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Pipeline leakage monitoring method, equipment and process

发布日期:2020-01-18 03:51 Document serial number: 19730142 Release date: 2020-01-18 03:51
Pipeline leakage monitoring method, equipment and process

The present application relates to the technical field of pipeline transmission, and in particular, to a method and a device for monitoring pipeline leakage.



Background technique:

Urban underground pipeline network is not only an important public facility related to national economic lifeline and national energy security, but also to underground space security. There are insufficient technical means to maintain the integrity and safety of pipeline transmission, and there are risks such as oil and gas pipeline fires, pipeline leakage and environmental pollution. There are also frequent occurrences of communication fiber cables being cut and underground cables being stolen, which have severely affected people's normal production, life, and even national security.

Pipeline leaks are caused by cracks or corrosion holes due to corrosion and aging of materials or other external forces, and there is a pressure difference between the inside and outside of the pipeline that causes the fluid in the pipeline to leak outward. The fluid is sprayed outward through cracks or corrosion holes to form a sound source, and then interacts with the pipe, and the sound source radiates energy to form a sound wave. For example, when a water supply pipe leaks, the water is sprayed out of the pipe from the leak point under pressure to form a sound source, and it is transmitted outward through different media. When the water leaks, friction occurs with the pipe wall to generate stress waves. This energy mainly propagates up and down the leak source along the pipe wall. Its relatively weak energy is the lowest, but it is extremely susceptible to environmental noise. Therefore, in practical applications, the detected stress wave is more susceptible to infection by surrounding noise, which greatly limits the application scenario.



Technical realization elements:

The present application proposes a pipeline leak monitoring method and system to solve the problem of timely and accurately determining the collection and leakage of pressure pipelines.

The embodiment of the present application provides a method for monitoring pipeline leakage, which is characterized by collecting pipeline stress waves and background noise, and obtaining the difference values of the pipeline stress waves and the background noise at each corresponding time point, and the sum of the absolute values of the corresponding time point differences When it is greater than the threshold, determine the pipeline leakage status.

Further, in the same time period, performing fft transformation on the differences at the corresponding time points to obtain the coefficients of the corresponding time points, and when the sum of the absolute values of the coefficients of the corresponding time points is greater than the first threshold, it is determined The pipeline is suspected of leaking.

Further, in the same time period, the fft transform of the stress signal of the acquisition pipeline and the background noise signal is made and difference is obtained to obtain the coefficients of the corresponding time points. When the sum of the absolute values of the coefficients of the corresponding time points is greater than the second threshold, Make sure the pipeline is suspected of leaking.

Further, the sensor for collecting the stress wave of the pipeline is hard-connected to the metal part of the pipeline to be tested through a screw or a strong magnet.

Further, the sensor for collecting background noise is arranged in the soil or well wall around the pipeline.

An embodiment of the present application further provides a pipeline leak monitoring device, which is characterized by comprising: an acquisition module, a data processing module, and an identification module, wherein the acquisition module is used to acquire pipeline stress waves and background noise; the data processing module, It is used to make a difference between the collected pipeline stress wave and background noise, and calculate the sum of the absolute values of the difference values at the corresponding time points; the identification module is used to determine the pipeline leakage state.

Further, the pipeline stress wave and the background noise are collected, and the difference values of the pipeline stress waves and the background noise at each corresponding time point are obtained. When the sum of the absolute values of the difference values at the corresponding time points is greater than the threshold, the pipeline leakage state is determined.

Further, in the same time period, performing fft transformation on the differences of the corresponding time points to obtain the coefficients of the corresponding time points, and determining the pipeline when the sum of the absolute values of the coefficients of the corresponding time points is greater than the first threshold. Suspected leak status.

Further, in the same time period, the fft transform of the stress signal of the acquisition pipeline and the background noise signal is made and difference is obtained to obtain the coefficients of the corresponding time points. When the sum of the absolute values of the coefficients of the corresponding time points is greater than the second threshold, Make sure the pipeline is suspected of leaking.

Further, the sensor for collecting the stress wave of the pipeline is hard-connected to the metal part of the pipeline to be tested by screws or strong magnets, and the sensor for collecting background noise is arranged in the soil or well wall around the pipeline.

