Oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave flux balance

Abstract

The application provides a pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave flux balance, and relates to the technical field of oil and gas pipeline safety monitoring. The monitoring system comprises a multi-source sensing module, a data preprocessing module, a fusion analysis module, a positioning calculation module, an alarm response module, a data management module and a pipeline three-dimensional geographic information module, and is characterized in that the multi-source sensing module is used for collecting vibration signals, temperature signals, pressure infrasound signals and flow signals of the pipeline, and comprises a distributed optical fiber sensing unit, a negative pressure wave infrasound collecting unit and a flow collecting unit. Compared with the prior art, the application has the effect of comprehensive and accurate monitoring, has stronger anti-interference capability, can cope with different terrain environments such as plains, mountainous areas and cities, and complex working conditions such as negative pressure zones, frequently started and stopped pumps and multiple interferences, and has strong environmental adaptability and working condition compatibility.

Description

Technical Field

[0001] This invention relates to the field of oil and gas pipeline safety monitoring technology, specifically to an oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transport balance. Background Technology

[0002] Oil and gas pipelines, as core infrastructure for energy transportation, have advantages such as large transport capacity, high efficiency, and low cost. However, they have long faced the risk of leakage, including corrosion and perforation, construction damage, and oil theft through drilling. Leaks not only cause huge energy and economic losses, but may also trigger serious safety accidents such as environmental pollution, fires, and explosions, threatening the lives and property of nearby residents. Therefore, developing an efficient and accurate pipeline leak monitoring system is of great practical significance. Currently, oil and gas pipeline leak monitoring technologies mainly include single technologies such as distributed optical fiber monitoring technology, negative pressure wave monitoring technology, and flow balance monitoring technology, as well as some combined monitoring schemes. However, existing technologies still have many shortcomings. Although single distributed optical fiber monitoring technology has the advantages of long-distance and high-density monitoring and can capture pipeline vibration and temperature anomalies, it is greatly affected by environmental noise interference and has insufficient accuracy in identifying minor leaks. Moreover, relying solely on vibration or temperature signals makes it difficult to completely distinguish between leaks and non-leakage events. On the other hand, single negative pressure wave flow balance monitoring technology judges leaks by pressure changes and flow differences, and has a fast response speed. However, its spatial positioning accuracy depends on the density of monitoring points, and there are monitoring blind spots for long-distance pipelines. Furthermore, in complex operating conditions such as negative pressure zones and multiphase flow, pressure signals are easily distorted, resulting in a high rate of missed and false alarms.

[0003] Therefore, this invention proposes a monitoring system that deeply integrates distributed optical fiber and negative pressure wave transmission balance technology. By collaboratively acquiring multi-source data and using intelligent algorithm fusion analysis, it overcomes the shortcomings of existing technologies and achieves efficient identification and accurate location of leaks in oil and gas pipelines. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transport balance, in order to solve the problems of insufficient positioning accuracy, weak anti-interference ability, and poor adaptability to complex working conditions in existing monitoring technologies.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A leak monitoring system for oil and gas pipelines based on distributed optical fiber combined with negative pressure wave transport balance includes a multi-source sensing module, a data preprocessing module, a fusion analysis module, a positioning calculation module, an alarm response module, a data management module, and a pipeline three-dimensional geographic information module. The system is characterized in that the multi-source sensing module is used to collect vibration signals, temperature signals, pressure infrasound signals, and flow signals of the pipeline, and includes a distributed optical fiber sensing unit, a negative pressure wave infrasound acquisition unit, and a flow acquisition unit. The data preprocessing module performs noise reduction, filtering and standardization on the acquired multi-source signals, including a vibration signal noise reduction submodule, a temperature signal correction submodule, a pressure and flow signal filtering submodule and a signal standardization submodule. The fusion analysis module extracts feature parameters from multi-source signals and uses data fusion and intelligent algorithms to achieve accurate judgment of leakage events. It includes a feature extraction submodule, a multi-source data fusion submodule, and a leakage judgment submodule. The positioning calculation module combines the high-density spatial positioning advantages of distributed optical fiber with the high-precision time difference positioning principle of negative pressure wave to achieve accurate calculation of the leakage point. The alarm response module quickly issues a tiered alarm based on the judgment result of the fusion analysis module and the positioning information of the positioning calculation module. The data management module is responsible for storing, querying, statistically analyzing, and sharing monitoring data, alarm information, system parameters, etc., providing data support for pipeline operation management and maintenance decisions; The pipeline 3D geographic information module integrates topographic, geomorphological, and surrounding environmental data along the pipeline route, and overlays the leak location results onto the 3D map to achieve a visual display of the leak location.

