A method and system for intelligent monitoring and positioning of pipeline leakage

Abstract

The present invention discloses a method and system for intelligent monitoring and positioning of pipeline leakage, which belongs to the field of distributed acoustic wave sensing. The sensing optical fiber is continuously laid on the pipeline in a spiral winding manner. The i-th sensing channel S of the sensing optical fiber is i and the i-th position interval P of the pipeline i The time-frequency characteristics of the acoustic vibration signal are calculated in real time, one-to-one, and compared with the signals before and after to determine the signal's fluctuation coefficient. When the signal's fluctuation coefficient suddenly changes and exceeds a certain threshold, a pipeline leak is determined. The abnormal signal fragment is then extracted, and its energy change is calculated using a sliding window algorithm to determine the precise time of the leak, ultimately achieving precise location of the leak. Compared to traditional pipeline leak monitoring methods, this method can reduce false alarms and missed alarms while maintaining leak location accuracy, significantly reducing the workload of manual secondary inspections.

Description

Technical Field

[0001] The present invention belongs to the field of pipeline monitoring, and more specifically, relates to a method and system for intelligently monitoring and locating pipeline leakage. Background Art

[0002] Pipelines play a vital role in transporting oil, gas, and water, forming the infrastructure of modern industry and urban life. However, as pipelines age, leaks are inevitable, leading not only to economic losses but also to serious threats to the environment and public safety. For example, oil leaks can pollute water and soil, natural gas leaks can cause explosions and fires, and water pipe leaks can lead to waste and unstable water supply systems. Therefore, real-time monitoring of pipeline leaks is essential.

[0003] Currently, pipeline leak monitoring technologies include a variety of methods, among which distributed fiber optic sensing technology has attracted much attention due to its high sensitivity and wide coverage. This technology uses fiber optic sensors arranged along the pipeline to monitor changes in characteristic parameters in real time, effectively detecting leaks.

[0004] Among distributed fiber optic sensing technologies used for pipeline leak monitoring, the fiber optic temperature measurement method disclosed in patent CN117309261A is significantly affected by weather, making it difficult to apply to buried pipelines in the field. Furthermore, the acoustic vibration method currently lacks a reliable algorithm. The leakage coefficient calculation method mentioned in patent CN117704295A is susceptible to interference from factors both inside and outside the pipeline system, including the complexity of fluid dynamics, differences in pipeline materials, and ambient noise. These factors can lead to frequent false positives or missed positives, affecting the accuracy and reliability of leak detection. Finally, the transmission of acoustic waves during pipeline leakage is limited by the pipeline material, the properties of the internal fluid, and external environmental conditions, which can affect the accuracy of leak location, especially in complex pipeline networks. Patent CN117743765A mentions the use of a large peak value for leak location. However, due to the variable propagation velocity of acoustic waves in pipelines, this approach can lead to leak location errors.

[0005] In summary, although distributed fiber optic sensing technology has excellent performance in pipeline monitoring, there are still certain deficiencies in the judgment and positioning algorithm of pipeline leaks: the algorithm has weak universality, and a single algorithm is difficult to apply to pipelines under different conditions, which easily leads to false alarms and missed alarms. At the same time, the positioning range is also limited, which restricts the promotion of this technology in the field of pipeline leakage monitoring. Summary of the Invention

[0006] In response to the defects of the existing technology and the need for improvement, the purpose of the present invention is to provide a method for intelligent monitoring and positioning of pipeline leaks, aiming to solve the problems of the current pipeline leak identification algorithm being prone to false alarms and missed alarms, insufficient positioning accuracy and poor universality.

[0007] To achieve the above objectives, the present invention provides a method and system for intelligent monitoring and locating pipeline leaks, focusing on processing the acoustic wave signals of the transmission medium in the pipeline to achieve intelligent monitoring of pipeline leaks and high-precision positioning of the leak point. After a pipeline leak occurs, the coupling between the transmission medium and the pipeline changes, and its flow and acoustic wave vibration characteristics also change accordingly. A distributed acoustic wave sensing system can detect this signal in real time. The sensing fiber is continuously laid out in a spiral winding manner on the pipeline. The i-th sensing channel S of the sensing fiber is a i and the i-th position interval P of the pipeline i One-to-one correspondence, mapping different sensing channels of the sensing fiber to the corresponding position intervals of the pipeline, establishing a corresponding relationship, i = 1, 2, ···, includes the following steps:

