furthermore, the positioning system is used to synchronize the acceleration acquisition module and the monitoring camera device using the satellite positioning module; The cloud server is used to record the data content of the acceleration signal at the moment the vehicle passes by; The cloud server is used to perform artificial intelligence training using the data content to obtain the data change pattern of the vehicle's acceleration signal at the moment of passage. The cloud server is used to delete data on the vehicle's passage time from the acceleration signal based on the data change patterns. The cloud server is used to obtain the cross-correlation map using the acceleration signal from the deleted vehicle passage time data.

[0034] For the target pipe segment, the cloud server is used to obtain the pressure value of the pressure gauge closest to the target pipe segment, and the pipe measured by the pressure gauge is connected to the pipe where the target pipe segment is located; The cloud server is used to determine whether the pressure value is greater than a preset value. If it is, the cloud server sends a diagnostic command to the lower-level module; otherwise, it sends a diagnostic command to the lower-level module at a preset time.

[0035] Furthermore, for a detection pipe segment, the lower-level module is used to synchronize two acceleration acquisition modules using a satellite positioning module, with the two acceleration acquisition modules respectively located at both ends of the detection pipe segment; The lower-level module is used to acquire acceleration signals using the synchronized acceleration acquisition module; The lower-level module is used to upload the acceleration signal to the cloud server (cloud server backend) using the communication module. The cloud server is used to determine whether the detected pipe section is leaking based on the acceleration signal and the preset reference value of the pipeline under normal operating conditions. If so, it outputs the leak detection result.

[0036] The acceleration acquisition module is connected to the lower-level machine module in a one-to-one correspondence. Each lower-level machine module is also used to connect to a digital-to-analog conversion module, a satellite positioning module, and a wireless communication module.

[0037] For a detection tube segment, the lower-level module is used to notify the acceleration acquisition module to acquire acceleration signals at a preset time. The lower-level machine module is used to acquire the acceleration digital signal using the digital-to-analog converter module, and the lower-level machine module is also used to store the acceleration digital signal; The lower-level module is used to upload the acceleration digital signal to the cloud server using the wireless communication module; The cloud server is used to acquire the average power spectral density of the acceleration digital signal within a preset frequency range; The cloud server is used to determine whether the detection pipe section is leaking based on the average power spectral density and the preset reference value of the pipeline under normal operating conditions.

[0038] In monitoring mode, the two lower-level machines synchronize signals via GPS modules every day between 3 and 4 a.m.

[0039] Then the lower-level module continuously sends instructions to each acceleration acquisition module to measure the acceleration of the pipeline. The acquisition frequency is selected in the range of 5 to 15 minutes / time, and the acquired data is transmitted to the analog-to-digital conversion module in real time.

[0040] After the analog signal is digitized, the digital signal is stored in the lower-level machine module. After data acquisition is completed, each lower-level machine transmits the lower-level machine signal to the cloud backend through the wireless WIFI module. After receiving the instruction, the cloud backend performs time-frequency conversion on the signal.

[0041] The background system calculates the average power spectral density D1 of each acquired signal within the 500-1500Hz range, and then compares it with the initial non-leakage value D0 (preset reference value). If D1 is greater than or equal to 5 times D0, the pipeline is considered to be leaking.

[0042] The alarm is displayed on the front-end web interface, and then the back-end sends commands to each lower-level machine to diagnose pipeline leaks.

[0043] Furthermore, the cloud server is used to obtain the measured length of the detection pipe segment; The cloud server is used to obtain the preset reference value of the pipe under the measured length under normal working conditions; The cloud server is used to determine whether the detection pipe section is leaking based on the average power spectral density and the preset reference value of the pipeline under normal operating conditions.

[0044] Specifically, the cloud server is used to acquire the positioning signal from the acceleration acquisition module using the satellite positioning module; The cloud server is also used to determine whether there is a pipeline drawing corresponding to the detected pipe section in the database. If so, the shortest pipe length at the location recorded by the two positioning signals in the pipeline drawing corresponding to the detected pipe section is obtained as the measurement length.

[0045] Furthermore, the pipeline drawing is initialized and calibrated using initial image points and their actual locations. This involves matching the image points on the pipeline drawing with their corresponding actual locations (which can be positioning coordinates), thus digitizing the pipeline drawing and giving the image points coordinate data. The positioning coordinates of the pipeline image points obtained through image recognition in the pipeline drawing are then calculated using the initial calibration results.

