A distributed optical fiber leakage detection method, device, and system

Abstract

This invention relates to the field of pipeline monitoring technology, and particularly to a distributed optical fiber leakage detection method, device, and system, comprising: S1: establishing a spatial gridded sensing scheme based on pipeline length and diameter parameters, laying sensing optical fibers in a grid pattern along the horizontal and vertical planes, and then covering the pipeline surface; S2: constructing a distributed optical fiber detection system for underground pipeline temperature and vibration to collect environmental signals; S3: analyzing the collected environmental signal data and establishing an environmental signal pattern analysis model under normal operating conditions; S4: acquiring abnormal points of optical fiber signals in real time through the distributed optical fiber detection system and calculating the possible location of pipeline leakage; S5: analyzing the pipeline temperature and vibration indicators at the possible leakage points to determine whether leakage has occurred. This invention solves the problem of sensors being unable to detect long-distance pipelines, comparing abnormal values ​​with normal values ​​to determine abrupt changes in temperature and vibration, thereby accurately locating pipeline leakage points.

Description

Technical Field

[0001] This invention relates to the field of pipeline monitoring technology, and in particular to a distributed optical fiber leakage detection method, device, and system. Background Technology

[0002] Underground pipe networks are a crucial component of urban infrastructure, responsible for transporting water, gas, and electricity, and playing a vital role in urban economic development. However, with the increasing age of these networks and the aging of their materials, leakage problems are becoming increasingly prominent, posing significant challenges to related enterprises and society. Pipeline leakage not only leads to substantial economic losses for the companies managing the network but also wastes valuable resources and poses uncontrollable safety risks, such as causing road cavities, ground subsidence, and gas explosions. These issues seriously threaten urban safety, residents' daily lives, and traffic safety. Therefore, underground pipe network leakage detection is of paramount importance.

[0003] Currently, conventional pipeline monitoring and protection methods mainly fall into two categories: external monitoring and protection, such as pipeline inspection, early warning instrument detection and monitoring, and online monitoring systems for pipe corridors; and internal safety protection systems, such as pipeline flow and pressure monitoring. For example, CN112629701A discloses a pipeline leakage monitoring system and leak location method based on distributed optical fiber temperature measurement technology. The optical fiber is wound around the surface of the pipeline in a two-dimensional grid and connected to the temperature measurement host. The two-dimensional grid of optical fiber monitors changes in the pipeline surface temperature, and the leak location is determined by the area formed by the grid edges where the temperature field is abnormal. However, simply setting up a two-dimensional grid temperature measurement scheme on the pipeline cannot accurately determine the leak point. Furthermore, while this method uses a zoned, back-and-forth arrangement to increase signal strength, it ignores the measurement uncertainty caused by the large number of measurement points, leading to errors in the results. Therefore, how to achieve health monitoring of urban underground pipe networks, promptly detect anomalies, and accurately locate and alarm them is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0004] To address the problems mentioned above, this invention provides a distributed optical fiber leakage detection method, apparatus, and system, which can solve problems such as leakage detection of underground pipelines and application limitations caused by inaccurate single detection data.

[0005] To achieve the above objectives, the technical solution provided by the present invention is as follows:

[0006] A distributed optical fiber leakage detection method includes the following steps:

[0007] S1: Based on the parameters of pipe length and diameter, establish a spatial gridded sensing scheme, lay the sensing optical fibers in a grid pattern in the horizontal and vertical planes, and then cover the pipe surface.

[0008] S2: Based on the fiber optic grid layout scheme, a distributed fiber optic detection system for underground pipeline temperature and vibration is built to collect environmental signal data.

[0009] S3: Establish an environmental signal pattern analysis model under normal operating conditions;

[0010] S4: The distributed optical fiber leakage detection system acquires environmental signal data in real time and calculates the possible location of pipeline leakage based on signal anomalies.

[0011] S5: Analyze the temperature and vibration signal data of the pipeline at potential leakage points, compare the data at abnormal signal points, and determine whether leakage has occurred.