[0008] A distributed fiber optic acoustic wave sensing system is used to obtain the acoustic wave vibration signal generated by the mutual coupling between the transmission medium of the monitored pipeline and the pipeline;

[0009] Calculate the time domain characteristics and frequency domain characteristics of the acoustic vibration signals of all optical fiber sensing channels, and calculate the fluctuation coefficient of the time domain characteristics and frequency domain characteristics. The time domain characteristic is the time domain average amplitude of the acoustic vibration signal of the transmission medium, the frequency domain characteristic is the energy distribution center of the acoustic vibration signal of the transmission medium in the frequency domain, and the fluctuation coefficient is the rate of change of the time domain characteristics and frequency domain characteristics of the acoustic vibration signal at the current sampling moment relative to the signal at the previous sampling moment. A sudden change in the fluctuation coefficient indicates a possible pipeline leak.

[0010] The fluctuation coefficient of each pipeline position interval is calculated in real time to determine whether the pipeline is leaking. The sampling time period and pipeline position interval of the leak are obtained, and the frequency range where the acoustic vibration signal changes significantly after the pipeline leak, that is, the abnormal signal frequency band caused by the pipeline leak, is calculated.

[0011] The leakage sampling period is the sampling period when the fluctuation coefficient suddenly changes;

[0012] The leaking pipeline location interval is the pipeline location interval where the fluctuation coefficient suddenly changes;

[0013] The abnormal frequency band is the frequency band range obtained by superimposing the frequency bands in which the energy ratio fluctuation exceeds 10 times the total energy fluctuation in all frequency bands obtained by wavelet decomposition of the acoustic vibration signal after leakage;

[0014] The sliding window algorithm is used to calculate the energy change of the abnormal frequency band in the sampling time period when the leakage occurs. The energy mutation time is the exact time when the pipeline leakage occurs. The interval where the energy mutation phenomenon first appears is the precise location interval of the leakage. Finally, the precise location of the leakage point is calculated based on the energy mutation time of the precise location interval and the adjacent pipeline location intervals.

[0015] Furthermore, the optical fiber is continuously laid on the pipeline in a spiral winding manner, with the starting point of the laying of the optical fiber as the zero point, and the i-th sensing channel S of the optical fiber i and the i-th position interval P of the pipeline i One-to-one correspondence, the mapping relationship is:

[0016] S i ∈((i-1)*L s ,i*L s )

[0017]

[0018] Among them L s is the length of a sensing channel of the sensing fiber, that is, the resolution of the sensing fiber, D is the outer diameter of the pipe, and the sensing channel S of the optical fiber is converted to i Mapped to the pipeline position interval P i Fiber optic sensing channel S i The monitored acoustic vibration signal is also the position interval P on the pipeline i The original signal generated in .

[0019] Furthermore, the time-frequency characteristics of the acoustic vibration signal are calculated. First, the average amplitude of the acoustic vibration signal of all the optical fiber sensing channels in the time domain is calculated to obtain the transmission medium acoustic vibration signal along the pipeline, where the pipeline position interval P i The average amplitude A of the medium acoustic vibration signal i for:

[0020]

[0021] where e j is the time domain signal amplitude corresponding to the jth data point in the acoustic vibration signal collected in the current sampling interval, F s is the signal sampling rate, T is the sampling time;

[0022] Wavelet energy decomposition is used to automatically calculate the energy distribution of all sensor channel signals in different frequency bands and adaptively calculate the decomposition level. For this method, the db3 wavelet is used as the basis function. To ensure that the frequency band width of the acoustic vibration signal after wavelet decomposition is around 100Hz, the decomposition level n of the wavelet decomposition is set to:

[0023]

[0024] After decomposition, the width of each frequency band is And all are less than or equal to 100Hz to ensure the fineness of frequency band division;

[0025] Calculate the energy of each frequency band after decomposition. The acoustic vibration signal is decomposed into 2 after wavelet decomposition. n frequency bands, and the wavelet coefficient of the kth decomposition level frequency band is D k (k∈[1,2 n ]), then the energy of this frequency band E k for:

[0026]

[0027] The frequency band range of the kth decomposition level frequency band is Its center frequency Then the pipeline position interval P i The energy distribution center E of the signal in the frequency domain i for:

[0028]

[0029] At this point, the time-frequency characteristics of the pipeline acoustic vibration signal have been calculated. Next, the fluctuation coefficient of the time-frequency characteristics is calculated, and the change in the fluctuation coefficient is used to determine whether the pipeline is leaking.