The at least one technical solution adopted in the embodiments of the present application can achieve the following beneficial effects: by adopting such a pipeline leakage monitoring method and equipment, the effect of reducing noise, improving the signal-to-noise ratio, and real-time monitoring of pipeline leakage can be achieved.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings described here are used to provide a further understanding of the present application and constitute a part of the present application. The schematic embodiments of the present application and the description thereof are used to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

FIG. 1 is a schematic flowchart of a pipeline leakage monitoring method;

FIG. 2 is a schematic structural diagram of a pipeline leak monitoring device.

detailed description

In order to make the purpose, technical solution, and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described in combination with specific embodiments of the present application and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

The technical solutions provided by the embodiments of the present application will be described in detail below with reference to the drawings.

FIG. 1 is a schematic flowchart of a pipeline leakage monitoring method. The method can be shown as follows.

Step 101: Collect stress waves and background noise of the pipeline.

In step 101, in a state where the electrical energy of the overall operation is normally supplied, a stress wave signal of the pipeline and a background noise signal around the pipeline are collected by a sensor.

The sensor that collects the stress wave of the pipeline is the same model as the sensor that collects the background noise.

Sensors of the same model output spectrums of the same amplitude. In the method of this embodiment, sensors of the same model are used to collect the stress signal of the pipeline and the background noise signal around the pipeline to obtain spectrums of the same range of amplitude.

In another embodiment of the present invention, the method further includes:

The sensor for collecting the stress wave of the pipeline is hard-connected to the metal part of the pipeline to be tested by screws or strong magnets.

In another embodiment of the present invention, the method further includes:

The sensor for collecting background noise is arranged in the soil or well wall around the pipeline.

Step 102: Obtain the difference between the pipeline stress wave and the background noise at each corresponding time point, and calculate the sum of the absolute values of the differences at the corresponding time points.

In step 102, the signals of the pipeline stress wave and the background noise are respectively collected by the same type of sensors to obtain two sets of data of the same time period monitored by the pipeline stress wave sensor and the background noise sensor, respectively. The normalization process is performed and a difference is made at each corresponding time point to obtain the difference value of the pipeline stress wave and the background noise at each corresponding time point, and then the absolute values of the corresponding time point difference values are summed.

It should be noted that the same time period is preset based on experience and is not specifically limited.

It should be noted that the normalization processing method includes min-max normalization (min-maxnormalization) / z-score normalization, such as min-max normalization (min-maxnormalization): by traversing each data in the array, each The max and min in an array are recorded, and the data is normalized by max-min as the base: The assignments in the two arrays of the same time period monitored by the pipeline stress wave sensor and the background noise sensor are normalized to the same interval, and no specific numerical limitation is made here.

After the normalization process, the two sets of normalized data in the same time period monitored by the pipeline stress wave sensor and the background noise sensor are respectively different at corresponding time points to obtain the pipeline stress wave and background noise. At each corresponding time point difference, the absolute values of the corresponding time point differences are then summed.

For example, the time interval between adjacent sampling points is 1/7500 seconds, and the signals of the pipeline stress wave and background noise are collected according to the same type of sensors, and it is determined that the pipeline stress wave signals are: 1/7500 seconds: 0.57164v; 2/7500 seconds: 0.06561v; 3/7500 seconds: -0.47738v; 4/7500 seconds: -0.69833v; 5/7500 seconds: -0.45361v; 6/7500 seconds: 0.09978v; 7 / 7500 seconds: 0.58922v; 8/7500 seconds: 0.69649v; 9/7500 seconds: 0.34913v; 10/7500 seconds: -0.22669v; 11/7500 seconds: -0.64323v; 12/7500 seconds : -0.63115v; 13/7500 seconds: -0.19473v; 14/7500 seconds: 0.3769v; 15/7500 seconds: 0.70241v; 16/7500 seconds: 0.57228v; and so on to determine the pipeline stress Wave signal.

It is determined that the background noise signals are: 1/7500 second: 0.56993v; 2/7500 second: 0.06282v; 3/7500 second: -0.47935v; 4/7500 second: -0.6981v; 5/7500 second : -0.45107v; 6/7500 seconds: 0.10289v; 7/7500 seconds: 0.59104v; 8/7500 seconds: 0.69595v; 9/7500 seconds: 0.34666v; 10/7500 seconds: -0.22936v ; 11/7500 seconds: -0.6444v; 12/7500 seconds: -0.63007v; 13/7500 seconds: -0.19212v; 14/7500 seconds: 0.37924v; 15/7500 seconds: 0.70283v; 16/7500 seconds: 0.5704v; and so on, to determine the background noise signal.