[0006] Furthermore, the distributed optical fiber sensing unit of the multi-source sensing module has a sensor optical fiber densely laid every meter along the entire oil and gas pipeline. Rayleigh scattering is used to detect vibration signals, and Raman scattering is used to detect temperature signals, achieving high-density monitoring at the meter level. The negative pressure wave infrasound acquisition unit is an integrated infrasound pressure sensor. The sensor has a built-in data fitting algorithm to achieve an acquisition frequency of not less than 100Hz and an acquisition accuracy better than 0.0001MPa. The flow acquisition unit uses a high-precision flow meter to collect the instantaneous flow rate and cumulative flow rate data of the pipeline medium in real time.

[0007] Furthermore, the vibration signal noise reduction submodule of the data preprocessing module uses wavelet transform algorithm to remove environmental noise interference and retain leakage-related characteristic vibration signals; the temperature signal correction submodule uses environmental temperature compensation algorithm to eliminate the influence of external temperature changes on pipeline body temperature monitoring; the pressure and flow signal filtering submodule uses adaptive Kalman filtering algorithm to filter signal fluctuations caused by non-leakage events such as pump and valve start-up and shutdown; and the signal standardization submodule converts signals of different types and magnitudes into standardized data of a unified dimension.

[0008] Furthermore, the feature extraction submodule of the fusion analysis module extracts the dominant frequency, amplitude, and period parameters from the vibration signal, the abnormal temperature change rate parameter from the temperature signal, and the pressure drop rate and transmission difference change parameters from the pressure / flow signal. The multi-source data fusion submodule uses DS evidence theory to fuse the vibration / temperature characteristics of the distributed optical fiber with the pressure / flow characteristics of the negative pressure wave-transmission balance. The leakage judgment submodule integrates the transmission difference transient model method, AI identification method, graffiti intelligent fuzzy analysis method, and special signal joint diagnosis method. It outputs the leakage probability based on the fused features. When the leakage probability is greater than 90%, it is judged as a leakage event.

[0009] Furthermore, the location method steps of the alarm response module are divided into: Step 1: Preliminary location step of distributed optical fiber, based on the time delay of backscattered light of Rayleigh scattering, to determine the approximate spatial range of the leakage event, with a location error of no more than 10 meters; Step 2: Negative pressure wave precise correction step. Based on the time difference τ0 between the upstream and downstream negative pressure wave infrasound acquisition units receiving the leakage wave, the distance from the leak point to the head end is calculated using the formula X=1 / 2 (L+ατ0), where X is the distance from the leak point to the head end pressure measurement point, L is the total length of the pipeline, and a is the propagation speed of the pressure sound wave in the pipeline medium. Step 3: Fusion positioning step, which weights and fuses the preliminary positioning results of distributed optical fiber with the accurate calculation results of negative pressure wave, and the final positioning accuracy is better than ±50 meters.

[0010] Furthermore, the graded alarm submodule classifies alarm levels into Level 1 emergency leak, Level 2 suspected leak, and Level 3 abnormal warning based on the probability and scale of leakage. The multi-channel notification submodule simultaneously pushes alarm information through voice broadcasts, SMS reminders, platform pop-ups, and audible and visual alarms. The emergency linkage submodule can be linked with the PLC system of the pipeline control center to realize emergency pump shutdown, valve closure, and other operations.

[0011] Furthermore, the distributed optical fiber sensing unit adopts wavelength division multiplexing technology to simultaneously detect vibration and temperature signals. The signal sampling rate is not less than 1kHz, the vibration monitoring frequency band covers 0.1Hz to 100Hz, the temperature monitoring range is -20℃ to 120℃, and the temperature measurement accuracy is better than ±0.5℃.

[0012] Furthermore, the data management module adopts a C / S+B / S hybrid architecture. The C / S architecture is used for the on-site monitoring terminal to efficiently process high-density, high-precision data sources, realize real-time data curve display, output bar chart statistics, and historical data playback functions. The B / S architecture is used for the remote centralized management platform to allocate multi-user permissions and realize monitoring data query, alarm record statistics, and system parameter configuration functions.