[0030] Pipeline position interval P i The average amplitude in the tth sampling interval Volatility coefficient for:

[0031]

[0032] in is the average amplitude of the acoustic vibration signal measured in the t-th sampling interval, is the average amplitude of the acoustic vibration signal measured in the t-1 sampling interval;

[0033] Pipeline position interval P i The center of gravity of energy distribution in the tth sampling interval Volatility coefficient for:

[0034]

[0035] in is the energy distribution center of the acoustic vibration signal measured in the t-th sampling interval, is the energy distribution center of the acoustic vibration signal measured in the t-1 sampling interval;

[0036] Then the pipeline position interval P i The total fluctuation coefficient in the tth sampling interval for:

[0037]

[0038] Finally, according to the volatility coefficient The fluctuation coefficient is used to determine whether the pipeline is leaking. When the pipeline is operating normally, its fluctuation coefficient will remain in a stable range. When the fluctuation coefficient suddenly changes, it means that the pipeline is leaking. The specific judgment method is as follows;

[0039] In the t-th sampling interval, the first five groups of sampling interval signals are taken to calculate the amplitude and the fluctuation coefficient of the energy distribution center, and the average value is compared with the fluctuation coefficient of the t-th sampling interval to calculate B1. The calculation formula is:

[0040]

[0041] If B1>10%, it is considered that the pipeline is abnormal. At this time, the system continues to collect the acoustic vibration signals of the next 5 sampling intervals. The fluctuation coefficients of the acoustic vibration signals of the previous and next 5 sampling intervals are compared and calculated to obtain B2. The calculation formula is:

[0042]

[0043] If B2 still exceeds 10%, it is determined that the pipeline is leaking. In the tth sampling interval, the pipeline position interval P i When a leak occurs, multiple locations may be identified as leaks. Therefore, it is necessary to automatically extract the abnormal frequency band of the signal and use a sliding window algorithm to further confirm the precise time point of the pipeline leak and then determine the leak location of the pipeline.

[0044] The range of abnormal frequency bands automatically extracted is: the energy fluctuation coefficient of each frequency band after the acoustic vibration signal of the leakage location interval is decomposed by wavelet

[0045]

[0046] The abnormal frequency band is the frequency band whose energy ratio fluctuation exceeds 10 times of the total energy fluctuation in all frequency bands generated after the signal is decomposed by wavelet. The total frequency band range after superposition is F M for;

[0047]

[0048] Automatically calculate the sliding window parameters, where the size of the sliding window W s And the sliding step length S is:

[0049]

[0050] Perform FFT on the signal intercepted by the sliding window and then extract the F M frequency band, calculate the change of the total energy of the frequency band as the sliding window moves. M The energy of the frequency band will mutate. If the peak of the mutation occurs at time T P , the trough appears at time T T , then the exact time when the pipeline leaks is determined to be:

[0051]

[0052] If multiple locations are identified as leaks, the exact time of the leaks in the different locations is compared, and the location where the leak occurred the earliest is determined to be the leaking location. At this point, the location and exact time of the pipeline leak are known. To improve positioning accuracy, the specific location of the leak can be further determined.

[0053] Take the leakage interval and its two adjacent tracks, a total of three position intervals. The time when the leakage occurs in the leakage interval is T L1 The time when the leakage occurs in the adjacent interval on the left is T L2 The time when the leakage occurs in the adjacent interval on the right is T L3 , then it occurs in the position interval P i The specific location of the leakage point is:

[0054]

[0055] After confirming that the pipeline has been repaired, the pipeline monitoring algorithm is initialized and a new round of monitoring is carried out on the pipeline.

[0056] The present invention also provides a system for intelligent monitoring and positioning of pipeline leakage, comprising: a computer-readable storage medium and a processor;

[0057] The computer-readable storage medium is used to store executable instructions;

[0058] The processor is used to read the executable instructions stored in the computer-readable storage medium to execute the above-mentioned method for intelligent monitoring and positioning of pipeline leakage.

