Ring main unit cable head state detection method and device and computer program product

Abstract

The invention discloses a ring main unit cable head state detection method and device and a computer program product, and the method comprises the steps: collecting a backscattering signal of a distributed optical fiber which is disposed at a ring main unit cable head in advance, and demodulating a temperature data sequence and / or a strain data sequence; based on the temperature data sequence and / or the strain data sequence, evaluating the insulation state, the contact state and the mechanical stress state of the ring main unit cable head; inputting the insulation state, the contact state and the mechanical stress state into a preset cable head fault identification model to obtain a fault type of the cable head of the ring main unit; according to the fault type and the spatial position of the abnormal data on the optical fiber, the actual fault position is determined, and early warning is given out. According to the invention, temperature measurement and / or strain measurement are / is carried out by introducing the distributed optical fiber sensing technology, automatic judgment of the fault type of the cable head, accurate positioning of the fault position and timely early warning are realized, the fault diagnosis efficiency and accuracy are remarkably improved, and safe operation of a power distribution network is ensured.

Description

Technical Field

[0001] This invention relates to the field of power equipment testing technology, specifically to a method, device, and computer program product for detecting the condition of cable heads in a ring main unit. Background Technology

[0002] Ring main units are core equipment in urban power distribution networks, and their cable heads are responsible for connecting the main cable to the switch unit. Operating under high voltage and high current conditions for extended periods, these cable heads are prone to malfunctions due to factors such as insulation aging, poor contact, partial discharge, and excessive temperature. In severe cases, this can lead to equipment burnout or even fire, threatening the safe operation of the power grid.

[0003] Currently, the status monitoring of cable heads in ring main units mainly relies on periodic inspections, infrared thermography, and partial discharge detection. These methods have long detection cycles, limited coverage, insufficient accuracy, and cannot provide real-time early warning. For cable heads deeply buried inside the cabinet or in complex environments, continuous, online, and high spatial resolution monitoring is even more difficult. Summary of the Invention

[0004] The technical problem to be solved by the embodiments of the present invention is to provide a method, device and computer program product for detecting the status of cable heads in ring main units, so as to improve the efficiency and accuracy of fault diagnosis and ensure the safe operation of the power distribution network.

[0005] To solve the above technical problems, the present invention provides a method for detecting the status of cable heads in a ring main unit, comprising: Step S1: Collect the backscattered signal of the distributed optical fiber that has been pre-deployed at the cable head of the ring network cabinet, and demodulate the temperature data sequence and / or strain data sequence. Step S2: Based on the temperature data sequence and / or strain data sequence, evaluate the insulation state, contact state, and mechanical stress state of the cable head of the ring main unit; Step S3: Input the insulation state, contact state and mechanical stress state into the preset cable head fault identification model to obtain the fault type of the ring main unit cable head; Step S4: Determine the actual location of the fault and issue an early warning based on the fault type and the spatial location of the abnormal data on the optical fiber.

[0006] Preferably, step S1 specifically includes: The backscattered signal is divided into multiple sub-signals, each corresponding to a different frequency range; The corresponding local oscillator signal is determined based on the frequency range of each sub-signal and then mixed to obtain the intermediate frequency signal. Based on the intermediate frequency signal, extract temperature-related Rayleigh scattering signal and / or strain-related Brillouin scattering signal; The Rayleigh scattering signal is processed to obtain a temperature data sequence, and / or the Brillouin scattering signal is processed to obtain a strain data sequence.

[0007] Preferably, step S2 specifically includes: Based on the temperature data sequence and / or strain data sequence, determine at least one of the following: temperature distribution, temperature change rate, and hot spot location along the cable head; and / or at least one of the following: strain distribution and strain change rate. Based on at least one of the temperature distribution, temperature change rate, hot spot location, strain distribution and strain change rate along the cable head, at least one of the contact state assessment model, insulation state assessment model and mechanical stress state assessment model is constructed. Based on at least one of the contact condition assessment model, the insulation condition assessment model, and the mechanical stress condition assessment model, determine at least one of the following: contact condition score, insulation degradation level, and stress risk level of the cable head. The insulation condition, contact condition, and mechanical stress condition of the cable head are determined based on at least one of the following: contact condition score, insulation degradation level, and stress risk level.

[0008] Preferably, step S3 specifically includes: The insulation state, contact state, and mechanical stress state are pre-processed to obtain the pre-processed insulation state, pre-processed contact state, and pre-processed mechanical stress state. The pre-processed insulation state, pre-processed contact state, and pre-processed mechanical stress state are input into the cable head fault identification model, and the cable head fault identification model is used to extract features and perform sequence analysis on the input data to obtain the fault feature vector of the cable head; wherein, the cable head fault identification model is constructed based on a combination structure of convolutional neural network and recurrent neural network; The fault type of the cable head is determined using a preset classification algorithm based on the fault feature vector.

[0009] Preferably, step S4 specifically includes: Based on the temperature or strain anomaly characteristics corresponding to the fault type, locate the abnormal data point in the temperature data sequence or the strain data sequence. An abnormal signal is generated based on the located abnormal data points, and the spatial position of the abnormal signal on the optical fiber is obtained. The abnormal signal is determined based on the portion of the temperature data sequence and strain data sequence that exceeds a preset threshold. Based on the spatial layout information of the optical fiber, the spatial location of the abnormal signal is converted into the actual physical location of the ring main unit cable head. Based on the actual physical location, fault location is determined for the cable head of the ring main unit, and fault location information is generated. A fault warning is issued based on the fault location information and fault type.

