Cable Channel Fault Location Method and System for Distributed Optical Fiber Sensing

Abstract

The present application discloses a method and system for cable channel fault location of distributed optical fiber sensing, which relates to the field of cable fault measurement. The method includes: analyzing the adaptability evaluation values of ambient temperature, ambient humidity, magnetic field strength, and ambient light intensity with the detection optical pulse parameters according to the detection adaptability function; when the adaptability evaluation value is less than or equal to the adaptability threshold, optimizing the detection optical pulse parameters according to the detection adaptability function based on the ambient temperature, ambient humidity, magnetic field strength, and ambient light intensity, obtaining the recommended detection optical pulse parameters to control the detection optical transmitter to emit detection light to the optical fiber sensor, receiving the feedback information of the optical fiber sensor for signal classification processing, obtaining the generated position of the fault signal, adding it to the cable channel fault location result and sending it to the cable management terminal. It solves the technical problem that the traditional cable channel relies on manual inspection and simple test equipment, and realizes the technical effect of real-time monitoring and accurate location of cable channel faults.

Description

Technical Field

[0001] This application relates to the field of cable fault measurement, and particularly to a method and system for cable channel fault location based on distributed optical fiber sensing. Background Art

[0002] In key industries such as power and communication, cable channels play an important role in transmitting power and information. However, cable channels are vulnerable to various factors such as environmental factors, construction quality, and material aging, resulting in frequent failures. Traditional cable channel fault location methods mainly rely on manual inspections and simple testing equipment, but these methods have defects such as low location accuracy, time-consuming and laborious, and inability to monitor in real time. Summary of the Invention

[0003] This application provides a method and system for cable channel fault location based on distributed optical fiber sensing, solves the technical problem that traditional cable channels rely on manual inspections and simple testing equipment, and realizes the technical effect of real-time monitoring and accurate location of cable channel faults.

[0004] This application provides a method for cable channel fault location based on distributed optical fiber sensing. The method is applied to a cable channel fault location system based on distributed optical fiber sensing. The system is embedded in the service layer, and the service layer is communicatively connected to a detection optical transmitter, an optical fiber sensor, and an environmental sensor. The optical fiber sensors are arranged along the cable laying path at a preset interval distance, and the method includes: communicating with the environmental sensor to obtain the environmental temperature, environmental humidity, magnetic field strength, and environmental light intensity; obtaining the detection optical pulse parameters of the detection optical transmitter; constructing a detection fitness function; analyzing the fitness evaluation values of the environmental temperature, environmental humidity, magnetic field strength, and environmental light intensity and the detection optical pulse parameters according to the detection fitness function; when the fitness evaluation value is less than or equal to the fitness threshold, optimizing the detection optical pulse parameters according to the detection fitness function based on the environmental temperature, environmental humidity, magnetic field strength, and environmental light intensity to obtain recommended detection optical pulse parameters; controlling the detection optical transmitter to emit detection light to the optical fiber sensor according to the recommended detection optical pulse parameters, and receiving the feedback information of the optical fiber sensor; performing signal classification processing on the feedback information of the optical fiber sensor to obtain the generated position of the fault signal, and adding it to the cable channel fault location result and sending it to the cable management terminal.

[0005] In a possible implementation, a detection fitness function is constructed and the following processing is performed: Using the environmental temperature, the environmental humidity, the magnetic field strength, and the environmental light intensity as environmental constraints, and using the detection light pulse parameters as detection light constraints, a fiber optic sensing detection record is collected, where the fiber optic sensing detection record includes the pulse record parameters received by the fiber optic sensor for the detection light pulse, the cable fault record positioning result, and the actual cable fault positioning result, and the actual cable fault positioning result is obtained by measurement using a dedicated instrument; According to the pulse record parameters received by the fiber optic sensor for the detection light pulse, the cable fault record positioning result, and the actual cable fault positioning result, a detection fitness function is constructed:

[0006] ,

[0007] where, respectively represent the environmental temperature, the environmental humidity, the magnetic field strength, the environmental light intensity, the pulse width of the pulse record parameters received by the fiber optic sensor for the detection light pulse, the pulse frequency of the pulse record parameters received by the fiber optic sensor for the detection light pulse, the optical power of the pulse record parameters received by the fiber optic sensor for the detection light pulse, and the cable fault record positioning result, represents the pulse width of the detection light pulse parameters, represents the pulse frequency of the detection light pulse parameters, represents the actual cable fault positioning result, represents the optical power of the detection light pulse parameters, 、 、 and respectively represent the pulse width weight, the pulse frequency weight, the optical power weight, and the fault location weight.

[0008] In a possible implementation, according to the detection fitness function, analyze the fitness evaluation value of the ambient temperature, the ambient humidity, the magnetic field strength, and the ambient light intensity, and the detection light pulse parameters, and perform the following processing: Constrained by the detection light emitter model and the fiber optic sensor model, collect ambient temperature record data, ambient humidity record data, magnetic field strength record data, ambient light intensity record data, and detection light pulse record parameters; According to the detection fitness function, analyze the initial fitness evaluation data of the ambient temperature record data, the ambient humidity record data, the magnetic field strength record data, and the ambient light intensity record data, and the detection light pulse record parameters; Apply an allowable fault tolerance perturbation to the initial fitness evaluation data to obtain fitness identification data; Construct decision constraint conditions based on the detection fitness function; Using the fitness identification data as supervision, and using the ambient temperature record data, the ambient humidity record data, the magnetic field strength record data, the ambient light intensity record data, and the detection light pulse record parameters as inputs, train the fitness evaluation unit based on the decision constraint conditions; According to the fitness evaluation unit, analyze the fitness evaluation value of the ambient temperature, the ambient humidity, the magnetic field strength, and the ambient light intensity, and the detection light pulse parameters.

[0009] In a possible implementation, when the fitness evaluation value is less than or equal to the fitness threshold, based on the ambient temperature, the ambient humidity, the magnetic field strength, and the ambient light intensity, optimize the detection light pulse parameters according to the detection fitness function to obtain the recommended detection light pulse parameters, and perform the following processing: Obtain the layout distance information between the fiber optic sensor and the detection light emitter; Based on the layout distance information, configure the pulse width constraint interval, the pulse frequency constraint interval, and the optical power constraint interval, and construct the pulse parameter optimization space; Obtain the pulse parameter historical configuration database, where the pulse parameter historical configuration database includes a set of four-element arrays of detection light pulse parameters, and any four-element array of detection light pulse parameters includes pulse width, pulse frequency, optical power, and fitness; According to the pulse width, the pulse frequency, and the optical power, screen the initial set of four-element arrays of detection light pulse parameters that meet the pulse parameter optimization space from the set of four-element arrays of detection light pulse parameters; According to the fitness, optimize the detection light pulse parameters based on the initial set of four-element arrays of detection light pulse parameters to obtain the recommended detection light pulse parameters.