[0013] This invention provides a leak monitoring system for oil and gas pipelines based on distributed optical fiber combined with negative pressure wave transport balancing. It has the following beneficial effects: 1. This invention provides a leak monitoring system for oil and gas pipelines based on distributed optical fiber combined with negative pressure wave flow balance. Compared with existing technologies, it has a comprehensive and accurate monitoring effect. It integrates vibration and temperature monitoring of distributed optical fiber with pressure and flow monitoring of negative pressure wave and flow balance, thereby realizing multi-dimensional and full-parameter pipeline status monitoring. It effectively covers different types and scales of leak events, avoids the monitoring blind spots of single technologies, and combines the meter-level high-density positioning of distributed optical fiber with the accurate calculation of time difference of negative pressure wave. Through weighted fusion algorithm, it achieves meter-level positioning of leak points with a positioning accuracy within an error range of 50 meters, which greatly improves the monitoring accuracy.

[0014] 2. This invention provides a leak monitoring system for oil and gas pipelines based on distributed optical fiber combined with negative pressure wave transport balance. Compared with existing technologies, it has stronger anti-interference capabilities. Through multi-level data preprocessing algorithms, it removes environmental noise and operating condition interference. Combined with multi-source data fusion and intelligent algorithm combination, it significantly reduces the false alarm rate and the missed alarm rate. It is applicable to various oil and gas pipelines such as crude oil, natural gas, and multiphase flow pipelines. It can cope with different terrain environments such as plains, mountains, and cities, as well as complex operating conditions such as negative pressure zones, frequent pump start-stop, and multiple interferences. It has strong environmental adaptability and operating condition compatibility. Attached Figure Description

[0015] Figure 1 This is a structural framework diagram of the monitoring system of the present invention; Figure 2 This is a schematic diagram of the field deployment topology of the present invention; Figure 3 This is a diagram illustrating the micro-leakage analysis of the decision algorithm in the fusion analysis module of this invention. Figure 4 This is a leakage engineering analysis diagram of the decision algorithm of the fusion analysis module of the present invention, showing normal operation, leakage, and pump shutdown. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1: like Figures 1-4As shown, this embodiment of the invention provides an oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transport balance, including a multi-source sensing module, a data preprocessing module, a fusion analysis module, a positioning calculation module, an alarm response module, a data management module, and a pipeline three-dimensional geographic information module. These modules work collaboratively to achieve comprehensive and high-precision monitoring of oil and gas pipeline leaks. The multi-source sensing module is the core of the system's data acquisition, responsible for acquiring various key signals of the pipeline's operating status, including vibration signals, temperature signals, pressure infrasound signals, and flow signals, providing comprehensive data support for subsequent analysis. The distributed optical fiber sensing unit uses sensing optical fibers laid tightly along the entire oil and gas pipeline. The optical fibers serve as both the sensing medium and the signal transmission medium. Rayleigh scattering technology is used to detect pipeline vibration signals. When a pipeline leaks, the ejection and diffusion of the leaking medium will cause vibration of the pipeline wall. The intensity and phase of the Rayleigh scattered light will change with the vibration. Vibration information can be obtained by demodulating this change. Raman scattering technology is used to detect pipeline temperature signals. Temperature changes affect the intensity ratio of Stokes light to anti-Stokes light. By measuring this ratio, the temperature at various points in the pipeline can be accurately obtained. The negative pressure wave infrasound acquisition unit employs a novel integrated infrasound / pressure sensor. This sensor incorporates a data fitting algorithm, reducing distortion of analog signals during acquisition and transmission, significantly improving anti-interference capabilities. The sensor's acquisition frequency is no lower than 100Hz, with pressure acquisition accuracy better than 0.0001MPa, and infrasound acquisition range covering 2Hz–20Hz. It can quickly capture negative pressure waves and infrasound signals caused by leaks. The sensors are spaced along the pipeline, with the pipeline length between adjacent acquisition points not exceeding 60km, ensuring effective capture of negative pressure wave signals. The flow acquisition unit uses a high-precision ultrasonic flow meter or electromagnetic flow meter, which is installed at the first station, the last station and key distribution stations of the pipeline to collect the instantaneous flow and cumulative flow data of the pipeline medium in real time. The signals collected by the multi-source sensing module are susceptible to environmental noise, equipment interference, and operating condition fluctuations. The data preprocessing module uses a series of algorithms to purify, correct, and standardize the original signals, providing high-quality data for subsequent fusion analysis. The vibration signal denoising submodule uses wavelet transform algorithm to decompose the original vibration signals collected by distributed optical fiber into multiple scales, separating the high-frequency components representing environmental noise and the low-frequency components representing leakage characteristics. High-frequency noise is removed by threshold processing, and the signal is reconstructed to obtain the denoised vibration characteristic signal, effectively suppressing environmental interference such as traffic vibration and equipment operation vibration. The temperature signal correction submodule is used to establish an environmental temperature compensation model. By collecting ambient temperature data around the pipeline, it corrects the pipeline body temperature measured by distributed optical fiber, eliminating temperature measurement deviations caused by external factors and ensuring that abnormal temperature changes only reflect internal faults such as pipeline leaks. The signal standardization submodule uses the Z-score standardization method to convert various types of signals such as vibration, temperature, pressure, and flow rate into standardized data with a mean of 0 and a standard deviation of 1, eliminating the influence of dimensions and laying the foundation for multi-source data fusion.