[0010] Preferably, the distributed optical fiber is pre-laid at least at the conductor connection of the ring main unit cable head, the end of the insulation shielding layer, the stress control cone, and the outer sheath of the cable; the distributed optical fiber is laid along the axial direction of the ring main unit cable head, or along the spiral winding method of the ring main unit cable head.

[0011] Preferably, the deployment of the distributed optical fiber specifically includes: Obtain the three-dimensional structural information of the cable heads in the ring main unit; The initial fiber optic routing path and initial fiber optic routing density are determined based on the three-dimensional structural information. The initial fiber optic deployment path and the initial fiber optic deployment density are optimized using the locust optimization algorithm to obtain the optimal fiber optic deployment scheme. Fiber optic cables were laid at key locations of the ring main unit cable heads according to the optimal fiber optic deployment scheme.

[0012] Preferably, the optimization of the initial fiber optic deployment path and the initial fiber optic deployment density using the locust optimization algorithm to obtain the optimal fiber optic deployment scheme specifically includes: Initialize a locust swarm, wherein each locust in the swarm represents a combination of an initial optical fiber deployment path and an initial optical fiber deployment density. The fitness value of each locust is calculated based on the objective function, which is determined according to the rationality of the optical fiber deployment path, the uniformity of the optical fiber deployment density, and the accuracy of the optical fiber acquisition data. The locusts in the locust population are sorted according to the fitness value to obtain the sorted locust population. Select locusts whose fitness values ​​reach a preset fitness value from the sorted locust population as elite locusts. The position of the locust population is updated to obtain an updated locust population. The new position of each locust in the updated locust population is determined based on its current position, the position of the elite locust, and a preset jump intensity and a preset flight direction. Repeat the steps of calculating fitness value, sorting, and updating position until the preset number of iterations or convergence condition is met. Then, take the fiber optic deployment path and fiber optic deployment density corresponding to the locust with the highest current fitness value as the optimal fiber optic deployment scheme.

[0013] The present invention also provides a ring main unit cable head status detection device, comprising: The signal acquisition and demodulation module is used to acquire the backscattered signal of the distributed optical fiber that has been pre-deployed in the cable head of the ring network cabinet, and demodulate the temperature data sequence and / or strain data sequence. The condition assessment module is used to assess the insulation condition, contact condition, and mechanical stress condition of the cable head of the ring main unit based on the temperature data sequence and / or strain data sequence. The fault identification module is used to input the insulation state, contact state and mechanical stress state into a preset cable head fault identification model to obtain the fault type of the cable head of the ring main unit. The fault location and early warning module is used to determine the actual location of the fault and issue an early warning based on the fault type and the spatial location of the abnormal data on the optical fiber.

[0014] The present invention also provides a ring main unit cable head status detection device, comprising: One or more processors; Memory; One or more computer programs, wherein the one or more computer programs are stored in the memory and configured to be executed by the one or more processors, and the one or more computer programs are configured to perform the ring main unit cable head status detection method.

[0015] The present invention also provides a computer program product, characterized in that it includes computer instructions, which instruct computer equipment to perform the operation corresponding to the ring main unit cable head status detection method.

[0016] The implementation of this invention has the following beneficial effects: By introducing distributed optical fiber sensing technology, this invention achieves temperature and strain measurement at cable heads, providing comprehensive optimization for the condition detection and fault management of cable heads in ring main units, bringing multi-dimensional core benefits. From a technical adaptability perspective, distributed optical fiber sensing possesses unique advantages such as resistance to electromagnetic interference, intrinsic safety, and high-precision distributed measurement. It can accurately match the complex electromagnetic environment of the power distribution network, avoiding data deviations caused by electromagnetic interference in traditional detection methods. This ensures the authenticity and continuity of temperature and strain field data acquisition at key parts of the cable head (such as conductor connections and stress control cones), providing reliable data support for subsequent diagnosis. From a fault diagnosis efficiency perspective, this technology can automatically demodulate temperature / strain data sequences. Combined with condition assessment models and fault identification models, it can automatically determine the fault type, eliminating the need for manual point-by-point inspection and significantly shortening fault diagnosis time. Simultaneously, relying on the spatial positioning characteristics of optical fibers, it can map abnormal data to the actual physical location of the cable head, solving the problem of ambiguous traditional positioning and significantly improving the efficiency and accuracy of fault diagnosis. From the perspective of power distribution network operation and maintenance, real-time monitoring and timely early warning functions can identify potential faults such as insulation aging and poor contact in advance, transforming passive emergency repairs into preventive maintenance, effectively reducing the risk of large-scale power outages caused by cable head faults, and reducing the economic losses caused by power outages; at the same time, it reduces unnecessary equipment disassembly and maintenance, lowers operation and maintenance costs, extends the service life of cable heads, and comprehensively ensures the safe, stable and efficient operation of the power distribution network. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a method for detecting the status of cable heads in a ring main unit according to an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram illustrating the specific process of laying optical fibers in an embodiment of the present invention.