[0010] In a possible implementation manner, according to the adaptation degree, the detection optical pulse parameters are optimized based on the set of initial detection optical pulse parameter quadruples to obtain the recommended detection optical pulse parameters, and the following processing is performed: when the set of initial detection optical pulse parameter quadruples has a quadruple greater than the adaptation degree threshold, it is output as the recommended detection optical pulse parameters; when the set of initial detection optical pulse parameter quadruples does not have a quadruple greater than the adaptation degree threshold, the set of initial detection optical pulse parameter quadruples is distributed in the pulse parameter optimization space based on the pulse width, the pulse frequency, and the optical power to obtain a set of initial distribution positions; an aggregation analysis is performed on the set of initial distribution positions according to a distribution distance threshold to obtain multiple clusters of distribution positions; the maximum adaptation degree is extracted by traversing the multiple clusters of distribution positions to obtain multiple initial position sorting results; based on the multiple initial position sorting results, iterative expansion is performed in combination with the detection adaptation degree function to obtain a distribution position expansion result, where the distribution position expansion result has an expanded position adaptation degree evaluation value; when the expanded position adaptation degree evaluation value is greater than the adaptation degree threshold, the detection optical pulse parameters corresponding to the distribution position expansion result are set as the recommended detection optical pulse parameters.

[0011] In a possible implementation manner, based on the multiple initial position sorting results, iterative expansion is performed in combination with the detection adaptation degree function to obtain a distribution position expansion result, and the following processing is performed: the multiple initial position sorting results are sorted according to the adaptation degree from large to small to obtain an initial position sorting result; the first number of head serial number initial positions are selected, and the first number of head serial number initial positions are connected to obtain a head serial number distribution network; the second number of tail serial number initial positions are selected, and the second number of tail serial number initial positions are connected to obtain a tail serial number distribution network; taking any position on the line of the head serial number distribution network as the target and any position on the line of the tail serial number distribution network as the starting point, a search is performed according to a preset search step for a preset number of times to obtain the distribution position expansion result.

[0012] In a possible implementation, taking any position on a line of the head sequence distribution network as a target and any position on a line of the tail sequence distribution network as a starting point, search a preset number of times according to a preset search step size to obtain the distribution position expansion result, and perform the following processing: taking any position on a line of the head sequence distribution network as a target and any position on a line of the tail sequence distribution network as a starting point, search according to a preset search step size to obtain a primary search direction and a primary search position; analyze the primary search position fitness of the primary search position according to the detection fitness function; when the primary search position fitness is less than the search starting point fitness, retreat to the search starting point, update the primary search direction and search again; when the primary search position fitness is greater than or equal to the search starting point fitness, perform iterative search based on the primary search direction and the primary search position.

[0013] The present application also provides a cable channel fault location system for distributed optical fiber sensing, including: a communication module for communicating with an environmental sensor to obtain environmental temperature, environmental humidity, magnetic field intensity, and environmental light intensity; a detection module for obtaining detection optical pulse parameters of a detection optical transmitter; a construction module for constructing a detection fitness function; an evaluation module for analyzing the fitness evaluation values of the environmental temperature, the environmental humidity, the magnetic field intensity, and the environmental light intensity, and the detection optical pulse parameters according to the detection fitness function; an optimization module for, when the fitness evaluation value is less than or equal to a fitness threshold, optimizing the detection optical pulse parameters according to the detection fitness function based on the environmental temperature, the environmental humidity, the magnetic field intensity, and the environmental light intensity to obtain recommended detection optical pulse parameters; a control module for controlling the detection optical transmitter to emit detection light to an optical fiber sensor according to the recommended detection optical pulse parameters and receiving feedback information from the optical fiber sensor; a classification module for performing signal classification processing on the feedback information of the optical fiber sensor to obtain a fault signal generation position, adding it to the cable channel fault location result, and sending it to a cable management terminal.

[0014] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0015] The cable channel fault location method and system for distributed optical fiber sensing provided by the present application relate to the technical field of cable fault measurement, solve the technical problem that traditional cable channels rely on manual inspection and simple testing equipment, and achieve the technical effect of real-time monitoring and accurate location of cable channel faults. Description of the Drawings

[0016] To more clearly illustrate the technical solutions of the embodiments of the present application, the accompanying drawings of the embodiments of the present application will be briefly introduced below. Flowcharts are used in the present application to illustrate the operations performed by the systems according to the embodiments of the present application. It should be understood that the operations described above or below do not necessarily need to be executed precisely in sequence. On the contrary, according to the need, various steps can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several steps can be removed from these processes.

[0017] Figure 1 It is a schematic flowchart of the cable channel fault location method for distributed optical fiber sensing provided by the embodiments of the present application;

[0018] Figure 2 It is a schematic structural diagram of the cable channel fault location system for distributed optical fiber sensing provided by the embodiments of the present application. Detailed implementation manners

[0019] The above description is only an overview of the technical solutions of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically illustrates the detailed implementation manners of the present application.

[0020] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limitations of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0021] In the following description, "some embodiments" are involved, which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "first" and "second" involved are only used to distinguish similar objects and do not represent a specific order for the objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules not clearly listed or inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application.

[0022] The embodiment of the present application provides a method for fault location of cable channels based on distributed optical fiber sensing. The method is applied to a fault location system for cable channels based on distributed optical fiber sensing. The system is embedded in the service layer, and the service layer is communicatively connected to a detection optical transmitter, an optical fiber sensor, and an environmental sensor. The optical fiber sensors are arranged along the cable laying path at a preset interval distance, as Figure 1 shown. The method includes:

[0023] Step A100: Communicate with the environmental sensor to obtain the environmental temperature, environmental humidity, magnetic field intensity, and environmental light intensity;

[0024] When the system starts, it performs initialization communication with the environmental sensor module, including hardware connection detection and communication protocol verification. At the same time, according to the type of the environmental sensor, it loads corresponding communication protocols such as UART, SPI, I2C, MODBUS, etc. to ensure that the sensor can communicate normally, and sets the sampling frequency of the sensor according to the system requirements. For example, when the environmental parameters change violently, the sampling frequency can be increased; when the change is slow, the frequency can be appropriately reduced to save resources. Further, a data request instruction is sent to the environmental sensor, and at the same time, the data frame returned by the sensor is received, the frame header, data content, and check code are parsed, and the valid data is extracted. The valid data can include environmental temperature, environmental humidity, magnetic field intensity, and environmental light intensity. The environmental temperature is the temperature value parsed from the data returned by the environmental sensor, the environmental humidity is the relative humidity value extracted from the data frame, the magnetic field intensity is the read three-axis magnetic field data, and the environmental light intensity is the intensity of the light radiated by the light source in the environment. Finally, the collected environmental data is stored in the local cache and arranged in chronological order to provide reliable environmental information support for subsequent detection adaptability analysis and optical pulse parameter optimization.