[0012] Preferably, the specific process of establishing the environmental signal law analysis model under normal operating conditions in step S3 includes:

[0013] S31: A grid-like sensing fiber optic cover on the detection pipeline;

[0014] S32: Based on actual engineering cases, obtain the characteristic values ​​of temperature and vibration data of pipelines under historical leakage conditions and under normal operating conditions.

[0015] S33: By comparing the characteristic values ​​of data under normal operating conditions with the characteristic values ​​of comparative data under leakage conditions, data noise is eliminated, and an environmental signal pattern analysis model is established.

[0016] Specifically, the steps in step S4 for calculating the possible locations of pipeline leaks include:

[0017] S41: Based on the temperature and vibration signal data under normal operating conditions, calculate the difference in the characteristic values ​​of the data under normal operating conditions and store it in the historical operating condition database;

[0018] S42: Real-time acquisition of fiber optic detection signals, comparison of the data difference at the fiber optic detection points with the difference in the historical operating condition database. If the comparison meets the standard of normal operating conditions, the sensor output result is normal. If the comparison does not meet the standard of normal operating conditions, the abnormal value of the output signal is calculated, and the fiber optic detection signal corresponding to the abnormal value is determined.

[0019] S43: Based on the abnormal fiber optic detection signal, determine the abrupt change points of temperature and vibration signals, and then calculate the actual location of the underground pipeline in the corresponding grid area through grid points.

[0020] Furthermore, the specific process of step S5 includes:

[0021] S51: Collect and eliminate data noise from abnormal fiber optic detection signal data of pipe temperature and vibration that may cause leakage.

[0022] S52: Based on the database of historical operating conditions, determine the leakage medium and accident model in the pipeline, model and simulate pipeline leakage accidents, and establish a leakage accident model dataset.

[0023] S53: Collect and process the model dataset of pipeline leakage accidents, and calculate the temperature-time and vibration frequency-time data of the pipeline and surrounding space after the pipeline leakage accident through finite element simulation, and determine the maximum value of the temperature and vibration changes around the pipeline.

[0024] S54: Principal component analysis is used to analyze environmental signals and remove environmental noise data from the maximum values;

[0025] S55: Compare the environmental characteristic information with the environmental signal pattern analysis model under normal operating conditions to determine whether leakage has occurred.

[0026] The hardware component of the distributed optical fiber leakage detection system includes a distributed optical fiber leakage detection device, which comprises a distributed optical fiber temperature measurement host, a computer, several data amplifiers, a data analysis device, and a dynamic testing device. The distributed optical fiber temperature measurement host is connected to the dynamic testing device, and the dynamic testing device is connected to the data amplifiers. The distributed optical fiber temperature and vibration detection device is used to collect temperature and vibration data on the optical fibers in the distributed optical fiber temperature measurement host.

[0027] Furthermore, the distributed optical fiber temperature measurement host is connected to a dynamic testing device, which includes a test bracket and test wiring. The test bracket is fixedly installed on the outer wall of the pipe to be tested, and the test wiring is installed on the test bracket. Several S-shaped loops are wrapped around the distributed optical fiber temperature and vibration monitoring device. Adjacent S-shaped loops are connected by a fixing device. The sensing optical fiber in the distributed optical fiber leakage detection device is routed along the entire length of the pipe. The sensing optical fiber routing is as follows: the length and diameter parameters of the pipe are obtained, and the sensing optical fiber is laid on the outermost layer of the pipe according to the grid plane, covering the entire pipe wall surface. The grid is laid with a square grid of 0.2m*0.2m interval.