Then the absolute value of the difference between the pipeline stress wave and the background noise at each corresponding time point is: at the 1/7500 second, the difference between the pipeline stress wave and the background noise is 0.00171v; at 2/7500 seconds, the pipeline The difference between the stress wave and the background noise is 0.00279v; at the 3/7500 second, the difference between the stress wave and the background noise is 0.00197v; at the 4/7500 second, the difference between the stress wave and the background noise is- 0.00023v; at 5/7500 seconds, the difference between the pipeline stress wave and the background noise is -0.00254v; at 6/7500 seconds, the difference between the pipeline stress wave and the background noise is -0.00311v; at 7/7500 In the second, the difference between the pipeline stress wave and the background noise is -0.00182v; in the 8/7500 second, the difference between the pipeline stress wave and the background noise is 0.00054v; in the 9/7500 second, the pipeline stress wave and the background noise are The difference is 0.00247v; at the 10/7500 second, the difference between the pipeline stress wave and the background noise is 0.00267v; at the 11/7500 second, the difference between the pipeline stress wave and the background noise is 0.00117v; at 12/7 7500 seconds, the difference between pipeline stress wave and background noise is -0.00108v; at 13/7500 seconds, pipeline stress wave and background noise The difference is -0.00261v; at the 14/7500 second, the difference between the pipeline stress wave and the background noise is -0.00234v; at the 15/7500 second, the difference between the pipeline stress wave and the background noise is -0.00042v; at At 16/7500 seconds, the difference between the pipeline stress wave and the background noise is 0.00188v; and so on, the difference between the pipeline stress wave and the background noise at each corresponding time point is determined.

Then the absolute values of the differences between the corresponding time points of the pipeline stress wave and the background noise are: The absolute values of the differences between the corresponding time points of the pipeline stress wave and the background noise are: 1/7500 seconds, The difference between pipeline stress wave and background noise is 0.00171v; at 2/7500 seconds, the difference between pipeline stress wave and background noise is 0.00279v; at 3/7500 seconds, the difference between pipeline stress wave and background noise is 0.00197v; at 4/7500 seconds, the difference between the pipeline stress wave and the background noise is 0.00223v; at 5/7500 seconds, the difference between the pipeline stress wave and the background noise is 0.00254v; at 6/7500 seconds, The difference between pipeline stress wave and background noise is 0.00311v; at 7/7500 seconds, the difference between pipeline stress wave and background noise is 0.00182v; at 8/7500 seconds, the difference between pipeline stress wave and background noise is 0.00054v; at 9/7500 seconds, the difference between the pipeline stress wave and the background noise is 0.00247v; at 10/7500 seconds, the difference between the pipeline stress wave and the background noise is 0.00267v; at 11/7500 seconds, The difference between the pipeline stress wave and the background noise is 0.00117v; at 12/7500 seconds, the pipeline stress wave and the background noise The difference between scene noise is 0.00108v; at 13/7500 seconds, the difference between pipeline stress wave and background noise is 0.00261v; at 14/7500 seconds, the difference between pipeline stress wave and background noise is 0.00234v; at At 15/7500 seconds, the difference between the stress wave and the background noise of the pipeline is 0.00042v; at 16/7500 seconds, the difference between the stress wave and the background noise of the pipeline is 0.00188v; and so on, the pipeline stress wave and the background are determined by analogy The absolute value of the noise difference at each corresponding time point.

The sum of the absolute values of the difference values of the pipeline stress waves and the background noise at corresponding time points is 0.02935v.

Step 103: When the sum of the absolute values of the difference values at the corresponding time points is greater than the threshold, determine the pipeline leakage state.

In step 103, according to the sum of the absolute values of the respective time point difference values determined in step 102, when the sum of the absolute values of the respective time point difference values is greater than a threshold value, the pipeline leakage state is determined.

It should be noted that the threshold is set in advance based on experience, and is not specifically limited here.

The technical method provided by the embodiment of the present invention collects pipeline stress waves and background noise signals by using sensors of the same model, normalizes the pipeline stress waves and background noise signals, respectively, and combines the pipeline stress wave sensors and background noise. The sensors in the two arrays of the same time period respectively monitor the assignments in the same time period to normalize to the same interval, obtain the difference between the stress wave and background noise of the pipeline at the corresponding time points in the same time period, and calculate the corresponding time points The sum of the absolute values of the differences, and the sum of the absolute values of the differences at the respective time points is greater than the threshold, to determine the pipeline leakage status. The signal-to-noise ratio of the pressure wave signal is improved, the noise impact of surrounding noise is reduced, and the real-time monitoring of pressure pipeline leakage is realized.