[0025] Execute step A200 to obtain the detection optical pulse parameters of the detection optical transmitter;

[0026] During the system startup phase, initializing communication with the detection light emitter may include communication interface detection and protocol verification, etc. Then, according to the communication interface of the detection light emitter, load the corresponding communication protocol. At the same time, send instructions to the detection light emitter to obtain its current detection light pulse parameters, which means constructing a data request frame. The data request frame includes a frame header, which identifies the device type and request type, a command code, which indicates the parameter to be queried, and a check code to ensure data integrity. Send the request frame to the detection light emitter and wait for the emitter to feedback a response data frame. Receive the data frame returned by the detection light emitter, which may include pulse frequency, pulse width, optical power, and optical wavelength. Finally, according to the system requirements, regularly send query instructions to the detection light emitter to obtain the latest detection light pulse parameters, and at the same time set the update frequency (for example, once per second or adjust the frequency according to environmental changes) to ensure the real-time nature of the parameters, so as to efficiently and accurately obtain the detection light pulse parameters of the detection light emitter, providing necessary technical support for subsequent adaptability calculation and detection light optimization.

[0027] Execute step A300 to construct a detection adaptability function; in a possible implementation, step A300 further includes step A310. Taking the environmental temperature, the environmental humidity, the magnetic field strength, and the environmental light intensity as environmental constraints, and taking the detection light pulse parameters as detection light constraints, collect fiber optic sensing detection records. Among them, the fiber optic sensing detection records include the pulse width of the detection light pulse record parameters received by the fiber optic sensor, the cable fault record positioning result, and the actual cable fault positioning result, and the actual cable fault positioning result is obtained by measuring with a dedicated instrument; execute step A320, and construct a detection adaptability function according to the pulse width of the detection light pulse record parameters received by the fiber optic sensor, the cable fault record positioning result, and the actual cable fault positioning result:

[0028] ,

[0029] Wherein, respectively represent the environmental temperature, the environmental humidity, the magnetic field strength, the environmental light intensity, the pulse width of the detection light pulse record parameters received by the fiber optic sensor, the pulse frequency of the detection light pulse record parameters received by the fiber optic sensor, the optical power of the detection light pulse record parameters received by the fiber optic sensor, and the cable fault record positioning result, represents the pulse width of the detection light pulse parameters, represents the pulse frequency of the detection light pulse parameters, represents the actual cable fault positioning result, represents the optical power of the detection light pulse parameters, 、 、 and Respectively characterize the pulse width weight, pulse frequency weight, optical power weight, and fault location weight.

[0030] First, continuously collect the ambient temperature, ambient humidity, magnetic field strength, and ambient light intensity through an environmental sensor. At the same time, based on the time stamp of the environmental data recorded by the environmental sensor, synchronize it with the detection optical pulse record and the fault location record. Take the critical values of the ambient temperature, ambient humidity, magnetic field strength, and ambient light intensity as environmental constraints. Further, obtain real-time detection optical pulse parameters from the detection optical transmitter, which can include pulse frequency, pulse width, optical power, optical wavelength, etc., record the change trend of the detection optical pulse parameters, and mark the synchronization time point with the environmental constraints. Judge whether the detection optical parameters are within the recommended range of the device, and set it as the detection optical constraint. Then collect the fiber optic sensing detection record, which means controlling the detection optical transmitter to emit detection light to the fiber optic sensor according to the constraint conditions and record the feedback parameters of the fiber optic sensor receiving the detection optical pulse. The feedback parameters include the reflection intensity, that is, the reflection signal intensity of the detection light in the fiber, the optical loss, that is, the attenuation value of the optical signal during propagation, the signal delay, that is, the return time of the detection optical pulse, etc., and extract the location data of the cable fault, which can include the fault record location result, that is, the fault location obtained by analyzing the fiber optic feedback signal, and the actual location result. By using a professional cable fault location instrument, that is, a cable fault locator for measurement. The cable fault locator further determines the exact location of the cable fault point after determining the approximate location of the cable fault point by the main unit of the cable fault tester, and analyzes it in combination with the cable laying data, fault type, and on-site situation, so as to accurately determine the location of the fault point, which can be the actual fault location obtained through on-site verification or other location means, and compare the record location result with the actual location result and mark the location deviation.

[0031] Further, according to the detection optical pulse record parameters received by the fiber optic sensor, the cable fault record location result, and the cable fault actual location result, construct a detection fitness function:

[0032] ,

[0033] Among them, Respectively characterize the ambient temperature, ambient humidity, magnetic field strength, ambient light intensity, the pulse width of the detection optical pulse record parameters received by the fiber optic sensor, the pulse frequency of the detection optical pulse record parameters received by the fiber optic sensor, the optical power of the detection optical pulse record parameters received by the fiber optic sensor, and the cable fault record location result. Characterize the pulse width of the detection optical pulse parameters. Characterize the pulse frequency of the detection optical pulse parameters. Characterize the cable fault actual location result. Characterize the optical power of the detection optical pulse parameters. , , and respectively represent the pulse width weight, pulse frequency weight, optical power weight, and fault location weight.

[0034] The above detection fitness function is used to evaluate the matching degree between the detection light parameters and the environmental constraints, as well as the effectiveness of the detection light pulse for fault location. By using historical detection data as training samples, including multiple groups of environmental parameters, detection light parameters, and location results, and using regression analysis or machine learning algorithms (such as linear regression, support vector machine) to determine the weight coefficients , , and optimal values, and finally verify the effect of the fitness function through simulation or experiment to ensure that it can accurately evaluate the matching of detection conditions. By substituting the real-time collected environmental parameters, detection light parameters, and location data into the detection fitness function, calculate the current fitness value, optimize the detection light pulse parameters according to the fitness value, and improve the location accuracy. The detection fitness function can comprehensively consider environmental conditions, detection light parameters, and location results, provide a comprehensive evaluation of detection conditions, and provide high-precision support for cable fault location.

[0035] Execute step A400, and analyze the fitness evaluation value of the environmental temperature, environmental humidity, magnetic field strength, and environmental light intensity, and the detection light pulse parameters according to the detection fitness function; in a possible implementation manner, step A400 further includes step A410, which takes the detection light emitter model and the fiber optic sensor model as constraints, and collects environmental temperature record data, environmental humidity record data, magnetic field strength record data, environmental light intensity record data, and detection light pulse record parameters; execute step A420, and analyze the initial fitness evaluation data of the environmental temperature record data, environmental humidity record data, magnetic field strength record data, environmental light intensity record data, and the detection light pulse record parameters according to the detection fitness function; execute step A430, apply an allowable tolerance perturbation to the initial fitness evaluation data to obtain fitness identification data; execute step A440, construct a decision constraint condition based on the detection fitness function; execute step A450, use the fitness identification data as supervision, and use the environmental temperature record data, environmental humidity record data, magnetic field strength record data, environmental light intensity record data, and the detection light pulse record parameters as inputs, and train the fitness evaluation unit based on the decision constraint condition; execute step A460, and analyze the fitness evaluation value of the environmental temperature, environmental humidity, magnetic field strength, and environmental light intensity, and the detection light pulse parameters according to the fitness evaluation unit.