[0020] Figure 3 This is a schematic diagram of the structure of a ring main unit cable head status detection device according to Embodiment 2 of the present invention.

[0021] Figure 4 This is a schematic diagram of the structure of a ring main unit cable head status detection device according to Embodiment 3 of the present invention. Detailed Implementation

[0022] The following description of the embodiments is taken with reference to the accompanying drawings, which illustrate specific embodiments in which the invention can be implemented.

[0023] Please refer to Figure 1 As shown, Embodiment 1 of the present invention provides a method for detecting the status of cable heads in a ring main unit, comprising: Step S1: Collect the backscattered signal of the distributed optical fiber that has been pre-deployed at the cable head of the ring network cabinet, and demodulate the temperature data sequence and / or strain data sequence. Step S2: Based on the temperature data sequence and / or strain data sequence, evaluate the insulation state, contact state, and mechanical stress state of the cable head of the ring main unit; Step S3: Input the insulation state, contact state and mechanical stress state into the preset cable head fault identification model to obtain the fault type of the ring main unit cable head; Step S4: Determine the actual location of the fault and issue an early warning based on the fault type and the spatial location of the abnormal data on the optical fiber.

[0024] As can be seen from the above steps, the embodiments of the present invention introduce distributed optical fiber sensing technology for temperature and / or strain measurement, thereby achieving automatic judgment of cable head fault types, accurate location of faults, and timely early warning, significantly improving fault diagnosis efficiency and accuracy, and ensuring the safe operation of the power distribution network.

[0025] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device capable of performing the above functions, such as a ring main unit cable head status detection device based on distributed optical fiber sensing technology. The following description uses a ring main unit cable head status detection device based on distributed optical fiber sensing technology as an example to illustrate this embodiment.

[0026] Specifically, in this embodiment of the invention, optical fibers are pre-laid at key parts of the ring main unit cable head. The key parts include at least the conductor connection, the end of the insulation shielding layer, the stress control cone, and the cable outer sheath. As an example, the laid optical fibers include temperature measuring optical fibers and / or strain measuring optical fibers, and are laid along the axial direction or in a spiral winding manner along the ring main unit cable head, for real-time acquisition of temperature field distribution data and / or strain field distribution data along the cable head.

[0027] It should be noted that the cable heads of ring main units are a crucial component of the power distribution network, and their operational status directly affects the safety and stability of the grid. During actual operation, cable heads may fail for various reasons, such as insulation aging, poor contact, or excessive mechanical stress. If these faults are not detected and addressed promptly, they may lead to more serious consequences, even triggering large-scale power outages.

[0028] To achieve real-time monitoring and accurate early warning of the cable head status of ring main units, this embodiment of the invention employs distributed optical fiber sensing technology. Distributed optical fiber sensing technology utilizes the backscattering effect (such as Raman scattering, Brillouin scattering, and Rayleigh scattering) generated when light propagates in optical fibers to achieve continuous measurement of physical quantities such as temperature, strain, and vibration along the length of the optical fiber. It has advantages such as resistance to electromagnetic interference, intrinsic safety, long-distance operation, high precision, and distributed measurement, making it particularly suitable for status monitoring in complex electromagnetic environments within power equipment.

[0029] It is understood that, in this embodiment of the invention, the distributed optical fiber sensing technology, by deploying temperature-measuring optical fibers and / or strain-measuring optical fibers at key locations in the cable head, can acquire real-time temperature field distribution data and / or strain field distribution data along the cable head. The temperature-measuring optical fiber employs Raman scattering distributed temperature measurement technology; by measuring the intensity distribution of backscattered Raman light in the optical fiber, temperature information along the line can be obtained. The strain-measuring optical fiber employs Brillouin scattering distributed strain measurement technology; by measuring the frequency change of the Brillouin scattered light, the strain along the optical fiber can be calculated.

[0030] It is worth noting that the key parts of the cable head of the ring main unit refer to those parts that are prone to failure or require special monitoring, including but not limited to conductor connections, the end of the insulation shield, stress control cones and cable outer sheaths. The health status of these parts is directly related to the overall performance of the cable head, so real-time monitoring of them is of great significance.

[0031] In practical implementation, when laying optical fibers, temperature-sensing fibers, strain-sensing fibers, or a combination of both can be selected according to actual needs to ensure comprehensive and accurate acquisition of temperature and strain field information of the cable head. The fiber optics can be laid axially or spirally, depending on the cable head structure and monitoring requirements. Along the axial or spiral winding pattern of the ring main unit cable head, temperature-sensing and / or strain-sensing fibers should be precisely placed at key locations such as conductor connections, the ends of insulation shielding layers, stress control cones, and the cable outer sheath. The fiber optic layout must ensure comprehensive coverage and tight fit to all key areas of the cable head to accurately collect temperature and strain field data. During the laying process, care must be taken to protect the fibers to prevent damage due to vibration, friction, or other factors during cable head operation, which could affect the accuracy of data acquisition.

[0032] After the optical fiber is laid out, a probe light pulse is first emitted into the optical fiber in step S1, and the echo signal generated by backscattering in the optical fiber is received.