In another embodiment of the present invention, during the same time period, performing fft transformation on the difference between the corresponding time points to obtain the coefficients of the corresponding time points, when the sum of the absolute values of the coefficients of the corresponding time points When it is greater than the first threshold, it is determined that the pipeline is in a suspected leak state.

In the monitoring method of this embodiment, the information of the pipeline stress wave and the background noise is collected by the same type of sensor, respectively, to obtain two sets of data of the same time period monitored by the pipeline stress wave sensor and the background noise sensor, respectively. Group data is subjected to normalization processing to obtain the difference values at each corresponding time point.

For example, the time interval between adjacent sampling points is 1/7500 seconds, and the signals of the pipeline stress wave and background noise are collected according to the same type of sensors, and it is determined that the pipeline stress wave signals are: 1/7500 seconds: 0.57164v; 2/7500 seconds: 0.06561v; 3/7500 seconds: -0.47738v; 4/7500 seconds: -0.69833v; 5/7500 seconds: -0.45361v; 6/7500 seconds: 0.09978v; 7 / 7500 seconds: 0.58922v; 8/7500 seconds: 0.69649v; 9/7500 seconds: 0.34913v; 10/7500 seconds: -0.22669v; 11/7500 seconds: -0.64323v; 12/7500 seconds : -0.63115v; 13/7500 seconds: -0.19473v; 14/7500 seconds: 0.3769v; 15/7500 seconds: 0.70241v; 16/7500 seconds: 0.57228v; and so on to determine the pipeline stress Wave signal.

It is determined that the background noise signals are: 1/7500 second: 0.56993v; 2/7500 second: 0.06282v; 3/7500 second: -0.47935v; 4/7500 second: -0.6981v; 5/7500 second : -0.45107v; 6/7500 seconds: 0.10289v; 7/7500 seconds: 0.59104v; 8/7500 seconds: 0.69595v; 9/7500 seconds: 0.34666v; 10/7500 seconds: -0.22936v ; 11/7500 seconds: -0.6444v; 12/7500 seconds: -0.63007v; 13/7500 seconds: -0.19212v; 14/7500 seconds: 0.37924v; 15/7500 seconds: 0.70283v; 16/7500 seconds: 0.5704v; and so on, to determine the background noise signal.

Then the absolute value of the difference between the pipeline stress wave and the background noise at each corresponding time point is: at the 1/7500 second, the difference between the pipeline stress wave and the background noise is 0.00171v; at 2/7500 seconds, the pipeline The difference between the stress wave and the background noise is 0.00279v; at the 3/7500 second, the difference between the stress wave and the background noise is 0.00197v; at the 4/7500 second, the difference between the stress wave and the background noise is- 0.00023v; at 5/7500 seconds, the difference between the pipeline stress wave and the background noise is -0.00254v; at 6/7500 seconds, the difference between the pipeline stress wave and the background noise is -0.00311v; at 7/7500 In the second, the difference between the pipeline stress wave and the background noise is -0.00182v; in the 8/7500 second, the difference between the pipeline stress wave and the background noise is 0.00054v; in the 9/7500 second, the pipeline stress wave and the background noise are The difference is 0.00247v; at the 10/7500 second, the difference between the pipeline stress wave and the background noise is 0.00267v; at the 11/7500 second, the difference between the pipeline stress wave and the background noise is 0.00117v; at 12/7 7500 seconds, the difference between pipeline stress wave and background noise is -0.00108v; at 13/7500 seconds, pipeline stress wave and background noise The difference is -0.00261v; at the 14/7500 second, the difference between the pipeline stress wave and the background noise is -0.00234v; at the 15/7500 second, the difference between the pipeline stress wave and the background noise is -0.00042v; at At 16/7500 seconds, the difference between the pipeline stress wave and the background noise is 0.00188v; and so on, the difference between the pipeline stress wave and the background noise at each corresponding time point is determined.

Perform fft transformation on the difference between the stress wave and the background noise of the pipeline at each corresponding time point to obtain coefficients at each corresponding time point.

Using the Fourier principle and the fft method, the absolute value of the difference between the stress wave and the background noise at each corresponding time point is transformed to obtain Take the part from 0.2 to 5khz to obtain the coefficients at each corresponding time point.

When the sum of the absolute values of the coefficients at the corresponding time points is greater than the first threshold, it is determined that the pipeline is in a suspected leakage state.

When the sum of the absolute values of the coefficients at the respective time points is greater than the first threshold, it may be determined that the pipeline is in a suspected leakage state.