[0059] Compared with the prior art, the above technical solutions proposed by the present invention can achieve the following:

[0060] Beneficial effects:

[0061] (1) The present invention provides a method and system for intelligent pipeline leakage monitoring and location. This solution uses a distributed fiber-optic acoustic wave sensing system to measure the acoustic vibration signal of the pipeline transmission medium in real time. It is a long-distance, real-time, non-invasive pipeline leakage monitoring solution. The pipeline leakage is determined by calculating the fluctuation coefficient of the time domain characteristics and frequency domain characteristics of the acoustic vibration signal of the pipeline transmission medium. This algorithm combines the time domain characteristics, frequency domain characteristics and fluctuation coefficient, and has a low false alarm and missed alarm rate, greatly improving the efficiency of pipeline leakage monitoring.

[0062] (2) The present invention provides an intelligent pipeline leakage monitoring and positioning method. After monitoring the approximate interval of the pipeline leakage, the segment of the acoustic vibration signal after the pipeline leakage is extracted, the abnormal frequency band range is automatically calculated, and the energy change curve is calculated through the sliding window to determine the exact time of the leakage, and finally the leakage point is positioned with high precision. The sliding window algorithm can realize the automation of calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A flow chart of a pipeline leakage intelligent monitoring and positioning method provided by the present invention;

[0064] Figure 2 A schematic diagram of a pipeline leakage monitoring system provided by the present invention;

[0065] Figure 3 A flow chart of the pipeline leakage determination method provided by the present invention;

[0066] Figure 4 This is a flow chart of the pipeline leakage point locating method provided by the present invention. DETAILED DESCRIPTION

[0067] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0068] The present invention provides a method for intelligent monitoring and positioning of pipeline leakage, which can detect the signal in real time through a distributed acoustic wave sensing system. The sensing optical fiber is continuously laid on the pipeline in a spiral winding manner. The i-th sensing channel S of the sensing optical fiber is i and the i-th position interval P of the pipeline i One-to-one correspondence, mapping different sensing channels of the sensing fiber to the corresponding position intervals of the pipeline, establishing a corresponding relationship, i = 1, 2, ···, includes the following steps:

[0069] A distributed fiber optic acoustic wave sensing system is used to obtain the acoustic wave vibration signal generated by the mutual coupling between the transmission medium of the monitored pipeline and the pipeline;

[0070] Calculate the time domain characteristics and frequency domain characteristics of the acoustic vibration signals of all optical fiber sensing channels, and calculate the fluctuation coefficient of the signal's time domain characteristics and frequency domain characteristics. The time domain characteristic is the time domain average amplitude of the transmission medium's acoustic vibration signal, the frequency domain characteristic is the energy distribution center of the transmission medium's acoustic vibration signal in the frequency domain, and the fluctuation coefficient is the rate of change of the acoustic vibration signal's time domain characteristics and frequency domain characteristics at the current sampling moment relative to the signal at the previous sampling moment. A sudden change in the fluctuation coefficient indicates a possible pipeline leak.

[0071] The fluctuation coefficient of each pipeline position interval is calculated in real time to determine whether the pipeline is leaking. The sampling time period and pipeline position interval of the leak are obtained, and the frequency range where the acoustic vibration signal changes significantly after the pipeline leak, that is, the abnormal signal frequency band caused by the pipeline leak, is calculated.

[0072] The leakage sampling period is the sampling period when the fluctuation coefficient suddenly changes;

[0073] The leaking pipeline location interval is the pipeline location interval where the fluctuation coefficient suddenly changes;

[0074] The abnormal frequency band is the frequency band range obtained by superimposing the frequency bands in which the energy ratio fluctuation exceeds 10 times the total energy fluctuation in all frequency bands obtained by wavelet decomposition of the acoustic vibration signal after leakage;

[0075] The sliding window algorithm is used to calculate the energy change of the abnormal frequency band in the sampling time period of the leakage. The energy mutation time is the exact time when the pipeline leakage occurs. The interval where the energy mutation phenomenon first occurs is the exact location interval of the leakage. Finally, the exact location of the leakage point is calculated based on the energy mutation time of the precise location interval and the adjacent pipeline location intervals. The detailed flow chart is as follows Figure 1 shown.

[0076] Specifically, the optical fiber is continuously laid on the pipeline in a spiral winding manner, with the starting point of the optical fiber being the zero point, and the i-th sensing channel S of the optical fiber i and the i-th position interval P of the pipeline i One-to-one correspondence, such as Figure 2 As shown, the mapping relationship is:

[0077] S i ∈((i-1)*L s ,i*L s )

[0078]

[0079] Among them Ls is the length of a sensing channel of the sensing fiber, that is, the resolution of the sensing fiber, D is the outer diameter of the pipe, and the sensing channel S of the optical fiber is converted to i Mapped to the pipeline position interval P i Fiber optic sensing channel S i The monitored acoustic vibration signal is also the position interval P on the pipeline i The original signal generated in .