[0033] It should be noted that the probe light pulse is used to excite backscattering effects in the optical fiber, such as Raman scattering, Brillouin scattering, Rayleigh scattering, etc. This embodiment does not impose specific limitations on this, thereby obtaining information on physical quantities such as temperature and strain along the optical fiber.

[0034] In practice, a series of short-pulse optical signals can be emitted into an optical fiber using a laser. As these signals propagate through the fiber, they interact with the fiber material, causing backscattering and generating echo signals. These echo signals carry information about physical quantities along the fiber, such as temperature and strain. By receiving and analyzing these echo signals, real-time monitoring of the cable head condition can be achieved.

[0035] Then, the echo signal is demodulated to extract the temperature data sequence and / or strain data sequence.

[0036] In practice, the demodulation process can be accomplished using photodetectors and signal processing circuits. The photodetector converts the received echo signal into an electrical signal, which is then amplified and filtered by the signal processing circuit to ultimately extract the temperature and / or strain data sequences. These data sequences reflect the distribution of the temperature and / or strain fields along the cable head, forming the basis for subsequent condition analysis and fault diagnosis.

[0037] In one feasible implementation, step S1 may include: dividing the echo signal into multiple sub-echo signals, wherein each sub-echo signal corresponds to a different frequency range; determining the corresponding local oscillator signal according to the frequency range of each echo signal, and mixing each echo signal with the corresponding local oscillator signal to obtain an intermediate frequency signal; demodulating the intermediate frequency signal to obtain a demodulation result; extracting the temperature-related Rayleigh scattering signal and the strain-related Brillouin scattering signal according to the demodulation result; performing signal amplification, filtering, and analog-to-digital conversion on the Rayleigh scattering signal to obtain a temperature data sequence; and performing signal amplification, frequency analysis, and analog-to-digital conversion on the Brillouin scattering signal to obtain a strain data sequence.

[0038] It should be noted that dividing the echo signal into multiple sub-echo signals and demodulating each sub-echo signal is to improve the accuracy and efficiency of data extraction. Since the echo signal generated by backscattering effects in optical fibers may contain multiple frequency components, these frequency components correspond to different physical quantities (such as temperature and strain). By segmenting the echo signal and selecting an appropriate local oscillator signal for mixing each segment, temperature-related Rayleigh scattering signals and strain-related Brillouin scattering signals can be effectively extracted.

[0039] Understandably, the local oscillator signal is a reference signal used for mixing with the echo signal, and its frequency matches the target frequency component in the echo signal. Through the mixing process, the target frequency component in the echo signal can be converted into an intermediate frequency (IF) signal, which is a lower frequency signal that is easier to process. Demodulating the IF signal yields a demodulated result containing temperature and strain information.

[0040] Furthermore, based on the demodulation results, temperature-related Rayleigh scattering signals and strain-related Brillouin scattering signals can be extracted separately. Rayleigh scattering signals are related to the inhomogeneity of the fiber material's density and refractive index, and their intensity is proportional to temperature. Therefore, temperature data sequences can be obtained by processing Rayleigh scattering signals. Brillouin scattering signals, on the other hand, are related to acoustic vibrations in the fiber, and their frequency shift is proportional to strain. Therefore, strain data sequences can be obtained by processing Brillouin scattering signals.

[0041] In practice, the Rayleigh scattering signal is amplified, filtered, and converted from analog to digital to obtain a series of discrete temperature data points. These data points are arranged according to the fiber optic cable's location, forming a temperature data sequence. This temperature data sequence reflects the temperature distribution along the cable head. By analyzing the trend of the temperature data sequence, it is possible to determine whether there are any abnormalities such as overheating at the cable head.

[0042] By amplifying, analyzing the frequency, and converting the Brillouin scattering signal to digital, a series of discrete strain data points can be obtained. These data points are arranged in the order of the fiber optic cable's location, forming a strain data sequence. The strain data sequence reflects the strain distribution along the cable head. By analyzing the changes in the strain data sequence, it is possible to determine whether the cable head is subjected to excessive mechanical stress or has potential faults such as deformation.

[0043] After obtaining the temperature data sequence and / or strain data sequence, further analysis of the cable head condition and fault diagnosis can be performed based on these data sequences.

[0044] Step S2 will determine the insulation state, contact state, and mechanical stress state of the cable head based on the temperature data sequence and / or strain data sequence.

[0045] It should be noted that establishing a state assessment model that correlates cable head condition parameters with fiber optic sensing data, based on temperature and strain data sequences, and combining this model, allows for the determination of cable head condition parameters, including insulation condition, contact condition, and mechanical stress condition. The insulation condition of the cable head is a key indicator for evaluating its electrical performance and safety. Good insulation ensures effective voltage isolation under both normal operation and fault conditions, preventing current leakage and short-circuit accidents. The contact condition reflects the connection between the cable head and other components (such as conductors and connectors). Good contact ensures the continuity and stability of current transmission, avoiding problems such as overheating and arcing caused by poor contact. The mechanical stress condition relates to the stability and durability of the cable head under external forces. Excessive mechanical stress may lead to cable head deformation, cracks, or even breakage, thus affecting its normal operation and service life.