That is, when the pipeline leaks, the collected stress signal of the pipeline at the corresponding time point is strong, so the difference between the pipeline stress wave and the background noise at each corresponding time point will be relatively large, and the spectrum amplitude after fft transformation is relatively large. Large, at the same base frequency, the absolute value of the coefficient at the corresponding time point will also be larger, and the sum of the absolute values of the coefficients of the pipeline stress wave and the background noise at each corresponding time point will also be larger. When the sum of the absolute values of the point coefficients is greater than the first threshold, it can be determined that the pipeline is in a suspected leak state.

It should be noted that the first threshold is preset according to experience, and is not specifically limited herein.

The technical method provided by the embodiment of the present invention collects pipeline stress waves and background noise signals by using sensors of the same model, normalizes the pipeline stress waves and background noise signals, respectively, and combines the pipeline stress wave sensors and background noise. The sensors in the two arrays in the same time period respectively monitor the assignments normalized to the same interval. In the same time period, the Fourier principle is used to perform fft transformation on the differences at the corresponding time points. The coefficients of the corresponding time points are obtained. When the sum of the absolute values of the coefficients of the corresponding time points is greater than the first threshold value, it is determined that the pipeline is in a suspected leakage state. The signal-to-noise ratio of the pressure wave signal is improved, the noise impact of the surrounding noise is reduced, and the function of filtering is realized, real-time monitoring of pressure pipeline leakage is realized.

In another embodiment of the present invention, in the same time period, the fft transform and difference of the stress wave and background noise signal of the acquisition pipeline are obtained to obtain the coefficients of the corresponding time points. When the sum is greater than the second threshold, the pipeline is determined to be in a suspected leak state.

In the monitoring method of this embodiment, the information of the pipeline stress wave and the background noise is collected by the same type of sensor, respectively, to obtain two sets of data of the same time period monitored by the pipeline stress wave sensor and the background noise sensor, respectively. The set of data is subjected to normalization processing to obtain two sets of data of the pipeline stress wave and the background noise in the same interval at each corresponding time point.

For example, the time interval between adjacent sampling points is 1/7500 seconds, and the signals of the pipeline stress wave and background noise are collected according to the same type of sensors, and it is determined that the pipeline stress wave signals are: 1/7500 seconds: 0.57164v; 2/7500 seconds: 0.06561v; 3/7500 seconds: -0.47738v; 4/7500 seconds: -0.69833v; 5/7500 seconds: -0.45361v; 6/7500 seconds: 0.09978v; 7 / 7500 seconds: 0.58922v; 8/7500 seconds: 0.69649v; 9/7500 seconds: 0.34913v; 10/7500 seconds: -0.22669v; 11/7500 seconds: -0.64323v; 12/7500 seconds : -0.63115v; 13/7500 seconds: -0.19473v; 14/7500 seconds: 0.3769v; 15/7500 seconds: 0.70241v; 16/7500 seconds: 0.57228v; and so on to determine the pipeline stress Wave signal.

It is determined that the background noise signals are: 1/7500 second: 0.56993v; 2/7500 second: 0.06282v; 3/7500 second: -0.47935v; 4/7500 second: -0.6981v; 5/7500 second : -0.45107v; 6/7500 seconds: 0.10289v; 7/7500 seconds: 0.59104v; 8/7500 seconds: 0.69595v; 9/7500 seconds: 0.34666v; 10/7500 seconds: -0.22936v ; 11/7500 seconds: -0.6444v; 12/7500 seconds: -0.63007v; 13/7500 seconds: -0.19212v; 14/7500 seconds: 0.37924v; 15/7500 seconds: 0.70283v; 16/7500 seconds: 0.5704v; and so on, to determine the background noise signal.

It should be noted that the same time period is preset based on experience and is not specifically limited.

It should be noted that the normalization processing method includes min-max normalization (min-maxnormalization) / z-score normalization, such as min-max normalization (min-maxnormalization): by traversing each data in the array, each The max and min in an array are recorded, and the data is normalized by using max-min as the base: the pipeline stress wave sensor and the background noise sensor are respectively monitored in two arrays of the same time period The assignments of are normalized to the same interval, and no specific numerical limitation is made here.

After the normalization process, fft transform and difference are performed on the two sets of normalized data of the same time period monitored by the pipeline stress wave sensor and the background noise sensor, respectively, to obtain the corresponding time points. coefficient.