[0028] A distributed optical fiber leakage detection system includes a historical operating condition database, sensing optical fibers, a signal preprocessor, a sensor signal database, and a calculation module. The signal preprocessor preprocesses the collected environmental signals, temperature, and vibration signals. The calculation module analyzes the preprocessed signals against accident data in the historical operating condition database to derive accident results. The system's workflow is as follows: Environmental signals, temperature, and vibration signals collected by the distributed optical fiber detection system are preprocessed by the signal preprocessor and then compared with signals in the sensor signal database within the calculation module to determine accident characteristics and output results. The specific workflow of the system is as follows:

[0029] S101: Collect fiber temperature and vibration data through a distributed fiber optic leakage detection system and preprocess them;

[0030] S102: Identify the status of the pipeline environment signal. If abnormal, proceed to S103; if normal, return to S101 to continue running the system.

[0031] S103: By comparing data in the historical operating condition database and the sensor signal database, determine the spatial range and location of the accident's impact;

[0032] S104: Based on the results of S103, identify the pipes in the abnormal area and determine whether leakage has occurred.

[0033] Furthermore, the specific process of identifying the pipeline environment status in step S102 includes:

[0034] S1021: Calculate the temperature change at various locations on the optical fiber, process signal characteristics, analyze the vibration spectrum, and analyze the environmental signal to obtain the feature vector dataset of optical fiber temperature and vibration signal in the region, and perform calculations on it.

[0035] S1022: Obtain the ambient temperature T' and vibration frequency V' in the pipeline environment; obtain the actual temperature T and vibration frequency V data of the accident data; calculate the difference in the environment, compare it with the temperature and vibration difference under historical working conditions, and determine the abnormal signal A = (A1, A2, ..., An).

[0036] Furthermore, the process of obtaining the feature vector dataset in S1021 includes establishing a multidimensional feature vector set: storing the dataset obtained during the fiber optic temperature measurement and detection process into the sensor signal database, processing it in conjunction with the system data obtained by the fiber optic leakage detection system, performing matrix representation, and obtaining a multidimensional feature vector set.

[0037] Furthermore, in S1022, the location of the abnormal signal A is determined; the region (A1, A2, ..., Am) where the abnormal signal A is located in the multidimensional feature vector set is determined, and the abnormal point Amin' = minA' is calculated, where A' represents the multidimensional feature vector set, and Amin' is the signal feature vector with the smallest value in the abnormal region A. Then, the signal feature vector minA' is the location of the leakage point.

[0038] The beneficial effects of this invention are as follows:

[0039] 1. In the detection and location of leaks in underground pipelines, the changes in the operating temperature and vibration frequency of the pipeline are monitored to solve the problem that sensors are difficult to detect in long-distance pipelines. By using dynamic testing equipment, the problems of temperature and vibration signal intensity are solved, thereby improving detection accuracy and safety.

[0040] 2. By collecting temperature and vibration frequency signals from the pipeline surface when there is no leakage, the signals when there is no leakage are identified as normal values; the temperature and vibration frequency signals when there is a leak are identified as abnormal values; the abnormal values ​​are compared with the normal values ​​to determine the abrupt changes in temperature and vibration, thereby accurately locating the leakage point in the pipeline network.

[0041] 3. A distributed fiber optic detection system is used for real-time monitoring. Combined with fiber optic equipment and dynamic testing equipment, it can identify hazardous sources and provide real-time early warning of temperature and vibration data in the pipeline. Furthermore, the dynamic testing equipment can analyze and provide early warning of the location, hazard level, and historical data of hazardous sources along the pipeline network, thereby realizing dynamic testing. Attached Figure Description

[0042] Figure 1 This is a one-dimensional planar unfolded view of the sensor fiber mesh layout in an embodiment of the present invention;

[0043] Figure 2 This is a primary template diagram of the detection signal in an embodiment of the present invention;

[0044] Figure 3 This is the final template diagram of the detection signal in the embodiment of the present invention;

[0045] Figure 4 This is a signal diagram of the linear fiber optic laying detection in an embodiment of the present invention;

[0046] Figure 5 This is a signal diagram of fiber optic U-shaped laying detection in an embodiment of the present invention;

[0047] Figure 6 This is a signal diagram of fiber optic mesh laying detection in an embodiment of the present invention. Detailed Implementation

[0048] The technical solutions of this invention will now be clearly and completely described with reference to the accompanying drawings. The components of the invention described and shown in the drawings herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of this invention.