[0046] In one feasible implementation, step S2 may include: determining the temperature distribution, temperature change rate, hot spot location, strain distribution, and strain change rate along the cable head based on the temperature data sequence and / or strain data sequence; constructing a contact condition assessment model, an insulation condition assessment model, and a mechanical stress condition assessment model based on the temperature distribution, temperature change rate, hot spot location, strain distribution, and strain change rate along the cable head; determining the contact condition score, insulation degradation level, and stress risk level of the cable head based on the contact condition score, insulation degradation level, and stress risk level of the cable head; and determining the insulation condition, contact condition, and mechanical stress condition of the cable head based on the contact condition score, insulation degradation level, and stress risk level of the cable head.

[0047] It should be noted that temperature distribution is the spatial representation of temperature measurements along the cable head, reflecting the temperature conditions at different locations within the cable head. The rate of temperature change reflects how quickly the cable head temperature changes over time, i.e., the temperature gradient. By monitoring the rate of temperature change, abnormal temperature changes in the cable head, such as rapid temperature rises, can be detected promptly, which is crucial for early warning of potential overheating faults. Hotspot locations refer to areas on the cable head where the temperature rises abnormally. These areas are often high-risk zones for cable head faults. Identifying hotspot locations allows for precise location of potential faults, providing a strong basis for subsequent fault handling and maintenance. Strain distribution reflects the magnitude and distribution of strain along the cable head. By analyzing the strain distribution, the deformation of the cable head under external forces can be understood. The rate of strain change reflects how quickly the strain of the cable head changes over time. By monitoring the rate of strain change, abnormal strain changes in the cable head can be detected promptly, which is also crucial for early warning of potential faults caused by excessive mechanical stress.

[0048] Understandably, the temperature distribution is calculated using the functional relationship between the intensity ratio of Stokes and anti-Stokes light in Raman scattering and temperature. By measuring the intensity ratio of Stokes and anti-Stokes light and combining it with the known relationship between temperature and light intensity ratio, the temperature values ​​at various points along the fiber can be deduced, thus obtaining the temperature distribution. The formula for calculating temperature is:

[0049] in, For position The temperature at that location , Stokes and anti-Stokes light are located in positions respectively. The strength, This is the calibration constant.

[0050] The temperature change rate is calculated by differentiating the temperature distribution over time. It reflects the trend of temperature change of the cable head over time and helps to detect temperature anomalies in a timely manner.

[0051] Hotspot locations are typically determined by analyzing temperature distribution maps; areas with abnormally high temperatures are identified as hotspots. These hotspots may be caused by poor contact, insulation aging, or other reasons, and are high-risk areas for cable head faults. By accurately locating hotspots, targeted measures can be taken for fault warning and handling.

[0052] The strain distribution is calculated by measuring the frequency change of the Brillouin scattered light. The frequency of the Brillouin scattered light in the optical fiber is proportional to the strain experienced by the fiber; therefore, by measuring the frequency distribution of the Brillouin scattered light, the strain distribution along the fiber can be calculated. The strain rate of change is also obtained by calculating the time derivative of the strain distribution. It reflects the trend of strain change at the cable head over time, helping to detect abnormalities such as excessive mechanical stress in a timely manner.

[0053] Understandably, the relevant parameters of the contact condition assessment model include hotspot temperature. Temperature gradient Operating current Its physical model is based on Joule's law of heating and the heat conduction equation, as follows:

[0054] in, For operating power, This represents the contact resistance.

[0055] Contact resistance The larger the current, the more severe the heat generation. A temperature-current calibration curve is established, recording the temperature rise under different currents under normal conditions. If the temperature rises significantly under the same current, it indicates increased contact resistance and a risk of poor contact. A contact status score (normal / warning / fault) is output through a contact status assessment model.

[0056] The parameters associated with the insulation condition assessment model include hotspot location, temperature distribution, and partial discharge (PD) characteristics (if the optical fiber has PD sensing capability). Its judgment logic includes: when hotspots are located at the end of the insulation shield or at stress cones, electric field concentration is likely to occur, leading to insulation aging or partial discharge; a slow and uniform temperature rise may indicate overall insulation degradation; when combined with strain data, insulation material aging is often accompanied by minor deformation, and strain anomalies can be used as an auxiliary criterion. The insulation condition assessment model outputs the insulation degradation level (good / mildly aged / severely aged).

[0057] The associated parameters of the mechanical stress state assessment model include strain distribution, strain rate of change, and thermal strain caused by temperature changes. Its judgment logic includes: sudden changes in local strain, which may be due to uneven installation stress, external extrusion, or material fatigue; and long-term cumulative strain, reflecting material creep or structural loosening. By establishing a strain-position reference map, real-time strain data is compared with the reference map to determine the deviation. If the strain in a certain area exceeds a threshold (e.g., 500...), the deviation is considered. If the stress level is abnormal, it is determined that there is an abnormal mechanical stress, and the stress risk level is output through the mechanical stress state assessment model.

[0058] It is worth noting that by using the determined contact condition score, insulation degradation level, and stress risk level as the insulation condition, contact condition, and mechanical stress condition of the cable head, comprehensive monitoring and early warning of the cable head's health status can be achieved.