[0018] Example 2: like Figures 1-4 As shown, this embodiment of the invention provides an oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transport balance. The fusion analysis module is the core decision-making unit of the system. By extracting the characteristic parameters of multi-source signals, data fusion and intelligent algorithms are used to achieve accurate judgment of leakage events. Feature extraction submodule: Performs feature mining on various preprocessed signals to extract feature parameters strongly correlated with the leakage event, including vibration signal features, temperature signal features, pressure signal features, and flow signal features. Vibration signal features are extracted using the Fast Fourier Transform algorithm to extract the main frequency, and the amplitude is extracted through time-domain peak detection. The period is calculated through peak interval statistics or frequency reciprocal. Temperature signal features are obtained by calculating the rate of temperature change per unit time. When leakage causes media ejection, the local temperature will rise or fall sharply. If the rate of temperature change exceeds the set threshold, it is an abnormal feature. Pressure signal features are obtained by extracting parameters such as pressure drop rate, minimum pressure value, and pressure recovery time. The negative pressure wave caused by leakage will cause the pressure to drop rapidly. Flow signal features are obtained by calculating the real-time output difference, i.e., the difference between the input flow of the first station and the output flow of the last station, the change in output difference, and the duration of output difference. During leakage, the output difference will increase significantly and last for more than the set time. The multi-source data fusion submodule treats the vibration and temperature characteristics of distributed optical fibers, along with the pressure and flow characteristics of negative pressure waves and load balance, as different sources of evidence, establishing an evidence confidence function and a likelihood function. Through evidence combination rules, the confidence levels of each evidence source are synthesized to obtain a comprehensive confidence level, achieving complementary verification of multi-dimensional features and reducing the uncertainty of single-feature judgments. The leakage judgment submodule integrates transient modeling, AI identification, graffiti-based intelligent fuzzy analysis, and special signal joint diagnosis methods, dynamically configuring algorithm combination weights based on pipeline operating conditions and the site environment. The comprehensive confidence level after multi-source data fusion is input into the algorithm combination model, outputting a leakage probability. When the leakage probability is greater than 90%, it is judged as a leakage event; less than 30%, it is judged as normal operation; and 30%–90% is judged as a suspected leakage, requiring further tracking and analysis. The positioning and calculation module combines the high-density spatial positioning advantages of distributed optical fiber with the high-precision time-difference positioning principle of negative pressure waves to achieve accurate calculation of the leak point. The initial positioning using distributed optical fiber is based on the principle of optical time-domain reflectometry. The distributed optical fiber sensing unit sends light pulses into the optical fiber, and by measuring the time delay of the backscattered light, the distance between the vibration or temperature anomaly point and the starting end of the optical fiber is calculated, thus initially determining the spatial range of the leak event. Since the optical fiber monitoring density is one monitoring point per meter, the initial positioning error does not exceed 10 meters, providing a clear range reference for subsequent precise correction. Then, through the precise correction step using negative pressure waves, the distance from the leak point to the starting end is calculated using the formula X = 1 / 2 (L + ατ0), based on the time difference τ0 between the upstream and downstream negative pressure wave infrasound acquisition units receiving the leak wave. Here, X is the distance from the leak point to the pressure measurement point at the starting end, L is the total length of the pipeline, and α is the propagation speed of the pressure wave in the pipeline medium. Finally, the initial positioning results from the distributed optical fiber and the precise calculation results from the negative pressure waves are weighted and fused. Combined with terrain correction from the pipeline's three-dimensional geographic information module, the final leak point positioning accuracy is better than ±50 meters, meeting the needs of on-site emergency response. The alarm response module quickly issues graded alarms based on the judgment results of the fusion analysis module and the location information of the location calculation module, and supports emergency linkage to minimize leakage losses. The graded alarm submodule divides the alarm level into three levels based on the leakage probability, leakage scale and environmental risk of the leakage location. A Level 1 alarm is set as an emergency leak, characterized by a leak probability ≥ 95% and an estimated leak volume ≥ 1m³. 3 / h or if the leak is located in a high-consequence area such as a river crossing or a densely populated area, the system will issue the highest level alarm and trigger the emergency response procedure; The level 2 alarm is set as a suspected leak, characterized by a leak probability of 90% ≤ leak probability < 95%, and an estimated leak volume of 0.1 m³. 3 / h~1m 3 / h, the system issues a medium-level alarm, prompting staff to verify and confirm; The Level 3 alarm is set as an abnormal warning, characterized by a leakage probability of 30% ≤ leakage probability < 90%. When the transmission error, vibration, or temperature signal is abnormal but does not meet the leakage judgment criteria, the system issues an early warning and continuously tracks signal changes. While issuing an alarm, the multi-channel notification submodule simultaneously pushes alarm information through various means, including voice broadcasts, audible and visual alarms, and pop-up prompts from the on-site monitoring terminal, SMS messages and APP push notifications from management personnel, and alarm log records from the remote management platform. This ensures that relevant personnel receive alarm information as soon as possible. The emergency linkage submodule links information to the PLC system and valve chamber control system of the pipeline control center. When a level one alarm occurs, it can automatically trigger emergency pump shutdown, closure of upstream and downstream valves at the leak point, or allow staff to manually issue control commands through the remote management platform to quickly cut off the leak source and reduce the leakage.