[0036] According to the parameter constraints of the detection light emitter model and the fiber optic sensor model, determine the acquisition frequencies and ranges of environmental data and detection light pulse data. Obtain recorded data such as environmental temperature, environmental humidity, magnetic field strength, and environmental light intensity through environmental sensors, and record the detection light pulse parameters in real time through the detection light emitter, including pulse frequency, pulse width, power, and wavelength. Substitute the collected environmental recorded data and detection light pulse parameters into the detection fitness function to calculate the initial fitness evaluation value. The fitness function comprehensively considers the influence of environmental parameters on the performance of the detection light and the matching degree between the detection light pulse parameters and the fiber optic feedback signal to generate the initial evaluation data.

[0037] Apply an allowable fault tolerance perturbation to the initial fitness evaluation data, that is, control the dynamics of the fitness through the fault tolerance range to avoid over-sensitivity or under-sensitivity of the evaluation results. The range of the perturbation is determined by the precision requirements set by the system and the characteristics of environmental fluctuations, which means adding random noise or adjustment factors within a reasonable range to the initial data to generate fitness identification data. Based on the detection fitness function, establish decision constraint conditions, define the objective function and constraints of the evaluation unit, such as maximizing the fitness value, minimizing the interference of environmental parameters on the detection light pulse, and constraining the detection efficiency under specific environments. The decision constraint conditions provide an optimization goal for subsequent model training.

[0038] Furthermore, use the fitness identification data as the supervision signal, and take the environmental temperature recorded data, environmental humidity recorded data, magnetic field strength recorded data, environmental light intensity recorded data, and detection light pulse recorded parameters as inputs, and use the supervised learning method to train the fitness evaluation unit. The training process optimizes the model parameters so that the evaluation unit can accurately predict the fitness value under the given input conditions. The algorithms used can include linear regression, support vector machine, or neural network, etc.

[0039] Finally, apply the trained fitness evaluation unit to real-time data analysis. The construction and training of the fitness evaluation unit can achieve a comprehensive evaluation of the detection conditions, improve the dynamic adaptation ability and detection accuracy of the system, and then calculate the fitness evaluation values of the environmental temperature, humidity, magnetic field strength, and light intensity and the detection light parameters according to the real-time collected environmental parameters and detection light pulse parameters. The fitness evaluation unit can combine historical data and real-time data to provide accurate fitness values to assist in the optimization of detection light parameters and fault location.

[0040] Execute step A500. When the adaptation degree evaluation value is less than or equal to the adaptation degree threshold, based on the environmental temperature, the environmental humidity, the magnetic field intensity, and the environmental light intensity, optimize the detection optical pulse parameters according to the detection adaptation degree function to obtain the recommended detection optical pulse parameters. In a possible implementation, step A500 further includes step A510 of obtaining the layout distance information between the fiber optic sensor and the detection optical transmitter; execute step A520, based on the layout distance information, configure the pulse width constraint interval, the pulse frequency constraint interval, and the optical power constraint interval to construct a pulse parameter optimization space; execute step A530 to obtain a pulse parameter historical configuration database, where the pulse parameter historical configuration database includes a set of detection optical pulse parameter quadruples, and any detection optical pulse parameter quadruple includes pulse width, pulse frequency, optical power, and adaptation degree; execute step A540, according to the pulse width, the pulse frequency, and the optical power, screen out the initial detection optical pulse parameter quadruple set that meets the pulse parameter optimization space from the set of detection optical pulse parameter quadruples.

[0041] When the adaptation degree evaluation value is less than or equal to the adaptation degree threshold, based on the environmental temperature, the environmental humidity, the magnetic field intensity, and the environmental light intensity, optimizing the detection optical pulse parameters according to the detection adaptation degree function means first using the layout plan or the built-in ranging function of the sensor to obtain the actual layout distance between the fiber optic sensor and the detection optical transmitter, ensuring that the distance data is accurate to the meter level or higher precision, and marking the measurement time. By comparing the measured layout distance with the preset distance range, eliminating the obviously abnormal data, recording the valid distance data, and binding it with the sensor number and the transmitter number, so as to obtain the layout distance information between the fiber optic sensor and the detection optical transmitter.

[0042] Further, according to the layout distance information, respectively configure the pulse width constraint interval, the pulse frequency constraint interval, and the optical power constraint interval to construct a pulse parameter optimization space. For short-distance layout (hundreds of meters to one kilometer), the pulse width can be set to 10 nanoseconds to 50 nanoseconds, the repetition frequency to 1000 times per second to 5000 times per second, and the optical power to -10 dBm to 0 dBm. For medium-distance layout (one kilometer to several kilometers), the pulse width can be set to 50 nanoseconds to 200 nanoseconds, the repetition frequency to 500 times per second to 1000 times per second, and the optical power to 0 dBm to 5 dBm. For long-distance layout (several kilometers to more than ten kilometers), the pulse width can be set to 100 nanoseconds to 1 microsecond, the repetition frequency to 100 times per second to 500 times per second, and the optical power to 5 dBm to 10 dBm.

[0043] Further, obtain a historical configuration database of pulse parameters according to the historical data structure, wherein the historical configuration database of pulse parameters includes a set of four-element arrays of probe light pulse parameters. The set of four-element arrays of the probe light pulse parameters may include pulse width, pulse frequency, optical power, and fitness. Any four-element array of the probe light pulse parameters includes pulse width, pulse frequency, optical power, and fitness. At the same time, according to the pulse width, the pulse frequency, and the optical power, screen an initial set of four-element arrays of probe light pulse parameters that meet the pulse parameter optimization space from the set of four-element arrays of probe light pulse parameters, which means screening a set of parameters that meet the optimization space constraints from the historical configuration data, setting an expected fitness threshold, sorting the screened set of parameters according to the expected fitness threshold, and at the same time marking the parameters with high fitness as priority candidates to improve the adaptability and accuracy of fiber optic sensing detection.

[0044] Execute step A550, and optimize the probe light pulse parameters based on the initial set of four-element arrays of probe light pulse parameters according to the fitness to obtain the recommended probe light pulse parameters.

[0045] In a possible implementation manner, step A550 further includes step A551. When the set of four-element arrays of the initial probe light pulse parameters has a four-element array greater than the fitness threshold, output it as the recommended probe light pulse parameters; execute step A552. When the set of four-element arrays of the initial probe light pulse parameters does not have a four-element array greater than the fitness threshold, distribute the set of four-element arrays of the initial probe light pulse parameters in the pulse parameter optimization space based on the pulse width, the pulse frequency, and the optical power to obtain an initial set of distribution positions; execute step A553, perform aggregation analysis on the initial set of distribution positions according to the distribution distance threshold to obtain multiple clusters of distribution positions; execute step A554, traverse the multiple clusters of distribution positions to extract the maximum fitness value to obtain multiple initial position sorting results.