[0049] It should be explained that the environmental signals in this patent include physical parameter data such as pressure, humidity, concentration of harmful gases, and light intensity collected by other sensors or monitoring equipment through manual inspection or automatic detection, which are used to collect information about the environment around the pipeline and are used to indicate the different environments in which different sections of the pipeline are located.

[0050] To address the limitations of underground pipeline leakage detection and the inaccuracy of single detection data, this invention provides a distributed optical fiber leakage detection method, apparatus, and system. The apparatus includes a distributed optical fiber temperature measurement host, a computer, several data amplifiers, a data analysis device, and a dynamic testing device. The distributed optical fiber temperature measurement host is connected to the dynamic testing device; the dynamic testing device is connected to the data amplifiers; and the distributed optical fiber temperature and vibration detection device is used to collect temperature and vibration data from the optical fibers in the distributed optical fiber temperature measurement host.

[0051] The distributed fiber optic temperature measurement host is connected to a dynamic testing device, which includes a test bracket and test wiring. The test bracket is fixedly installed on the outer wall of the pipe to be tested, and the test wiring is installed on the test bracket and secured to the distributed fiber optic temperature and vibration monitoring device using several S-shaped loops. Each adjacent buried S-shaped loop is connected by a fixing device. The distributed fiber optic temperature and vibration monitoring device is wired along the entire length of the pipe via sensing optical fibers. Please refer to [link to relevant documentation]. Figure 1 A one-dimensional planar unfolded diagram of the sensor fiber optic network layout, where X in the diagram... i Y represents the horizontal coordinate of the sensing fiber optic mesh laid out in a one-dimensional plane. i L represents the vertical coordinate of the sensing fiber optic mesh after it has been tiled into a one-dimensional plane. i The grid consists of equally spaced squares. Figure 1 L2 to L7 in the diagram represent the arrangement sequence of the sensing fibers, i.e., the sensing fibers are arranged sequentially along L... 2至The L7 routing is as follows: the length and diameter parameters of the pipe are obtained, and the sensing fiber is laid on the outermost layer of the pipe according to the grid plane, covering the entire pipe wall surface. The grid is laid with a square grid of 0.2m*0.2m intervals, so that the coordinate position of each fiber detection point on the pipe can be determined, which is used to determine the leakage detection point.

[0052] Please see Figure 2 The primary template diagram of the detection signal and Figure 3 The final template diagram of the detection signal is shown in this embodiment. A distributed optical fiber sensing system is used to simulate a small-scale optical fiber mesh measurement experiment for monitoring leaks in a tap water pipeline. In the small-scale pipeline leak simulation experiment, the length of the optical fiber used is 180m. The tap water pipeline is a DN300 steel pipe, the water temperature inside the pipeline is controlled at 18°C, and the ambient temperature is controlled at 23°C. The leak in the pipeline is manually controlled by a valve, which is set 3.2 meters directly above the test pipeline.

[0053] Before the pipeline leak detection experiment begins, 50 sets of non-leaking signals are collected and sequentially divided into initial signals (10 sets), intermediate signals (10 sets), and late signals (30 sets). Please refer to [link to relevant documentation]. Figure 2 First, after preprocessing the initial signal, the primary template is determined by comparing its correlation coefficient with that of the intermediate signal; please refer to [link to relevant documentation]. Figure 3 Then, the difference coefficients between the 30 sets of later signals and the primary template signals are calculated respectively. After removing the larger difference values, the remaining signals are accumulated, averaged, and normalized to determine the final template signal.