[0080] Specifically, the time-frequency characteristics of the acoustic vibration signal are calculated. First, the average amplitude of the acoustic vibration signal of all optical fiber sensing channels in the time domain is calculated to obtain the transmission medium acoustic vibration signal along the pipeline, where the pipeline position interval P i The average amplitude A of the medium acoustic vibration signal i for:

[0081]

[0082] where e j is the time domain signal amplitude corresponding to the jth data point in the acoustic vibration signal collected in the current sampling interval, F s is the signal sampling rate, T is the sampling time;

[0083] Wavelet energy decomposition is used to automatically calculate the energy distribution of all sensor channel signals in different frequency bands and adaptively calculate the decomposition level. For this method, the db3 wavelet is used as the basis function. To ensure that the frequency band width of the acoustic vibration signal after wavelet decomposition is around 100Hz, the decomposition level n of the wavelet decomposition is set to:

[0084]

[0085] After decomposition, the width of each frequency band is And all are less than or equal to 100Hz to ensure the fineness of frequency band division;

[0086] Calculate the energy of each frequency band after decomposition. The acoustic vibration signal is decomposed into 2 after wavelet decomposition. n frequency bands, and the wavelet coefficient of the kth decomposition level frequency band is D k (k∈[1,2 n ]), then the energy of this frequency band E k for:

[0087]

[0088] The frequency band range of the kth decomposition level frequency band is Its center frequency Then the pipeline position interval P i The energy distribution center E of the signal in the frequency domain i for:

[0089]

[0090] At this point, the time-frequency characteristics of the pipeline acoustic vibration signal have been calculated. Next, the fluctuation coefficient of the time-frequency characteristics is calculated, and the change in the fluctuation coefficient is used to determine whether the pipeline is leaking.

[0091] Pipeline position interval P i The average amplitude in the tth sampling interval Volatility coefficient for:

[0092]

[0093] in is the average amplitude of the acoustic vibration signal measured in the t-th sampling interval, is the average amplitude of the acoustic vibration signal measured in the t-1 sampling interval;

[0094] Pipeline position interval P i The center of gravity of energy distribution in the tth sampling interval Volatility coefficient for:

[0095]

[0096] in is the energy distribution center of the acoustic vibration signal measured in the t-th sampling interval, is the energy distribution center of the acoustic vibration signal measured in the t-1 sampling interval;

[0097] Then the pipeline position interval P i The total fluctuation coefficient in the tth sampling interval for:

[0098]

[0099] Finally, according to the volatility coefficient The fluctuation coefficient is used to determine whether the pipeline is leaking. When the pipeline is operating normally, its fluctuation coefficient will remain in a stable range. When the fluctuation coefficient suddenly changes, it means that the pipeline is leaking. The specific judgment method is as follows;

[0100] In the t-th sampling interval, the first five groups of sampling interval signals are taken to calculate the amplitude and the fluctuation coefficient of the energy distribution center, and the average value is compared with the fluctuation coefficient of the t-th sampling interval to calculate B1. The calculation formula is:

[0101]

[0102] If B1>10%, it is considered that the pipeline is abnormal. At this time, the system continues to collect the acoustic vibration signals of the next 5 sampling intervals. The fluctuation coefficients of the acoustic vibration signals of the previous and next 5 sampling intervals are compared and calculated to obtain B2. The calculation formula is:

[0103]

[0104] If B2 still exceeds 10%, it is determined that the pipeline is leaking. In the tth sampling interval, the pipeline position interval P i A leak has occurred, the detailed flow chart is as follows Figure 3 At this time, multiple location intervals may be identified as leaks, so it is necessary to automatically extract the abnormal frequency band of the signal and further confirm the precise time point of the pipeline leak through the sliding window algorithm, and then determine the leak location of the pipeline;

[0105] The range of abnormal frequency bands automatically extracted is: the energy fluctuation coefficient of each frequency band after the acoustic vibration signal of the leakage location interval is decomposed by wavelet

[0106]