[0019] The data management module is responsible for storing, querying, statistically analyzing, and sharing monitoring data, alarm information, and system parameters, providing data support for pipeline operation management and maintenance decisions. The module adopts a hybrid C / S+B / S architecture. The C / S architecture is used for on-site monitoring terminals to efficiently process high-density, high-precision data sources, enabling real-time data curve display, differential bar chart statistics, and historical data playback. The B / S architecture is used for the remote centralized management platform to allocate multi-user permissions and enable monitoring data query, alarm record statistics, and system parameter configuration.

[0020] The pipeline 3D geographic information module is based on GIS technology, integrating topographic data, satellite imagery data, pipeline attribute data, and surrounding environmental data along the pipeline route to construct a 3D visualization model of the pipeline. When a leak alarm occurs, the system automatically overlays the leak location results onto the 3D map, intuitively displaying the geographical location, surrounding environment, and terrain features of the leak point.

[0021] The following points should be noted in this article: 1. The accompanying drawings of the embodiments disclosed herein only relate to the structures involved in the embodiments disclosed herein; other structures can be referred to in general design.

[0022] 2. Where there is no conflict, the embodiments of this disclosure and the features in the embodiments can be combined with each other to obtain new embodiments.

[0023] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

Claims

1. A leak monitoring system for oil and gas pipelines based on distributed optical fiber combined with negative pressure wave transport balance, comprising a multi-source sensing module, a data preprocessing module, a fusion analysis module, a location calculation module, an alarm response module, a data management module, and a pipeline three-dimensional geographic information module, characterized in that: The multi-source sensing module is used to collect vibration signals, temperature signals, pressure infrasound signals and flow signals of the pipeline, including a distributed optical fiber sensing unit, a negative pressure wave infrasound acquisition unit and a flow acquisition unit. The data preprocessing module performs noise reduction, filtering and standardization on the acquired multi-source signals, including a vibration signal noise reduction submodule, a temperature signal correction submodule, a pressure and flow signal filtering submodule and a signal standardization submodule. The fusion analysis module extracts feature parameters from multi-source signals and uses data fusion and intelligent algorithms to achieve accurate judgment of leakage events. It includes a feature extraction submodule, a multi-source data fusion submodule, and a leakage judgment submodule. The positioning calculation module combines the high-density spatial positioning advantages of distributed optical fiber with the high-precision time difference positioning principle of negative pressure wave to achieve accurate calculation of the leakage point. The alarm response module quickly issues a tiered alarm based on the judgment result of the fusion analysis module and the positioning information of the positioning calculation module. The data management module is responsible for storing, querying, statistically analyzing, and sharing monitoring data, alarm information, system parameters, etc., providing data support for pipeline operation management and maintenance decisions; The pipeline 3D geographic information module integrates topographic, geomorphological, and surrounding environmental data along the pipeline route, and overlays the leak location results onto the 3D map to achieve a visual display of the leak location.