[0046] Traverse the set of initial detection optical pulse parameter quadruples, and check whether the fitness is greater than the expected fitness threshold. When the set of initial detection optical pulse parameter quadruples has a quadruple greater than the fitness threshold, directly output the corresponding detection optical pulse parameters as the recommended detection optical pulse parameters. If the set of initial detection optical pulse parameter quadruples does not have a quadruple greater than the fitness threshold, map each quadruple to the pulse parameter optimization space according to the pulse width, pulse frequency, and optical power to form a set of initial distribution positions, and check whether the distribution positions are located in the valid region of the optimization space, eliminating invalid points. At the same time, calculate the Euclidean distance between each position based on the distribution positions, and set a distribution distance threshold according to the historical data distribution distance, and perform clustering analysis on the set of initial distribution positions, which means classifying data points less than the distribution distance threshold into one category, so as to complete the clustering of the set of initial distribution positions, divide the set of initial distribution positions into multiple clusters, and record the central position and the number of distribution points of each cluster, that is, the multi-cluster distribution positions. Finally, traverse the multi-cluster distribution positions to extract the maximum fitness value, and obtain multiple initial position sorting results, which means traversing the distribution positions of each cluster, extracting the corresponding position with the maximum fitness value, and summarizing the set of positions with the maximum fitness in all clusters as the initial position sorting results, so as to improve the detection effect and system robustness of the fiber optic sensor.

[0047] Execute step A555, and based on the multiple initial position sorting results, perform iterative expansion in combination with the detection fitness function to obtain a distribution position expansion result, where the distribution position expansion result has an expanded position fitness evaluation value; in a possible implementation manner, step A555 further includes step A5551, sorting the multiple initial position sorting results according to the fitness from large to small to obtain an initial position sorting result; execute step A5552, screen the initial positions of the first number of head serial numbers, connect the initial positions of the first number of head serial numbers to obtain a head serial number distribution network; execute step A5553, screen the initial positions of the second number of tail serial numbers, connect the initial positions of the second number of tail serial numbers to obtain a tail serial number distribution network;

[0048] First, traverse all the initial position sorting results, sort them in descending order according to the fitness, and then number the sorted initial positions according to the serial numbers to form the initial position sorting result. Filter out the first number of positions according to the preset number of heads, that is, the initial positions of the first number of head serial numbers. At the same time, connect the lines between the filtered head serial number positions to construct a head distribution network. The connection method can include a fully connected network, that is, establish a connection between any two points, or a minimum spanning tree based on the position distance. The head serial number distribution network is a set of points and lines. Further, similarly, filter out the second number of positions according to the preset number of tails, that is, the initial positions of the second number of tail serial numbers, and connect the lines between the filtered tail serial number positions to construct a tail distribution network. The connection method is the same as that of the head serial number distribution network, which will not be elaborated here too much, and the tail serial number distribution network is a set of points and lines. Under the guidance of the head and tail serial number distribution networks, the optimization of the detection optical pulse parameters is realized through extended search, and the recommended parameters with high fitness are generated to improve the accuracy and robustness of fiber optic sensing detection.

[0049] Execute step A5554, taking any position on the line of the head serial number distribution network as the target and any position on the line of the tail serial number distribution network as the starting point, and search a preset number of times according to the preset search step size to obtain the distribution position expansion result.

[0050] In a possible implementation manner, step A5554 further includes step A55541, taking any position on the line of the head serial number distribution network as the target and any position on the line of the tail serial number distribution network as the starting point, and search according to the preset search step size to obtain a primary search direction and a primary search position; execute step A55542, analyze the primary search position fitness of the primary search position according to the detection fitness function; execute step A55543, when the primary search position fitness is less than the search starting point fitness, return to the search starting point and update the primary search direction to search again; execute step A55544, when the primary search position fitness is greater than or equal to the search starting point fitness, perform iterative search based on the primary search direction and the primary search position.

[0051] Taking any position on a line of the head serial number distribution network as the target and starting from any position on a line of the tail serial number distribution network, and searching according to a preset search step size means selecting the search target and the starting point. The selected target position is a randomly selected target point from any line of the head serial number distribution network, and the selected starting point position is a randomly selected starting point from any line of the tail serial number distribution network. The preset search step size can be a fixed step size, and its initial direction can be set by calculating the initial direction vector from the starting point to the target. Further, according to the step size and direction, calculate a search position once, and synchronize the once search position to the above-constructed detection fitness function to calculate the fitness of the once search position, and compare the fitness of the once search position with the fitness of the search starting point. When the fitness of the once search position is less than the fitness of the search starting point, retreat to the search starting point, and adjust the direction vector according to the new direction offset (random perturbation can be introduced) to update the once search direction and search again. When the fitness of the once search position is greater than or equal to the fitness of the search starting point, take the once search position as the new starting point, iterate the search along the current direction, and update the starting point. At the same time, judge whether the current search position is close to the target position. If the condition is met, terminate the search and record the final position. If the maximum search step number is reached, terminate the search, record the position and fitness of each search, extract the position with the highest fitness in the search path, and output the recommended pulse parameters of the highest fitness point in the search path to ensure the detection accuracy and reliability of the fiber optic sensing system.

[0052] Execute step A556. When the evaluation value of the extended position fitness is greater than the fitness threshold, set the detection optical pulse parameters corresponding to the distribution position extension result as the detection optical recommended pulse parameters.

[0053] Evaluate the extended position fitness, check whether the fitness of the extended position is greater than the fitness threshold. When the evaluation value of the extended position fitness is greater than the fitness threshold, record the extended position and its pulse parameters. If the evaluation value of the fitness of the extended position meets the condition, use the corresponding pulse parameters as the detection optical recommended pulse parameters. The detection optical recommended pulse parameters can include pulse width, pulse frequency, optical power, recommended fitness. Through distribution aggregation and extension analysis, generate the detection optical recommended pulse parameters that meet the conditions, so as to improve the detection effect and system robustness of the fiber optic sensor.

[0054] Next, execute step A600. Control the detection optical transmitter to emit detection light to the fiber optic sensor according to the detection optical recommended pulse parameters, and receive the feedback information of the fiber optic sensor;

[0055] Generate the recommended pulse parameters of the detection light through the adaptability evaluation unit or optimization algorithm, and then confirm that the recommended parameters comply with the physical limitations of the detection light emitter and the fiber optic sensor, that is, determine that the pulse width is within the minimum and maximum widths supported by the emitter, the pulse frequency meets the propagation time constraint of the fiber optic signal, and the optical power does not exceed the power output capacity of the device. The recommended parameters can be written into the control module of the detection light emitter through the communication interface.

[0056] Further, start the detection light emitter, check whether the device operation status is normal (such as the hardware status, self-check result), and control the detection light emitter to generate detection light pulses according to the recommended parameters, which can include width control, that is, adjust the pulse modulation module of the laser to make the emitted pulse conform to the pulse width, frequency control, that is, set the emission frequency to generate periodic pulses, and power control, that is, adjust the laser power through the drive module to ensure that the emission power reaches the optical power.