[0054] The system includes a historical operating condition database, sensing optical fibers, a signal preprocessor, a sensor signal database, and a calculation module. The signal preprocessor is used to preprocess the collected environmental signals, temperature, and vibration signals. The calculation module is used to perform calculation and analysis on the preprocessed signals and accident data in the historical operating condition database to obtain accident results. The system's workflow is as follows: Environmental signals, temperature, and vibration signals collected by the distributed optical fiber detection system are preprocessed by the signal preprocessor and then compared with signals in the sensor signal database within the calculation module to determine accident characteristics and output results.

[0055] The aforementioned distributed fiber optic sensing system can monitor changes in the operating temperature and vibration frequency of underground pipelines for leak detection and location, solving the problem that sensors have difficulty detecting long-distance pipelines. By using dynamic testing equipment, it solves the problems of temperature and vibration signal intensity, and by using monitoring devices for protection, it improves detection accuracy and safety.

[0056] By collecting temperature and vibration frequency signals from the pipeline surface when there is no leakage, the signals when there is no leakage are identified as normal values; the temperature and vibration frequency signals when there is a leakage are identified as abnormal values; the abnormal values ​​are compared with the normal values ​​to determine the abrupt change points of temperature and vibration, thereby accurately locating the leakage points in the pipeline network.

[0057] The method for detecting fiber optic leakage using the above-mentioned device and system includes the following steps:

[0058] S1: Based on the parameters of pipe length and diameter, establish a spatial gridded sensing scheme, lay the sensing optical fibers in a grid pattern in the horizontal and vertical planes, and then cover the pipe surface.

[0059] S2: Based on the fiber optic grid layout scheme, a distributed fiber optic detection system for underground pipeline temperature and vibration is built to collect environmental signal data.

[0060] S3: Establish an environmental signal pattern analysis model under normal operating conditions;

[0061] S31: A grid-like sensing fiber optic cover on the detection pipeline;

[0062] S32: Based on actual engineering cases, obtain the characteristic values ​​of temperature and vibration data of pipelines under historical leakage conditions and under normal operating conditions.

[0063] S33: By comparing the characteristic values ​​of data under normal operating conditions with the characteristic values ​​of comparative data under leakage conditions, data noise is eliminated, and an environmental signal pattern analysis model is established.

[0064] S4: Environmental signal data is acquired in real time through a distributed optical fiber leakage detection system, and the potential location of pipeline leakage is calculated based on signal anomalies; the specific steps in step S4 for calculating the potential location of pipeline leakage include:

[0065] S41: Based on the temperature and vibration signal data under normal operating conditions, calculate the difference in the characteristic values ​​of the data under normal operating conditions and store it in the historical operating condition database;

[0066] S42: Real-time acquisition of fiber optic detection signals, comparison of the data difference at the fiber optic detection points with the difference in the historical operating condition database. If the comparison meets the standard of normal operating conditions, the sensor output result is normal. If the comparison does not meet the standard of normal operating conditions, the abnormal value of the output signal is calculated, and the fiber optic detection signal corresponding to the abnormal value is determined.

[0067] S43: Based on the abnormal fiber optic detection signal, determine the abrupt change points of temperature and vibration signals, and then calculate the actual location of the underground pipeline in the corresponding grid area through grid points.

[0068] S5: Analyze the temperature and vibration signal data of the pipeline at potential leakage points, compare the data at abnormal signal points, and determine whether leakage has occurred.

[0069] The specific process is as follows:

[0070] S51: Collect and eliminate data noise from abnormal fiber optic detection signal data of pipe temperature and vibration that may cause leakage.

[0071] S52: Based on the database of historical operating conditions, determine the leakage medium and accident model in the pipeline, model and simulate pipeline leakage accidents, and establish a leakage accident model dataset.

[0072] S53: Collect and process the model dataset of pipeline leakage accidents, and calculate the temperature-time and vibration frequency-time data of the pipeline and surrounding space after the pipeline leakage accident through finite element simulation, and determine the maximum value of the temperature and vibration changes around the pipeline.