[0059] Step S3 inputs the insulation state, contact state and mechanical stress state into the cable head fault identification model to obtain the fault type of the cable head.

[0060] It should be noted that the cable head fault identification model is built based on machine learning methods. This model can learn and identify the characteristics of cable heads under different states, thereby accurately determining the fault type of the cable head. When building the fault identification model, it is first necessary to collect a large amount of cable head state data, including temperature data sequences and strain data sequences under normal and fault states. Then, this data is used to train and validate the model, enabling it to learn the mapping relationship between cable head states and fault types.

[0061] In practical implementation, insulation condition, contact condition, and mechanical stress condition can be used as input features, and the fault type of the cable head can be used as the output target. Through the training process, the model can learn the feature patterns corresponding to different fault types and predict the fault type of the cable head based on the input state data in practical applications.

[0062] Fault types can include, but are not limited to, insulation aging, poor contact, and mechanical damage. Insulation aging refers to the degradation of the performance of the cable head insulation material due to prolonged operation or environmental factors, which may lead to electrical faults. Poor contact refers to poor connection between the cable head and other components, which may result in unstable current transmission or localized overheating. Mechanical damage refers to deformation or breakage of the cable head when subjected to external forces, which may affect its normal operation.

[0063] It is worth noting that the cable head fault identification model can quickly and accurately determine the type of cable head fault. Furthermore, this model can combine historical and real-time monitoring data to continuously monitor and provide early warnings about the health status of cable heads, thereby improving the safety and reliability of the power system.

[0064] In one feasible implementation, step S3 may include: constructing a cable head fault identification model, wherein the cable head fault identification model is constructed based on a combination structure of convolutional neural networks and recurrent neural networks; preprocessing the insulation state, contact state, and mechanical stress state to obtain preprocessed insulation state, preprocessed contact state, and preprocessed mechanical stress state, wherein the preprocessing includes data normalization, missing value imputation, and noise filtering; inputting the preprocessed insulation state, preprocessed contact state, and preprocessed mechanical stress state into the cable head fault identification model, and performing feature extraction and sequence analysis on the input data through the cable head fault identification model to obtain a fault feature vector of the cable head; and determining the fault type of the cable head using a preset classification algorithm based on the fault feature vector.

[0065] It's worth noting that Convolutional Neural Networks (CNNs) excel in image processing and feature extraction, automatically learning and extracting key features from images. Recurrent Neural Networks (RNNs), on the other hand, are adept at handling sequential data, capturing temporal dependencies between data points. Combining CNNs and RNNs leverages the strengths of both, improving the accuracy and efficiency of cable head fault identification.

[0066] Understandably, when constructing a cable head fault identification model, a CNN is first used to extract features from the input features, such as insulation state, contact state, and mechanical stress state. Through structures like convolutional layers and pooling layers, the CNN can automatically learn local and global features from the cable head state data, which are crucial for subsequent fault identification. Then, the extracted feature sequences are input into an RNN, utilizing the RNN's temporal analysis capabilities to further capture the temporal dependencies in the feature sequences, thereby obtaining a more accurate fault feature vector.

[0067] After obtaining the fault feature vector, a pre-defined classification algorithm (such as support vector machine, random forest, neural network, etc.) can be used to classify the fault feature vector, thereby determining the fault type of the cable head. The choice of classification algorithm can be determined based on actual needs and the characteristics of the dataset.

[0068] It is worth noting that the performance of a cable head fault identification model depends not only on the choice of model structure and parameter adjustment, but also closely on the quality and quantity of input data. Therefore, when constructing a fault identification model, it is necessary to ensure the accuracy and completeness of the input data and collect as much sample data as possible for training and validation to improve the model's generalization ability and identification accuracy.

[0069] Step S4 involves fault location and fault warning based on the fault type.

[0070] In practical implementation, high-precision location information provided by distributed fiber optic sensing technology can be used, combined with the fault type output by the fault identification model, to achieve precise fault location. Simultaneously, real-time monitoring and analysis of the cable head status can promptly identify potential fault hazards and trigger a fault early warning mechanism, sending alerts to maintenance personnel and reminding them to take appropriate measures.

[0071] Understandably, a fault early warning mechanism can include various notification methods, such as SMS, email, and audible and visual alarms, to ensure that maintenance personnel receive early warning information in a timely manner. Furthermore, it can be combined with technologies such as Geographic Information Systems (GIS) to visually display the fault location and early warning information to maintenance personnel, helping them quickly pinpoint the fault and develop appropriate handling plans.

[0072] By implementing fault location and early warning mechanisms, cable head faults can be detected and handled promptly, reducing their impact on the power system and improving its safety and reliability. Simultaneously, this provides maintenance personnel with a more convenient and efficient fault handling method, reducing maintenance costs and workload.

[0073] In one feasible implementation, step S4 may include: locating abnormal data points in the temperature data sequence or the strain data sequence according to the temperature anomaly or strain anomaly characteristics corresponding to the fault type; generating an abnormal signal based on the located abnormal data points and obtaining the spatial position of the abnormal signal on the optical fiber, wherein the abnormal signal is determined based on the portion of the temperature data sequence and the strain data sequence that exceeds a preset threshold; converting the spatial position of the abnormal signal into the actual physical position of the ring main unit cable head according to the spatial layout information of the optical fiber; locating the fault in the ring main unit cable head according to the actual physical position and generating fault location information; and providing a fault warning based on the fault location information and the fault type.