[0057] Further, the fiber optic sensor captures the returned detection light signal, including the direct light and the reflected light, and can process the optical signal such as amplification, filtering, and demodulation, and then extract the feedback information from the processed signal, which can include the reflection intensity, delay time, signal change rate, etc. Finally, the feedback signal is transmitted to the upper service layer or analysis system through the communication module (such as RS485 or Ethernet), realizing the efficient and accurate control of the detection light emission and feedback, and providing guarantee for the high sensitivity and reliability of the fiber optic sensing system.

[0058] Finally, execute step A700 to perform signal classification processing on the feedback information of the fiber optic sensor, obtain the position where the fault signal is generated, add it to the cable channel fault location result, and send it to the cable management terminal.

[0059] Based on the data such as reflection intensity, signal delay, frequency offset, and noise level contained in the fiber optic sensing feedback information, perform feature analysis to obtain the characteristics of the feedback signal. Classify the fiber optic sensor feedback information into normal signals, that is, the signal intensity and delay time are both within the preset range, and fault signals, that is, the signal intensity is significantly reduced or the delay time is abnormal. It can be rule-based classification, by setting the threshold range of the delay time and signal intensity for signal classification. If the fiber optic sensor feedback information exceeds the set threshold range, it is marked as a fault signal. It can also be machine learning-based classification, by using classification models such as support vector machine (SVM), random forest, or deep learning models to classify according to the characteristics of the feedback signal to determine normal signals or fault signals. Further, calculate the fault location based on the delay time of the fault signal and correct the calculation result, which can include using the average value of multiple measurements to improve the positioning accuracy, or comparing historical records to exclude sudden error points. Finally, format the generated position of the fault signal and related information into the cable channel fault location result, which can include timestamp, fault location, fault type, signal characteristics, etc. Store the fault location result in the local database for subsequent analysis and traceability.

[0060] Furthermore, use a communication protocol suitable for the cable management terminal to transmit the generated position of the fault signal. According to the requirements of the terminal interface, package and send the fault location result to the management terminal. At the same time, the management terminal visually displays the fault location (such as two-dimensional or three-dimensional graphical representation), shows the fault type and related signal characteristics, and generates a maintenance plan and instructions according to the positioning result to notify relevant personnel to repair. Collect the terminal feedback information, combine it with the subsequent signal analysis results, optimize the classification algorithm and positioning accuracy, and provide comprehensive technical support for cable fault detection and maintenance.

[0061] The embodiment of the present application solves the technical problem of the traditional cable channel relying on manual inspection and simple testing equipment, and realizes the technical effect of real-time monitoring and precise positioning of cable channel faults.

[0062] In the above text, reference is made to Figure 1 Describe in detail the cable channel fault location method based on distributed fiber optic sensing according to the embodiment of the present application. Next, reference will be made to Figure 2 Describe the cable channel fault location system based on distributed fiber optic sensing according to the embodiment of the present application.

[0063] A cable channel fault location system for distributed optical fiber sensing according to an embodiment of the present application is used to solve the technical problems of traditional cable channels relying on manual inspections and simple testing equipment, and achieve the technical effects of real-time monitoring and precise location of cable channel faults. The cable channel fault location system for distributed optical fiber sensing includes: a communication module 10, a detection module 20, a construction module 30, an evaluation module 40, an optimization module 50, a control module 60, and a classification module 70.

[0064] The communication module 10 is used to communicate with environmental sensors to obtain environmental temperature, environmental humidity, magnetic field strength, and environmental light intensity.

[0065] The detection module 20 is used to obtain the detection light pulse parameters of the detection light emitter.

[0066] The construction module 30 is used to construct a detection fitness function.

[0067] The evaluation module 40 is used to analyze the fitness evaluation values of the environmental temperature, the environmental humidity, the magnetic field strength, and the environmental light intensity, and the detection light pulse parameters according to the detection fitness function.

[0068] The optimization module 50 is used to optimize the detection light pulse parameters according to the detection fitness function based on the environmental temperature, the environmental humidity, the magnetic field strength, and the environmental light intensity when the fitness evaluation value is less than or equal to the fitness threshold, and obtain the recommended detection light pulse parameters.

[0069] The control module 60 is used to control the detection light emitter to emit detection light to the optical fiber sensor according to the recommended detection light pulse parameters and receive the feedback information of the optical fiber sensor.

[0070] The classification module 70 is used to perform signal classification processing on the feedback information of the optical fiber sensor, obtain the generated position of the fault signal, and add it to the cable channel fault location result and send it to the cable management terminal.

[0071] Next, the specific configuration of the construction module 30 will be described in detail. As described above, to construct the detection fitness function, the construction module 30 may further include: taking the environmental temperature, the environmental humidity, the magnetic field strength, and the environmental light intensity as environmental constraints, and the detection light pulse parameters as detection light constraints, collecting optical fiber sensing detection records, where the optical fiber sensing detection records include the detection light pulse record parameters received by the optical fiber sensor, the cable fault record location results, and the actual cable fault location results, and the actual cable fault location results are obtained by measuring with a dedicated instrument; constructing a detection fitness function according to the detection light pulse record parameters received by the optical fiber sensor, the cable fault record location results, and the actual cable fault location results:

[0072] ,

[0073] Among them, respectively represent the environmental temperature, environmental humidity, magnetic field strength, environmental light intensity, pulse width of the detection optical pulse recording parameter received by the fiber optic sensor, pulse frequency of the detection optical pulse recording parameter received by the fiber optic sensor, optical power of the detection optical pulse recording parameter received by the fiber optic sensor, and cable fault recording and positioning result, The pulse width characterizing the detection optical pulse parameter, The pulse frequency characterizing the detection optical pulse parameter, Represents the actual cable fault positioning result, The optical power characterizing the detection optical pulse parameter, 、 、 and respectively represent the pulse width weight, pulse frequency weight, optical power weight, and fault location weight.

[0074] Next, the specific configuration of the evaluation module 40 will be described in detail. As described above, according to the detection adaptability function, the adaptability evaluation values of the environmental temperature, the environmental humidity, the magnetic field strength, and the environmental light intensity, and the detection optical pulse parameters are analyzed. The evaluation module 40 may further include: Constrained by the detection optical transmitter model and the fiber optic sensor model, collect environmental temperature record data, environmental humidity record data, magnetic field strength record data, environmental light intensity record data, and detection optical pulse record parameters; According to the detection adaptability function, analyze the initial adaptability evaluation data of the environmental temperature record data, the environmental humidity record data, the magnetic field strength record data, the environmental light intensity record data, and the detection optical pulse record parameters; Apply an allowable fault tolerance perturbation to the initial adaptability evaluation data to obtain adaptability identification data; Construct decision constraint conditions based on the detection adaptability function; Using the adaptability identification data as supervision, using the environmental temperature record data, the environmental humidity record data, the magnetic field strength record data, the environmental light intensity record data, and the detection optical pulse record parameters as inputs, train the adaptability evaluation unit based on the decision constraint conditions; According to the adaptability evaluation unit, analyze the adaptability evaluation values of the environmental temperature, the environmental humidity, the magnetic field strength, and the environmental light intensity, and the detection optical pulse parameters.