[0046] The cloud server is used to acquire the positioning signal from the acceleration acquisition module using the satellite positioning module; The cloud server is used to determine whether there is a pipeline drawing corresponding to the detected pipe section in the database. If so, it uses the positioning coordinates to obtain the pipeline image point closest to the location recorded by the positioning signal. The cloud server is used to obtain the pipe length between the two nearest pipe image points as the measurement length.

[0047] See Figure 2 Using the aforementioned positioning system, this embodiment also provides a positioning method, including: Step 100: The lower-level module receives diagnostic instructions from the cloud server; Step 101: The lower-level computer module uses the satellite positioning module to synchronize with the acceleration acquisition module; Step 102: Use the synchronized acceleration acquisition module to acquire acceleration signals at a preset acquisition frequency. Step 103: Use the communication module to upload the acceleration signal to the cloud server; Step 104: The cloud server obtains the cross-correlation spectrum of the acceleration signals collected at both ends of the target pipe segment; Step 105: Use the cross-correlation map to locate the leak location on the target pipe section.

[0048] The preset range is 4000Hz to 15000Hz, the duration of acceleration signal acquisition is 8 minutes to 20 minutes, and step 105 includes: Step 1051: The cloud server acquires the acquisition time of the acceleration signal and the environmental data of the target pipe section; Step 1052: Use the cross-correlation spectrum, acquisition time, and environmental data to locate the leak location on the target pipe section.

[0049] Step 1051 includes: Obtain the surveillance video of the target pipe section during the specified acquisition time; Identify the vehicle positions in the surveillance video and the road surface positions of the acceleration acquisition module; The vehicle positions within the area of ​​the road surface location are correlated with acceleration signals; The data on the vehicle's elapsed time in the acceleration signal is deleted, and the acceleration signal after deleting the data is used to generate the cross-correlation map.

[0050] In this embodiment, the environmental data refers to the acceleration changes caused by the passing of a vehicle, which are obtained and analyzed from surveillance video recordings.

[0051] For road sections without surveillance, data from monitored road sections is first used as training samples for artificial intelligence. Then, the pattern of acceleration changes when vehicles pass by is found, and this pattern is used to make more accurate leak diagnosis.

[0052] Specifically, the positioning method includes: The satellite positioning module is used to synchronize the acceleration acquisition module and the monitoring camera device; Record the data content of the acceleration signal at the moment the vehicle passes by; The data content is used to perform artificial intelligence training to obtain the data change patterns of the vehicle's acceleration signal at the moment of passage; The cloud server uses the data change patterns to delete the data on the vehicle's passing time from the acceleration signal; The cloud server uses the acceleration signal from the deleted vehicle passage time data to obtain the cross-correlation map.

[0053] The positioning method further includes: For the target pipe segment, obtain the pressure value of the pressure gauge closest to the target pipe segment, and the pipe measured by the pressure gauge is connected to the pipe where the target pipe segment is located; If the pressure value is greater than a preset value, the cloud server sends a diagnostic command to the lower-level module; otherwise, it sends a diagnostic command to the lower-level module at a preset time.

[0054] The positioning method further includes: For a test pipe section, a satellite positioning module is used to synchronize two acceleration acquisition modules, which are respectively located at both ends of the test pipe section; Acceleration signals are acquired using the synchronized acceleration acquisition module; The acceleration signal is uploaded to the cloud server using a communication module; The system determines whether the detected pipe section is leaking based on the acceleration signal and the preset reference value of the pipeline under normal operating conditions. If so, it outputs the leak detection result and uses the detected pipe section as the target pipe section.

[0055] An acceleration acquisition module is connected to a lower-level machine module in a one-to-one correspondence. Each lower-level machine module is also used to connect to a digital-to-analog conversion module, a satellite positioning module, and a wireless communication module. The positioning method includes: For a detection tube segment, the lower-level module notifies the acceleration acquisition module to acquire the acceleration signal at a preset time. The digital acceleration signal is acquired using a digital-to-analog converter module, and the digital acceleration signal is stored in the lower-level computer module. The acceleration digital signal is uploaded to the cloud server using the wireless communication module. The cloud server acquires the average power spectral density of the acceleration digital signal within a preset frequency range; The cloud server obtains the measured length of the detection pipe segment; The cloud server obtains the preset reference value of the pipe under the measured length under normal working conditions; The cloud server determines whether the detection pipe section is leaking based on the average power spectral density and the preset reference value of the pipeline under normal operating conditions.