[0107] The abnormal frequency band is the frequency band whose energy ratio fluctuation exceeds 10 times of the total energy fluctuation in all frequency bands generated after the signal is decomposed by wavelet. The total frequency band range after superposition is F M for;

[0108]

[0109] Automatically calculate the sliding window parameters, where the size of the sliding window W s And the sliding step length S is:

[0110]

[0111] Perform FFT on the signal intercepted by the sliding window and then extract the F M frequency band, calculate the change of the total energy of the frequency band as the sliding window moves. M The energy of the frequency band will mutate. If the peak of the mutation occurs at time T P , the trough appears at time T T , then the exact time when the pipeline leaks is determined to be:

[0112]

[0113] If multiple locations are identified as leaks, the exact time of the leaks in the different locations is compared, and the location where the leak occurred the earliest is determined to be the leaking location. At this point, the location and exact time of the pipeline leak are known. To improve positioning accuracy, the specific location of the leak can be further determined.

[0114] Take the leakage interval and its two adjacent tracks, a total of three position intervals. The time when the leakage occurs in the leakage interval is T L1 The time when the leakage occurs in the adjacent interval on the left is T L2 The time when the leakage occurs in the adjacent interval on the right is T L3 , then it occurs in the position interval P i The specific location of the leakage point is:

[0115]

[0116] After confirming the pipeline repair, the pipeline monitoring algorithm is initialized and a new round of pipeline monitoring is carried out. The detailed flow chart is as follows: Figure 4 shown.

[0117] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for intelligent monitoring and positioning of pipeline leakage, wherein a sensing optical fiber is continuously laid on the pipeline in a spiral winding manner, and the i-th sensing channel S of the sensing optical fiber is i and the i-th position interval P of the pipeline i One-to-one correspondence, i=1,2,···, characterized in that, The following steps are involved: (1) Obtaining the acoustic vibration signal of each position interval of the monitored pipeline; (2) calculating the time domain characteristics and frequency domain characteristics of the acoustic vibration signal according to the acoustic vibration signal, and calculating the fluctuation coefficients of the time domain characteristics and the frequency domain characteristics; The time domain feature is the time domain average amplitude of the acoustic vibration signal; The frequency domain feature is the energy distribution center of the acoustic vibration signal in the frequency domain; The fluctuation coefficient is the rate of change of the time domain characteristics and frequency domain characteristics of the acoustic vibration signal at the current sampling moment relative to the previous sampling moment. A sudden change in the fluctuation coefficient indicates a pipeline leak. (3) Determine whether the pipeline leaks in each position interval, obtain the sampling time period and pipeline position interval of the leak, and calculate the frequency band in which the energy ratio of the acoustic vibration signal fluctuates after the pipeline leak, that is, the abnormal frequency band of the signal caused by the pipeline leak; The leakage sampling period is the sampling period when the fluctuation coefficient suddenly changes; The leaking pipeline location interval is the pipeline location interval where the fluctuation coefficient suddenly changes; The abnormal frequency band is the frequency band range obtained by superimposing the frequency bands in which the energy ratio fluctuation exceeds 10 times the total energy fluctuation in all frequency bands obtained by wavelet decomposition of the acoustic vibration signal after leakage; (4) Calculate the energy change of the acoustic vibration signal in the abnormal frequency band of the signal caused by pipeline leakage. The time when the energy change suddenly occurs is the exact time when the pipeline leaks. The interval where the energy sudden change first occurs is the exact position interval where the leak occurs. Finally, the exact position of the leakage point is calculated based on the energy sudden change time of the exact position interval and the adjacent pipeline position intervals before and after it.

2. The method according to claim 1, characterized in that The i-th sensing channel S of the sensing optical fiber i and the i-th position interval P of the pipeline i One-to-one correspondence, specifically: For a pipeline with a total length of L, the starting point of the sensing fiber is taken as the zero point, and the i-th sensing channel S of the sensing fiber is i and the i-th position interval P of the pipeline i One-to-one correspondence, the mapping relationship is: S i ∈((i-1)*L s ,i*L s ) Among them L s is the length of a sensing channel of the sensing fiber, that is, the resolution of the sensing fiber, D is the outer diameter of the pipe, The maximum number of fiber optic sensing channels that can be laid on the pipeline.