[0073] S54: Principal component analysis is used to analyze environmental signals and remove environmental noise data from the maximum values;

[0074] S55: Compare the environmental characteristic information with the environmental signal pattern analysis model under normal operating conditions to determine whether leakage has occurred.

[0075] The specific workflow of the distributed optical fiber leakage detection system is as follows:

[0076] S101: Collect fiber temperature and vibration data through a distributed fiber optic leakage detection system and preprocess them;

[0077] S102: Identify the status of the pipeline environment signal. If abnormal, proceed to S103; if normal, return to S101 to continue running the system.

[0078] The specific process for identifying the pipeline environment status in step S102 includes:

[0079] S1021: Calculate the temperature change at various locations on the optical fiber, process signal characteristics, analyze the vibration spectrum, and analyze the environmental signal to obtain the feature vector dataset of optical fiber temperature and vibration signal in the region, and perform calculations on it.

[0080] S1022: Obtain the ambient temperature T' and vibration frequency V' in the pipeline environment; obtain the actual temperature T and vibration frequency V data of the accident data; calculate the difference in the environment, compare it with the temperature and vibration difference under historical working conditions, and determine the abnormal signal A = (A1, A2, ..., An).

[0081] In step S1022, the location of the abnormal signal A is determined; the region (A1, A2, ..., Am) where the abnormal signal A is located in the multidimensional feature vector set is determined, and the abnormal point Amin' = minA' is calculated, where A' represents the multidimensional feature vector set, and Amin' is the signal feature vector with the smallest value in the abnormal region A. Then, the signal feature vector minA' is the location of the leakage point.

[0082] S103: Determine the spatial range and location of the accident's impact by comparing the data with the database and real-time processed data;

[0083] S104: Based on the results of S103, identify the pipes in the abnormal area and determine whether leakage has occurred.

[0084] Please see Figure 4 The experiment used distributed optical fiber to acquire temperature signals when the pipeline was leak-free. Fifty sets of leak-free detection signals were collected per minute. Thirty sets of leak detection signals for each laying method were compared with the final threshold template to determine the leak location effectiveness of the pipeline under the three optical fiber laying methods.

[0085] The sensing optical fibers are laid on the walls of the water pipes in straight, U-shaped and grid-like patterns. The distributed optical fiber sensing system collects the signals when there is no leakage on the pipe surface. The reference threshold signal is determined based on the no-leak signal. The threshold signal and the leakage signal are compared to determine the temperature and vibration change points.

[0086] Please refer to details. Figure 4 When the sensing fiber is laid in a straight line, the distributed fiber sensing signal changes significantly at 14.4m, and the temperature drops from 22 degrees to 20 degrees, indicating that the leak point is located at 4.4m of the pipe. The actual leak point is at 3.2m, and the positioning error is 1.2m.

[0087] Please see Figure 5 The optical fiber U-shaped laying detection signal diagram shows that when the sensing optical fiber adopts the U-shaped plane measurement method, the leak detection signal obtained is not just one abnormal point. The sensing optical fiber obtains signals at 13.6m and 23.8m respectively. The distributed optical fiber leakage detection system calculates the corresponding coordinates of the pipeline position as [3.8, 0.8] and [3.6, 0.4], with a positioning error within 0.6m.

[0088] Please see Figure 6 The image shows the detection signal of a fiber optic mesh layout. When the sensing fiber uses a mesh-type planar measurement method, it is laid on the pipe wall, with an overall fiber layout of 1m × 5m rectangle, and the fiber coverage area is approximately 47100 cm². 2Approximately 100 grids were formed on the pipe surface, and four signal anomaly points were identified, corresponding to the sensor fiber positions of 12.9m, 23.3m, 48.2m, and 48.4m, respectively. Using a distributed fiber optic leakage detection system, the coordinates of these anomaly points were determined to be [3.1, 0.8], [3.1, 0.4], and [3.2, 0.8], respectively.