Using the Fourier principle and the fft method, the absolute value of the difference between the stress wave and the background noise at each corresponding time point is transformed to obtain Take the part from 0.2 to 5khz to obtain the coefficients at each corresponding time point.

When the sum of the absolute values of the coefficients at the corresponding time points is greater than the second threshold, it is determined that the pipeline is in a suspected leakage state.

When the sum of the absolute values of the coefficients at the respective time points is greater than the second threshold, it may be determined that the pipeline is in a suspected leakage state.

That is, when the pipeline leaks, the stress signal of the pipeline collected at the corresponding time point is strong, and the spectrum amplitude after the fft transformation is large. Under the same basic frequency, the absolute value of the coefficient at the corresponding time point will also be large. The sum of the absolute values of the coefficients at the corresponding time points of the pipeline stress wave and the background noise will also be relatively large. When the sum of the absolute values of the coefficients at the respective time points is greater than the second threshold, it can be determined that the pipeline is at Suspected leak status.

It should be noted that the second threshold is preset according to experience, and is not specifically limited here.

The technical method provided by the embodiment of the present invention collects pipeline stress waves and background noise signals by using sensors of the same model, normalizes the pipeline stress waves and background noise signals, respectively, and combines the pipeline stress wave sensors and background noise. The sensors in the two arrays of the same time period monitor the assignments normalized to the same interval. In the same time period, using the Fourier principle, the two sets of normalized data at each corresponding time point are normalized. The fft transform is performed to obtain the coefficients of the corresponding time points. When the sum of the absolute values of the coefficients of the corresponding time points is greater than the second threshold, it is determined that the pipeline is in a suspected leakage state. The signal-to-noise ratio of the pressure wave signal is improved, the noise impact of the surrounding noise is reduced, and the function of filtering is realized, real-time monitoring of pressure pipeline leakage is realized.

In the monitoring method of the above embodiment, specifically, the sensor for collecting the stress wave of the pipeline is hard-connected to the metal part of the pipeline to be tested by a screw or a strong magnet.

Specifically, the sensor for collecting background noise is arranged in the soil or well wall around the pipeline.

FIG. 2 is a schematic structural diagram of a pipeline leak monitoring device. The device includes a collection module 201, a data processing module 202, and an identification module 203, wherein:

The acquisition module 201 is configured to acquire stress waves and background noise of the pipeline;

The data processing module 202 is configured to make a difference between the collected pipeline stress wave and the background noise, and calculate the sum of the absolute values of the differences at the corresponding time points;

The identification module 203 is configured to determine a pipeline leakage state.

Preferably, the data processing module 202 is configured to make a difference between the collected pipeline stress wave and the background noise, and calculate the sum of the absolute values of the difference values at the corresponding time points; the identification module 203 determines the pipeline leakage state, so that The data processing module 202 and the identification module 203 may adopt any one of the following data processing and identification processes:

In the same time period, the pipeline stress wave and background noise are collected to obtain the pipeline stress wave and background noise difference values at corresponding time points. When the sum of the absolute values of the corresponding time point differences is greater than the threshold value, the pipeline leakage state is determined.

Alternatively, in the same time period, perform fft transformation on the differences at the corresponding time points to obtain the coefficients of the corresponding time points. When the sum of the absolute values of the coefficients of the corresponding time points is greater than the first threshold, determine the pipeline as Suspected leak status.

Or, in the same time period, perform fft transformation on the stress signal and background noise signal of the acquisition pipeline and make a difference to obtain the coefficients of the corresponding time points. The pipeline is suspected of leaking.

Further, the sensor for collecting the stress wave of the pipeline is hard-connected to the metal part of the pipeline to be tested by screws or strong magnets, and the sensor for collecting background noise is arranged in the soil or well wall around the pipeline.

Those skilled in the art should understand that the embodiments of the present invention may be provided as a method, a system, or a computer program product. Therefore, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk memory, cd-rom, optical memory, etc.) containing computer-usable program code.

It should also be noted that the terms "including," "including," or any other variation thereof are intended to encompass non-exclusive inclusion, so that a process, method, product, or device that includes a range of elements includes not only those elements, but also Other elements not explicitly listed, or those that are inherent to such a process, method, product, or device. Without more restrictions, the elements defined by the sentence "including a ..." do not exclude the existence of other identical elements in the process, method, product or equipment including the elements.

The above are only examples of the present application and are not intended to limit the present application. For those skilled in the art, this application may have various modifications and changes. Any modification, equivalent replacement, and improvement made within the spirit and principle of this application shall be included in the scope of claims of this application.

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