[0074] It should be noted that when locating abnormal data points, the trends and numerical ranges in temperature and strain data sequences can be analyzed to identify data points that differ significantly from the normal state. These data points often reflect changes in the cable head condition and are important evidence for fault early warning.

[0075] Understandably, the spatial location of an abnormal signal can be determined by measuring the position of the abnormal data point on the optical fiber. This typically requires the use of high-precision location information provided by distributed optical fiber sensing technology. Then, combined with the spatial layout information of the optical fiber, the spatial location of the abnormal signal can be converted into the actual physical location of the ring main unit cable head, thereby achieving precise fault location. Fault location information can include the specific location of the fault point, the type of fault, and possible causes of the fault. This information is crucial for maintenance personnel to formulate handling plans.

[0076] It is worth noting that, regarding fault early warning, a preset threshold can be set. When the value in the temperature or strain data sequence exceeds the threshold, an early warning mechanism is triggered, sending an alert to maintenance personnel. The early warning information can include the fault location, fault type, and suggested handling measures to help maintenance personnel respond and handle the fault quickly. Through the implementation of fault location and early warning mechanisms, the impact of cable head faults on the power system can be effectively reduced, improving the safety and reliability of the power system.

[0077] As can be seen from the above description, the embodiments of the present invention introduce distributed optical fiber sensing technology for temperature and strain measurement, thereby achieving automatic judgment of cable head fault type, accurate location of fault, and timely early warning, significantly improving the efficiency and accuracy of fault diagnosis and ensuring the safe operation of the power distribution network.

[0078] Please refer to again Figure 2 As shown, the fiber optic deployment process of this embodiment of the invention further includes: Step S101: Obtain the three-dimensional structural information of the cable head of the ring main unit.

[0079] It should be noted that the three-dimensional structural information of the ring main unit cable head includes the cable head's geometry, dimensions, and the relative positions of its components. This three-dimensional structural information can be obtained through three-dimensional scanning or modeling of the ring main unit cable head; this embodiment does not impose specific limitations on this.

[0080] Step S102: Determine the initial fiber optic routing path and initial fiber optic routing density based on the three-dimensional structural information.

[0081] It should be noted that the fiber optic deployment path refers to the specific route in which the fiber optic cable is laid on the cable head of the ring main unit, while the fiber optic deployment density refers to the density of fiber optic deployment at various parts of the cable head.

[0082] When determining the initial fiber optic deployment path, key areas of the cable head need to be considered, such as conductor connections, the ends of the insulation shielding layer, stress control cones, and the cable outer sheath. This ensures the fiber optic cable can cover these critical areas to comprehensively collect temperature and strain field data from the cable head. Simultaneously, the fiber optic deployment route should be rationally planned based on the cable head's geometry and dimensions to avoid crossovers, tangles, or excessive bending during installation, which could negatively impact the fiber optic sensing performance.

[0083] When determining the initial fiber optic cable density, it is necessary to consider factors such as temperature variations and strain at different parts of the cable head, as well as the sensing sensitivity and resolution of the fiber optic cable. For areas with significant temperature variations or concentrated strain, the fiber optic cable density can be appropriately increased to improve the accuracy and reliability of data acquisition. Conversely, for areas with smaller temperature variations or more dispersed strain, the fiber optic cable density can be appropriately reduced to lower costs and improve construction efficiency.

[0084] Step S103: Optimize the initial fiber optic deployment path and the initial fiber optic deployment density using the locust optimization algorithm to obtain the optimal fiber optic deployment scheme.

[0085] It should be noted that the locust optimization algorithm is used to optimize the fiber optic deployment path and density in order to reduce fiber optic redundancy and improve the accuracy of data acquisition.

[0086] It is understandable that the locust optimization algorithm is an intelligent optimization algorithm based on the foraging behavior of locust swarms. It optimizes the objective function by simulating the locusts' aggregation, dispersion, and information sharing behaviors during foraging. When optimizing fiber optic deployment schemes, the fiber optic path and density can be used as optimization variables, while the accuracy and reliability of data acquisition can be used as the objective function. The locust optimization algorithm can then be used for iterative optimization to obtain the optimal fiber optic deployment scheme. The optimal fiber optic deployment scheme can reduce costs and improve construction efficiency while ensuring data acquisition quality.

[0087] In one feasible implementation, step S103 may include: initializing a locust swarm, wherein each locust in the swarm represents a combination of an initial fiber optic deployment path and an initial fiber optic deployment density; calculating the fitness value of each locust according to an objective function, wherein the objective function is determined based on the rationality of the fiber optic deployment path, the uniformity of the fiber optic deployment density, and the accuracy of the fiber optic data acquisition; sorting the locusts in the swarm according to the fitness values ​​to obtain a sorted locust swarm; selecting locusts in the sorted locust swarm whose fitness values ​​reach a preset fitness as elite locusts; updating the position of the locust swarm to obtain an updated locust swarm, wherein the new position of each locust in the updated locust swarm is determined based on its current position, the position of the elite locusts, and a preset jump intensity and a preset flight direction; repeating the steps of calculating fitness values, sorting, and updating positions until a preset number of iterations or convergence conditions are met, and taking the fiber optic deployment path and fiber optic deployment density corresponding to the locust with the highest current fitness value as the optimal fiber optic deployment scheme.