[0089] [3.2,0.6] According to the calculation results, the leakage area is located within a rectangle of 3.1m to 3.2m, and the positioning error is less than 0.2m from the actual leakage point of 3.2m.

[0090] Through the above comparison, the present invention collects temperature and vibration frequency signals from the pipeline surface when there is no leakage, determines the normal value signals of the signals when there is no leakage, and transforms the temperature and vibration frequency signals during leakage into abnormal signal values. By comparing the abnormal values ​​with the normal values, the abrupt change points of temperature and vibration can be determined, making the location of pipeline leakage points more accurate. Combined with fiber optic equipment and dynamic testing equipment, it can identify hazard sources and realize real-time early warning of temperature and vibration data in the pipeline. Furthermore, based on the dynamic testing equipment, it can analyze and provide early warning of the location, hazard level, and historical data of hazard sources along the pipeline, thereby realizing dynamic testing.

[0091] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the claims are intended to be included within the present invention. Furthermore, it should be understood that although this specification describes embodiments, this manner of description is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in the various embodiments can be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A distributed optical fiber leakage detection method, characterized in that, Includes the following steps: S1: Based on the parameters of pipe length and diameter, establish a spatial gridded sensing scheme, lay the sensing optical fibers in a grid pattern in the horizontal and vertical planes, and then cover the pipe surface. S2: Based on the fiber optic mesh laying scheme, a distributed fiber optic detection system for underground pipeline temperature and vibration is built to collect environmental signal data. S3: Establish an environmental signal pattern analysis model under normal operating conditions; S4: The distributed optical fiber leakage detection system acquires environmental signal data in real time and calculates the possible location of pipeline leakage based on signal anomalies. S5: Analyze the pipe temperature and vibration signal data at potential leakage points, compare the data at abnormal signal points, and determine whether leakage has occurred; The specific steps for calculating the possible locations of pipeline leakage in step S4 include: S41: Based on the temperature and vibration signal data under normal operating conditions, calculate the difference in the characteristic values ​​of the data under normal operating conditions and store it in the historical operating condition database; S42: Real-time acquisition of fiber optic detection signals, comparison of the data difference at the fiber optic detection points with the difference in the historical operating condition database. If the comparison meets the standard of normal operating conditions, the sensor output result is normal. If the comparison does not meet the standard of normal operating conditions, the abnormal value of the output signal is calculated, and the fiber optic detection signal corresponding to the abnormal value is determined. S43: Based on the abnormal fiber optic detection signal, determine the abrupt change points of temperature and vibration signals, and then calculate the actual location of the underground pipeline in the corresponding grid area through grid points; The specific process of step S5 includes: S51: Collect data on abnormal points in the temperature and vibration signals of pipelines that may leak, and eliminate data noise; S52: Based on the database of historical operating conditions, determine the leakage medium and accident model in the pipeline, model and simulate pipeline leakage accidents, and establish a leakage accident model dataset. S53: Collect and process the model dataset of pipeline leakage accidents, and calculate the temperature-time and vibration frequency-time data of the pipeline and surrounding space after the pipeline leakage accident through finite element simulation, and determine the maximum value of the temperature and vibration changes around the pipeline. S54: Principal component analysis is used to analyze environmental signals, removing environmental noise data from the maximum values ​​of temperature and vibration changes; S55: Compare the environmental characteristic information with the environmental signal pattern analysis model under normal operating conditions to determine whether leakage has occurred.

2. The distributed optical fiber leakage detection method according to claim 1, characterized in that, The specific process of establishing the environmental signal law analysis model under normal operating conditions in step S3 includes: S31: Cover the detection pipeline with a grid of sensing optical fibers; S32: Based on actual engineering cases, obtain the characteristic values ​​of temperature and vibration data of pipelines under historical leakage conditions and under normal operating conditions. S33: By comparing the characteristic values ​​of data under normal operating conditions with the characteristic values ​​of comparative data under leakage conditions, data noise is eliminated, and an environmental signal pattern analysis model is established.