2. The oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transmission balance according to claim 1, characterized in that: The distributed optical fiber sensing unit of the multi-source sensing module has a sensor optical fiber densely laid every meter along the entire oil and gas pipeline. It uses Rayleigh scattering to detect vibration signals and Raman scattering to detect temperature signals, achieving high-density monitoring at the meter level. The negative pressure wave infrasound acquisition unit is an integrated infrasound pressure sensor. The sensor has a built-in data fitting algorithm to achieve an acquisition frequency of not less than 100Hz and an acquisition accuracy better than 0.0001MPa. The flow acquisition unit uses a high-precision flow meter to collect the instantaneous flow rate and cumulative flow rate data of the pipeline medium in real time.

3. The oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transmission balance according to claim 1, characterized in that: The vibration signal noise reduction submodule of the data preprocessing module uses wavelet transform algorithm to remove environmental noise interference and retain leakage-related characteristic vibration signals. The temperature signal correction submodule uses environmental temperature compensation algorithm to eliminate the influence of external temperature changes on pipeline body temperature monitoring. The pressure and flow signal filtering submodule uses adaptive Kalman filtering algorithm to filter signal fluctuations caused by non-leakage events such as pump and valve start-up and shutdown. The signal standardization submodule converts signals of different types and magnitudes into standardized data of a unified dimension.

4. The oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transmission balance according to claim 1, characterized in that: The feature extraction submodule of the fusion analysis module extracts the dominant frequency, amplitude, and period parameters from the vibration signal, the abnormal temperature change rate parameter from the temperature signal, and the pressure drop rate and transmission difference change parameters from the pressure / flow signal. The multi-source data fusion submodule fuses the vibration / temperature characteristics of the distributed optical fiber with the pressure / flow characteristics of the negative pressure wave-transmission balance. The leakage judgment submodule integrates the transmission difference transient model method, AI identification method, graffiti intelligent fuzzy analysis method, and special signal joint diagnosis method. Based on the fused features, it outputs the leakage probability. When the leakage probability is greater than 90%, it is judged as a leakage event.

5. The oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transmission balance according to claim 1, characterized in that: The positioning method steps of the positioning calculation module are divided into: Step 1: Preliminary location step of distributed optical fiber, based on the time delay of backscattered light of Rayleigh scattering, to determine the approximate spatial range of the leakage event, with a location error of no more than 10 meters; Step 2: Negative pressure wave precise correction step. Based on the time difference τ0 between the upstream and downstream negative pressure wave infrasound acquisition units receiving the leakage wave, the distance from the leak point to the head end is calculated using the formula X=1 / 2 (L+ατ0), where X is the distance from the leak point to the head end pressure measurement point, L is the total length of the pipeline, and a is the propagation speed of the pressure sound wave in the pipeline medium. Step 3: Fusion positioning step, which weights and fuses the preliminary positioning results of distributed optical fiber with the accurate calculation results of negative pressure wave, and the final positioning accuracy is better than ±50 meters.

6. The oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transmission balance according to claim 1, characterized in that: The graded alarm submodule classifies alarm levels into Level 1 emergency leak, Level 2 suspected leak, and Level 3 abnormal warning based on the probability and scale of leakage. The multi-channel notification submodule pushes alarm information synchronously through voice broadcast, SMS reminder, platform pop-up, and sound and light alarms. The emergency linkage submodule can be linked with the PLC system of the pipeline control center to realize emergency pump stop, valve closure, and other operations.

7. The oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transmission balance according to claim 1, characterized in that: The distributed optical fiber sensing unit adopts wavelength division multiplexing technology to simultaneously detect vibration and temperature signals. The signal sampling rate is not less than 1kHz, the vibration monitoring frequency band covers 0.1Hz to 100Hz, the temperature monitoring range is -20℃ to 120℃, and the temperature measurement accuracy is better than ±0.5℃.

8. The oil and gas pipeline leakage monitoring system based on distributed optical fiber combined with negative pressure wave transmission balance according to claim 1, characterized in that: The data management module adopts a C / S+B / S hybrid architecture. The C / S architecture is used for the on-site monitoring terminal to efficiently process high-density, high-precision data sources, and realize real-time data curve display, differential bar chart statistics, and historical data playback functions. The B / S architecture is used for the remote centralized management platform to allocate multi-user permissions and realize monitoring data query, alarm record statistics, and system parameter configuration functions.

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