[0056] The cloud server obtains the measured length of the detection pipe segment, including: The positioning signal from the acceleration acquisition module is obtained using the satellite positioning module; The cloud server determines whether the database contains the pipe drawing corresponding to the tested pipe section. If so, the shortest pipe length at the location recorded by the two positioning signals in the pipe drawing corresponding to the detected pipe section shall be used as the measurement length. The pipeline drawing is initialized and calibrated using initial image points and their actual locations. The calibration results are then used to calculate the positioning coordinates of the pipeline image points obtained through image recognition in the pipeline drawing. The cloud server obtains the measured length of the inspected pipe section, including: The positioning signal from the acceleration acquisition module is obtained using the satellite positioning module; The cloud server determines whether there is a pipeline drawing corresponding to the detected pipe section in the database. If so, it uses the positioning coordinates to obtain the pipeline image point closest to the location recorded by the positioning signal. The pipe length between the two nearest pipe image points is obtained as the measurement length.

[0057] Furthermore, the cloud server acquires the measured length of the detection pipe segment, including: The cloud server determines whether the database contains the pipe drawing corresponding to the detected pipe section; otherwise, it obtains the straight-line distance or navigation distance between the two acceleration acquisition modules based on the two positioning signals. The measured length is obtained based on the straight-line distance or navigation distance.

[0058] In other embodiments, the positioning method includes: The cloud server determines whether the database contains the pipe drawing corresponding to the detected pipe section; otherwise, it obtains the straight-line distance and navigation distance of the two acceleration acquisition modules based on the two positioning signals. Determine whether the length difference between the straight-line distance and the navigation distance is less than a preset length. If so, use the straight-line distance as the measured length; otherwise, use the navigation distance as the measured length and obtain the number of bends in the pipeline based on the navigation route. The cloud server obtains the preset reference value of the pipe under the measured length under normal working conditions, and obtains the adjustment reference value according to the number of bends; The system determines whether the detection pipe section is leaking based on the acceleration signal, preset reference value, and adjusted reference value. If so, it outputs the leak detection result.

[0059] Specifically, the positioning method includes: For a training section, the acceleration signal is collected by the synchronized acceleration acquisition module to obtain the road monitoring video at the synchronization time of the training section. Identify the vehicle's position, size, speed, and road surface location in the surveillance video footage, as well as the location of the acceleration acquisition module. Artificial intelligence is used to train and obtain correlation data of vehicle position, vehicle size, vehicle speed and acceleration signal within the range of the road surface location; The preset reference value is obtained based on the associated data.

[0060] Specifically, the positioning method includes: For a detection pipe section, the acceleration signal is collected by the synchronized acceleration acquisition module to obtain the road surface monitoring video at the synchronization time of the detection pipe section; Identify the vehicle's position, size, speed, and road surface location in the surveillance video footage, as well as the location of the acceleration acquisition module. The preset reference value is obtained using the associated data, vehicle location, vehicle size, and vehicle speed; The system determines whether the detection pipe section is leaking based on the acceleration signal and the preset reference value obtained using the associated data. If so, it outputs the leak detection result.