3. An apparatus for using any one of the distributed optical fiber leakage detection methods according to claims 1-2, characterized in that, The hardware component of the distributed optical fiber leakage detection system includes a distributed optical fiber leakage detection device, which comprises a distributed optical fiber temperature measurement host, a computer, several data amplifiers, a data analysis device, and a dynamic testing device. The distributed optical fiber temperature measurement host is connected to the dynamic testing device, and the dynamic testing device is connected to the data amplifiers. The distributed optical fiber temperature and vibration detection device is used to collect temperature and vibration data on the optical fibers in the distributed optical fiber temperature measurement host.

4. The apparatus according to claim 3, characterized in that, The distributed optical fiber temperature measurement host is connected to the dynamic testing equipment, which includes a test bracket and test wiring. The test bracket is fixedly installed on the outer wall of the pipe to be tested, and the test wiring is installed on the test bracket. Several S-shaped loops are wrapped around the distributed optical fiber temperature and vibration monitoring device. Each adjacent S-shaped loop is connected by a fixing device. The sensing optical fiber in the distributed optical fiber leakage detection device is routed along the entire length of the pipe. The sensing optical fiber routing is as follows: the length and diameter parameters of the pipe are obtained, and the sensing optical fiber is laid on the outermost layer of the pipe according to the grid plane, covering the entire pipe wall surface. The grid is laid with a square grid of 0.2m*0.2m interval.

5. A system utilizing the distributed optical fiber leakage detection method according to any one of claims 1-2, characterized in that, The system includes a historical operating condition database, optical fiber sensors, a signal preprocessor, a sensor signal database, and a calculation module. The signal preprocessor is used to preprocess the collected environmental signals, temperature, and vibration signals. The calculation module is used to analyze the preprocessed signals against accident data in the historical operating condition database to obtain accident results. The system's workflow is as follows: Environmental signals, temperature, and vibration signals collected by the distributed optical fiber detection system are preprocessed by the signal preprocessor and then compared with sensor signals in the historical operating condition database within the calculation module to determine accident characteristics and output results. The specific workflow of the system is as follows: S101: Collect fiber temperature and vibration data through a distributed fiber optic leakage detection system and preprocess them; S102: Identify the status of the pipeline environment signal. If abnormal, proceed to S103; if normal, return to S101 to continue running the system. S103: By comparing data in the historical operating condition database and the sensor signal database, determine the spatial range and location of the accident's impact; S104: Based on the results of S103, identify the pipes in the abnormal area and determine whether leakage has occurred.

6. The system according to claim 5, characterized in that, The specific process for identifying the pipeline environment status in step S102 includes: S1021: Calculate the temperature change at various locations on the optical fiber, process signal characteristics, analyze the vibration spectrum, and analyze the environmental signal to obtain the feature vector dataset of optical fiber temperature and vibration signal in the region, and perform calculations on it. S1022: Obtain the ambient temperature T' and vibration frequency V' in the pipeline environment; obtain the actual temperature T and vibration frequency V data of the accident data; calculate the difference in the environment, compare it with the temperature and vibration difference under historical working conditions, and determine the abnormal signal A = (A1, A2, ..., An).

7. The system according to claim 6, characterized in that, The process of obtaining the feature vector dataset in S1021 includes establishing a multidimensional feature vector set: storing the dataset obtained during the fiber optic temperature measurement and detection process into the sensor signal database, processing it in conjunction with the system data obtained by the fiber optic leakage detection system, performing matrix representation, and obtaining a multidimensional feature vector set.

8. The system according to claim 7, characterized in that, In step S1022, the location of the abnormal signal A is determined; the region (A1, A2, ..., Am) where the abnormal signal A is located in the multidimensional feature vector set is determined, and the abnormal point Amin' = minA' is calculated, where A' represents the multidimensional feature vector set, and Amin' is the signal feature vector with the smallest value in the abnormal region A. Then, the signal feature vector minA' is the location of the leakage point.

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