3. The method according to claim 2, characterized in that The time domain features and frequency domain features in step (2) are: Time domain characteristics: Among them, F s is the signal sampling rate, T is the sampling time, and the total number of acoustic vibration signals collected in the current sampling interval is F s *T data points, e j is the time domain signal amplitude corresponding to the jth data point, 1≤j≤F s *T; Frequency domain characteristics: in, It represents the frequency band energy of the kth decomposition level frequency band after wavelet decomposition, represents the center frequency of the kth decomposition level frequency band, n is the decomposition level of wavelet decomposition, D k is the wavelet coefficient of the kth decomposition level frequency band.

4. The method according to claim 3, characterized in that The fluctuation coefficient in step (2) includes: Pipeline position interval P i The average amplitude fluctuation coefficient in the tth sampling interval for: in is the pipeline position interval P measured in the tth sampling interval i The average amplitude of the acoustic vibration signal, The pipeline position interval P is measured within the t-1 sampling interval i The average amplitude of the acoustic vibration signal; Pipeline position interval P i Energy distribution center fluctuation coefficient in the tth sampling interval for: in is the pipeline position interval P measured in the tth sampling interval i The energy distribution center of the acoustic vibration signal, The pipeline position interval P is measured within the t-1 sampling interval i The center of gravity of energy distribution of the acoustic vibration signal; Pipeline position interval P i The total fluctuation coefficient in the tth sampling interval for:

5. The method according to claim 4, characterized in that In the step (3), the fluctuation coefficient Determine pipeline leakage, including: In the t-th sampling interval, the fluctuation coefficients of the acoustic vibration signals of the first five groups of sampling intervals are taken and the average value is calculated. The average value is compared with the fluctuation coefficient of the t-th sampling interval to obtain B1. The calculation formula is: If B1>10%, it is considered that the pipeline is abnormal. Take the acoustic vibration signals of the last 5 sampling intervals, and compare the fluctuation coefficients of the acoustic vibration signals of the first and last 5 sampling intervals to obtain B2. The calculation formula is: If B2 still exceeds 10%, it is determined that the pipeline is leaking. In the tth sampling interval, the pipeline position interval P i A leak has occurred.

6. The method according to claim 5, characterized in that The frequency bands where the energy ratio of the acoustic vibration signal after pipeline leakage is calculated to fluctuate, i.e., the frequency bands where the signal is abnormal due to pipeline leakage, include: Calculate the energy fluctuation coefficient of each frequency band of the acoustic vibration signal in the leakage location interval after wavelet decomposition The abnormal frequency band is the frequency band whose energy ratio fluctuation exceeds 10 times of the total energy fluctuation in all frequency bands generated after the signal is decomposed by wavelet. The total frequency band range after superposition is F M for:

7. The method according to claim 6, characterized in that In step (4), a sliding window algorithm is used to calculate the energy change of the acoustic vibration signal in the abnormal frequency band of the signal caused by the pipeline leakage, including: Automatically calculate the sliding window parameters, where the size of the sliding window W s And the sliding step length S is: Perform FFT on the signal intercepted by the sliding window and then extract the F M frequency band, calculate the change of the total energy of the frequency band as the sliding window moves; when the pipeline leaks, F M The energy of the frequency band will mutate. If the peak of the mutation occurs at time T P , the trough appears at time T T , then the exact time when the pipeline leaks is determined to be:

8. The method according to claim 7, characterized in that In step (4), the interval where the energy mutation first occurs is the precise location interval where the leakage occurs, including: If multiple location intervals are identified as leaks, the precise time at which the pipeline leaked in different location intervals is compared, and the location interval where the leak occurred earliest is determined to be the precise location interval where the leak occurred.

9. The method according to claim 8, characterized in that In the step (4), the precise location of the leak point is calculated based on the energy mutation time of the precise location interval and the adjacent pipeline location intervals before and after it, including: Take the precise location interval and its adjacent pipeline location intervals, a total of 3 location intervals. The time when the precise location interval detects the leakage is T L1 The time when the leakage is detected in the previous position interval is T L2 The time when the leakage occurs in the next position interval is T L3 , then it occurs in the position interval P i The specific location of the leakage point is:

10. A system for intelligent monitoring and positioning of pipeline leakage, characterized in that: include: Computer-readable storage media and processor; The computer-readable storage medium is used to store executable instructions; The processor is used to read the executable instructions stored in the computer-readable storage medium and execute the method for intelligent monitoring and positioning of pipeline leakage according to any one of claims 1 to 9.

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