[0061] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A method for locating leaks in pipelines, characterized in that, The positioning method includes: The lower-level module receives diagnostic commands from the cloud server; The lower-level module uses a satellite positioning module to synchronize with the acceleration acquisition module; Acceleration signals are acquired using the synchronized acceleration acquisition module at a preset acquisition frequency. The acceleration signal is uploaded to the cloud server using a communication module; The cloud server acquires the cross-correlation spectrum of the acceleration signals collected at both ends of the target pipe segment; The location of the leak on the target pipe section was located using cross-correlation maps; The preset range is 4000Hz to 15000Hz, and the duration of acceleration signal acquisition is 8 minutes to 20 minutes. The method of locating the leak location on the target pipe section using cross-correlation maps includes: The cloud server acquires the acquisition time of the acceleration signal and the environmental data of the target pipe section; The location of the leak on the target pipe section was located using cross-correlation maps, acquisition time, and the environmental data. The environmental data includes road condition information at the time of collection, the time of collection of acceleration signals by the cloud server, and environmental data of the target pipe section, including: Obtain the surveillance video of the target pipe section during the specified acquisition time; Identify the vehicle positions in the surveillance video and the road surface positions in the acceleration acquisition module; The vehicle positions within the area of ​​the road surface location are correlated with acceleration signals; The data of the vehicle's elapsed time in the acceleration signal is deleted, and the acceleration signal after data deletion is used to generate the cross-correlation map. The positioning method further includes: The satellite positioning module is used to synchronize the acceleration acquisition module and the monitoring camera device; Record the data content of the acceleration signal at the moment the vehicle passes by; The data content is used to perform artificial intelligence training to obtain the data change patterns of the vehicle's acceleration signal at the moment of passage; The cloud server uses the data change patterns to delete the data on the vehicle's passing time from the acceleration signal; The cloud server uses the acceleration signal from the deleted vehicle passage time data to obtain the cross-correlation map.

2. The positioning method as described in claim 1, characterized in that, The positioning method further includes: For the target pipe segment, obtain the pressure value of the pressure gauge closest to the target pipe segment, and the pipe measured by the pressure gauge is connected to the pipe where the target pipe segment is located; If the pressure value is greater than a preset value, the cloud server sends a diagnostic command to the lower-level module; otherwise, it sends a diagnostic command to the lower-level module at a preset time.

3. The positioning method as described in claim 1, characterized in that, The positioning method further includes: For a test pipe section, a satellite positioning module is used to synchronize two acceleration acquisition modules, which are respectively located at both ends of the test pipe section; Acceleration signals are acquired using the synchronized acceleration acquisition module; The acceleration signal is uploaded to the cloud server using a communication module; The system determines whether the detected pipe section is leaking based on the acceleration signal and the preset reference value of the pipeline under normal operating conditions. If so, it outputs the leak detection result and uses the detected pipe section as the target pipe section.

4. The positioning method as described in claim 3, characterized in that, An acceleration acquisition module is connected to a lower-level machine module in a one-to-one correspondence. Each lower-level machine module is also used to connect to a digital-to-analog conversion module, a satellite positioning module, and a wireless communication module. The positioning method includes: For the detection pipe section, the lower-level module notifies the acceleration acquisition module to acquire the acceleration signal at a preset time. The digital acceleration signal is acquired using a digital-to-analog converter module, and the digital acceleration signal is stored in the lower-level computer module. The acceleration digital signal is uploaded to the cloud server using the wireless communication module. The cloud server acquires the average power spectral density of the acceleration digital signal within a preset frequency range; The cloud server obtains the measured length of the detection pipe segment; The cloud server obtains the preset reference value of the pipe under the measured length under normal working conditions; The cloud server determines whether the detection pipe section is leaking based on the average power spectral density and the preset reference value of the pipeline under normal operating conditions.

5. The positioning method as described in claim 4, characterized in that, The cloud server obtains the measured length of the detection pipe segment, including: The positioning signal from the acceleration acquisition module is obtained using the satellite positioning module; The cloud server determines whether the corresponding pipeline drawing for the tested pipe section exists in the database. If so, the shortest pipe length at the location recorded by the two positioning signals in the pipe drawing corresponding to the detected pipe section is taken as the measurement length.

6. The positioning method as described in claim 5, characterized in that, The pipeline drawing is initialized and calibrated using initial image points and their actual locations. The calibration results are then used to calculate the positioning coordinates of the pipeline image points obtained through image recognition in the pipeline drawing. The cloud server obtains the measured length of the inspected pipe section, including: The positioning signal from the acceleration acquisition module is obtained using the satellite positioning module; The cloud server determines whether there is a pipeline drawing corresponding to the detected pipe section in the database. If so, it uses the positioning coordinates to obtain the pipeline image point closest to the location recorded by the positioning signal. The pipe length between the two nearest pipe image points is obtained as the measurement length.

7. A positioning system, characterized in that, The positioning system is used to implement the positioning method as described in any one of claims 1 to 6.

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