[0075] Next, the specific configuration of the optimization module 50 will be described in detail. As described above, when the adaptation degree evaluation value is less than or equal to the adaptation degree threshold, based on the ambient temperature, the ambient humidity, the magnetic field strength, and the ambient light intensity, the detection light pulse parameters are optimized according to the detection adaptation function to obtain the recommended detection light pulse parameters. The optimization module 50 may further include: obtaining the layout distance information between the fiber optic sensor and the detection light emitter; based on the layout distance information, configuring the pulse width constraint interval, the pulse frequency constraint interval, and the optical power constraint interval to construct the pulse parameter optimization space; obtaining the pulse parameter historical configuration database, where the pulse parameter historical configuration database includes a set of four-element arrays of detection light pulse parameters, and any four-element array of detection light pulse parameters includes pulse width, pulse frequency, optical power, and adaptation degree; according to the pulse width, the pulse frequency, and the optical power, screening the initial set of four-element arrays of detection light pulse parameters that meet the pulse parameter optimization space from the set of four-element arrays of detection light pulse parameters; according to the adaptation degree, optimizing the detection light pulse parameters based on the initial set of four-element arrays of detection light pulse parameters to obtain the recommended detection light pulse parameters.

[0076] Next, the specific configuration of the optimization module 50 will be described in detail. As described above, according to the adaptation degree, the detection light pulse parameters are optimized based on the initial set of four-element arrays of detection light pulse parameters to obtain the recommended detection light pulse parameters. The optimization module 50 may further include: when the set of four-element arrays of initial detection light pulse parameters has a four-element array greater than the adaptation degree threshold, outputting it as the recommended detection light pulse parameters; when the set of four-element arrays of initial detection light pulse parameters does not have a four-element array greater than the adaptation degree threshold, distributing the set of four-element arrays of initial detection light pulse parameters based on the pulse width, the pulse frequency, and the optical power in the pulse parameter optimization space to obtain the initial distribution position set; performing aggregation analysis on the initial distribution position set according to the distribution distance threshold to obtain multiple clusters of distribution positions; traversing the multiple clusters of distribution positions to extract the maximum adaptation degree to obtain multiple initial position sorting results; based on the multiple initial position sorting results, combining the detection adaptation function for iterative expansion to obtain the distribution position expansion result, where the distribution position expansion result has an expanded position adaptation degree evaluation value; when the expanded position adaptation degree evaluation value is greater than the adaptation degree threshold, setting the detection light pulse parameters corresponding to the distribution position expansion result as the recommended detection light pulse parameters.

[0077] Next, the specific configuration of the optimization module 50 will be described in detail. As described above, based on the sorting results of the multiple initial positions and in combination with the detection fitness function, iterative expansion is performed to obtain the distribution position expansion result. The optimization module 50 may further include: sorting the sorting results of the multiple initial positions according to the fitness from large to small to obtain the initial position sorting result; screening the initial positions of the first number of head serial numbers, connecting the initial positions of the first number of head serial numbers to obtain the head serial number distribution network; screening the initial positions of the second number of tail serial numbers, connecting the initial positions of the second number of tail serial numbers to obtain the tail serial number distribution network; using any position on the line of the head serial number distribution network as the target and any position on the line of the tail serial number distribution network as the starting point, and performing a search for a preset number of times according to the preset search step length to obtain the distribution position expansion result.

[0078] Next, the specific configuration of the optimization module 50 will be described in detail. As described above, using any position on the line of the head serial number distribution network as the target and any position on the line of the tail serial number distribution network as the starting point, and performing a search for a preset number of times according to the preset search step length to obtain the distribution position expansion result. The optimization module 50 may further include: using any position on the line of the head serial number distribution network as the target and any position on the line of the tail serial number distribution network as the starting point, and performing a search according to the preset search step length to obtain a primary search direction and a primary search position; analyzing the primary search position fitness of the primary search position according to the detection fitness function; when the primary search position fitness is less than the search starting point fitness, retreating to the search starting point and updating the primary search direction to perform a re-search; when the primary search position fitness is greater than or equal to the search starting point fitness, performing an iterative search based on the primary search direction and the primary search position.

[0079] The cable channel fault location system for distributed optical fiber sensing provided by the embodiments of the present application can execute the cable channel fault location method for distributed optical fiber sensing provided by any embodiment of the present application, and has the corresponding functional modules and beneficial effects for executing the method.

[0080] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, however, any number of different modules can be used and run on the user terminal and / or the server. The included respective units and modules are only divided according to the functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present application.

[0081] The above specific embodiments do not constitute a limitation to the protection scope of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of this application shall be included within the protection scope of this application.

Claims

1. A cable channel fault location method based on distributed optical fiber sensing, characterized in that: A cable channel fault location system for distributed optical fiber sensing, wherein the system is embedded in a service layer, the service layer is in communication with a detection light transmitter, an optical fiber sensor, and an environmental sensor, and the optical fiber sensor is arranged along a cable laying path at a preset interval, including: Communicate with environmental sensors to obtain ambient temperature, ambient humidity, magnetic field strength and ambient light intensity; Obtaining detection light pulse parameters of the detection light transmitter; Construct detection fitness function; Analyzing the ambient temperature, the ambient humidity, the magnetic field strength and the ambient light intensity according to the detection fitness function, and the fitness evaluation value of the detection light pulse parameters; When the fitness evaluation value is less than or equal to the fitness threshold, based on the ambient temperature, the ambient humidity, the magnetic field strength and the ambient light intensity, the detection light pulse parameters are optimized according to the detection fitness function to obtain the detection light recommended pulse parameters; Controlling the detection light transmitter to transmit detection light to the optical fiber sensor according to the detection light recommended pulse parameter, and receiving feedback information from the optical fiber sensor; Perform signal classification processing on the feedback information of the optical fiber sensor to obtain the fault signal generation position, add it into the cable channel fault location result and send it to the cable management terminal; The constructing of the detection fitness function comprises: Taking the ambient temperature, the ambient humidity, the magnetic field strength and the ambient light intensity as environmental constraints, and taking the detection light pulse parameters as detection light constraints, collecting optical fiber sensing detection records, wherein the optical fiber sensing detection records include optical fiber sensor receiving detection light pulse record parameters, cable fault record positioning results and cable fault actual positioning results, and the cable fault actual positioning results are obtained by measuring with a dedicated instrument; According to the recording parameters of the detection light pulse received by the optical fiber sensor, the recorded positioning result of the cable fault and the actual positioning result of the cable fault, a detection fitness function is constructed: , in, Respectively characterize the ambient temperature, ambient humidity, magnetic field strength, ambient light intensity, the pulse width of the optical fiber sensor receiving the detection light pulse recording parameter, the pulse frequency of the optical fiber sensor receiving the detection light pulse recording parameter, the optical power of the optical fiber sensor receiving the detection light pulse recording parameter and the cable fault recording and positioning results, The pulse width that characterizes the detection light pulse parameters, The pulse frequency characterizes the parameters of the probe light pulse, Characterize the actual location results of cable faults, The optical power that characterizes the parameters of the probe light pulse, , , and The pulse width weight, pulse frequency weight, optical power weight and fault location weight are characterized respectively.

2. The method according to claim 1, characterized in that Analyzing the ambient temperature, the ambient humidity, the magnetic field strength, and the ambient light intensity according to the detection fitness function, and evaluating the fitness of the detection light pulse parameters, including: With the detection light transmitter model and the optical fiber sensor model as constraints, collect ambient temperature recording data, ambient humidity recording data, magnetic field intensity recording data, ambient light intensity recording data, and detection light pulse recording parameters; Analyzing the ambient temperature recording data, the ambient humidity recording data, the magnetic field intensity recording data, the ambient light intensity recording data, and the initial fitness evaluation data of the detection light pulse recording parameters according to the detection fitness function; Applying an allowable fault-tolerant disturbance to the initial fitness evaluation data to obtain fitness identification data; Constructing decision constraints based on the detection fitness function; Taking the fitness identification data as supervision, taking the ambient temperature recording data, the ambient humidity recording data, the magnetic field intensity recording data, the ambient light intensity recording data, and the detection light pulse recording parameters as input, and based on the decision constraints, training a fitness evaluation unit; The adaptability evaluation unit analyzes the ambient temperature, the ambient humidity, the magnetic field strength and the ambient light intensity to obtain an adaptability evaluation value of the detection light pulse parameter.

3. The method according to claim 1, characterized in that When the fitness evaluation value is less than or equal to the fitness threshold, the detection light pulse parameters are optimized according to the detection fitness function based on the ambient temperature, the ambient humidity, the magnetic field strength, and the ambient light intensity to obtain the detection light recommended pulse parameters, including: Obtaining the layout distance information between the optical fiber sensor and the detection light transmitter; Based on the deployment distance information, a pulse width constraint interval, a pulse frequency constraint interval and an optical power constraint interval are configured to construct a pulse parameter optimization space; Obtaining a pulse parameter history configuration database, wherein the pulse parameter history configuration database includes a set of detection light pulse parameter quaternary arrays, and any one of the detection light pulse parameter quaternary arrays includes pulse width, pulse frequency, optical power, and adaptability; According to the pulse width, the pulse frequency, and the optical power, selecting an initial detection light pulse parameter quaternary array set that satisfies the pulse parameter optimization space from the detection light pulse parameter quaternary array set; According to the adaptability, the detection light pulse parameters are optimized based on the initial detection light pulse parameter quaternion array set to obtain the detection light recommended pulse parameters.

4. The method according to claim 3, characterized in that According to the adaptability, the detection light pulse parameters are optimized based on the initial detection light pulse parameter quaternion array set to obtain the detection light recommended pulse parameters, including: When the set of the initial detection light pulse parameter quaternary arrays has a quaternary array greater than the adaptation threshold, outputting the detection light recommended pulse parameters; When the initial detection light pulse parameter quaternary array set does not have a quaternary array greater than the fitness threshold, distributing the initial detection light pulse parameter quaternary array set in the pulse parameter optimization space based on the pulse width, the pulse frequency, and the optical power to obtain an initial distribution position set; According to the distribution distance threshold, performing aggregation analysis on the initial distribution position set to obtain multiple cluster distribution positions; Traversing the multiple cluster distribution positions to extract the maximum value of the fitness degree, and obtaining multiple initial position sorting results; Based on the multiple initial position sorting results, iterative expansion is performed in combination with the detection fitness function to obtain a distribution position expansion result, wherein the distribution position expansion result has an expansion position fitness evaluation value; When the expanded position fitness evaluation value is greater than the fitness threshold, the detection light pulse parameter corresponding to the distribution position expansion result is set as the detection light recommended pulse parameter.

5. The method according to claim 4, characterized in that Based on the multiple initial position sorting results, iterative expansion is performed in combination with the detection fitness function to obtain a distribution position expansion result, including: Sorting the plurality of initial position sorting results from large to small according to the degree of fitness to obtain an initial position sorting result; Filter the initial positions of the first number of head numbers, connect the initial positions of the first number of head numbers, and obtain a head number distribution network; Filter the initial positions of the tail numbers of the second quantity, connect the initial positions of the tail numbers of the second quantity, and obtain a tail number distribution network; Taking any online position of the head sequence number distribution network as the target and any online position of the tail sequence number distribution network as the starting point, searching a preset number of times according to a preset search step length is performed to obtain the distribution position expansion result.

6. The method according to claim 5, characterized in that Taking any online position of the head sequence number distribution network as the target and any online position of the tail sequence number distribution network as the starting point, searching a preset number of times according to a preset search step length to obtain the distribution position expansion result, including: Taking any online position of the head sequence number distribution network as the target and any online position of the tail sequence number distribution network as the starting point, searching according to a preset search step length to obtain a search direction and a search position; Analyzing the first search position fitness of the first search position according to the detection fitness function; When the fitness of the first search position is less than the fitness of the search starting point, return to the search starting point, update the first search direction and search again; When the adaptation degree of the primary search position is greater than or equal to the adaptation degree of the search starting point, an iterative search is performed based on the primary search direction and the primary search position.

7. A cable channel fault location system using distributed optical fiber sensing, the system being used to implement the cable channel fault location method using distributed optical fiber sensing according to any one of claims 1 to 6, the system being embedded in a service layer, the service layer being communicatively connected to a detection light transmitter, an optical fiber sensor and an environmental sensor, the optical fiber sensor being arranged along a cable laying path at a preset interval, comprising: A communication module is used to communicate with the environmental sensor to obtain the ambient temperature, ambient humidity, magnetic field strength and ambient light intensity; A detection module, used to obtain detection light pulse parameters of a detection light transmitter; A construction module for constructing a detection fitness function; An evaluation module, used for analyzing the environmental temperature, the environmental humidity, the magnetic field strength and the environmental light intensity according to the detection fitness function, and the fitness evaluation value of the detection light pulse parameter; An optimization module, configured to optimize the detection light pulse parameters according to the detection fitness function to obtain detection light recommended pulse parameters when the fitness evaluation value is less than or equal to a fitness threshold value based on the ambient temperature, the ambient humidity, the magnetic field strength and the ambient light intensity; A control module, used for controlling the detection light transmitter to transmit detection light to the optical fiber sensor according to the detection light recommended pulse parameter, and receiving feedback information from the optical fiber sensor; The classification module is used to perform signal classification processing on the feedback information of the optical fiber sensor, obtain the fault signal generation position, add the fault location result into the cable channel and send it to the cable management terminal.

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