[0088] It should be noted that each locust in the locust swarm represents a combination of fiber optic deployment path and density. The fiber optic deployment path and density are parameters to be optimized.

[0089] Assuming the fiber optic cable deployment path has There are several possible options, and the deployment density is... There are several possible values. The solution for each locust is represented by a set of n×m dimensional combinations:

[0090] in, Indicates the first The locust's first step in path selection One location, Indicates the first The first locust in density selection One position.

[0091] The initialization of these positions is usually random, but to speed up convergence, an initial population with certain patterns can be generated based on prior knowledge or by randomization.

[0092] The objective function calculates the fitness of each locust based on the rationality of the fiber optic deployment path, the uniformity of the fiber optic deployment density, and the accuracy of the fiber optic data acquisition. The rationality of the fiber optic deployment path can be evaluated by calculating indicators such as path length, connectivity, and coverage. The uniformity of the fiber optic deployment density can be measured by calculating the standard deviation or uniformity of the fiber density in each region, with the goal of making the fiber density distribution as uniform as possible. The accuracy of the fiber optic data acquisition can be measured by the error or goodness of fit with actual measurement data, with the goal of making the data as close as possible to the true value. The value of the objective function is determined based on the rationality of the fiber optic deployment path, the uniformity of the fiber optic deployment density, and the accuracy of the fiber optic data acquisition, along with their corresponding weights. The weights can be adjusted according to actual needs to balance the performance requirements of each aspect.

[0093] During the optimization process, the selection of elite locusts plays a crucial role in the convergence speed of the algorithm and the quality of the final result.

[0094] When selecting elite locusts, a subset of locusts with high fitness values ​​are typically chosen, as they represent the optimal fiber optic deployment scheme within the current population. The location information of these elite locusts is used to guide other locusts towards a better solution, thereby accelerating the algorithm's convergence process.

[0095] Updating the locust population's position is one of the key steps in the locust optimization algorithm. In each iteration, the new position of each locust is calculated based on its current position, the position of elite locusts, and preset jump intensity and flight direction. In this way, the locust population gradually converges towards a better solution until the preset number of iterations or convergence conditions are met.

[0096] Convergence criteria are typically determined based on changes in fitness values. When the change in fitness values ​​over multiple consecutive iterations is less than a preset threshold, the algorithm is considered to have converged, and the resulting fiber optic deployment scheme is the optimal solution.

[0097] By optimizing the fiber optic deployment path and density using the locust optimization algorithm, an optimal fiber optic deployment scheme can be obtained that reduces costs and improves construction efficiency while ensuring data acquisition quality.

[0098] Step S104: Install optical fibers at the key parts of the ring main unit cable heads according to the optimal optical fiber deployment scheme.

[0099] It should be noted that when laying optical fibers according to the optimal optical fiber deployment scheme, the temperature measuring optical fiber and / or strain measuring optical fiber should be laid according to the optimal path and density in the optimal optical fiber deployment scheme to ensure that the optical fiber can fully cover the key parts and effectively collect data.

[0100] It is understandable that optical fibers are laid out at the optimal optical fiber density along the optimal optical fiber laying path according to the preset optical fiber laying rules. The preset optical fiber laying rules are designed based on the structural characteristics of the cable head and fault-prone areas to ensure that the optical fiber can fully and accurately cover key parts, thereby improving the accuracy and reliability of condition detection.

[0101] It is worth noting that during the deployment process, it is necessary to ensure that the optical fiber fits tightly against the surface of the cable head and maintains a certain tension to prevent loosening or displacement of the fiber during data acquisition. Simultaneously, the fiber optic connectors need to be reliably connected and secured to ensure stable signal transmission. During deployment, care must also be taken to protect the optical fiber from mechanical damage or environmental influences, which could affect its sensing performance. After the fiber optic deployment is completed, its sensing performance needs to be tested and verified to ensure it meets the data acquisition requirements. Through these steps, the optical fiber deployment of the ring main unit cable head can be achieved, providing a foundation for subsequent temperature and strain data acquisition.

[0102] This invention introduces distributed optical fiber sensing technology to optimize the optical fiber routing path and density based on the three-dimensional structural information of the ring main unit cable head, thereby obtaining the optimal optical fiber routing scheme and routing the optical fiber. This effectively reduces optical fiber redundancy and lowers costs while improving the accuracy and reliability of data acquisition.

[0103] Please refer to Figure 3 As shown, corresponding to the ring main unit cable head status detection method described in Embodiment 1 of the present invention, Embodiment 2 of the present invention also provides a ring main unit cable head status detection device, comprising: The signal acquisition and demodulation module 10 is used to acquire the backscattered signal of the distributed optical fiber that has been pre-deployed in the cable head of the ring network cabinet, and demodulate the temperature data sequence and / or strain data sequence. The condition assessment module 20 is used to assess the insulation condition, contact condition, and mechanical stress condition of the cable head of the ring main unit based on the temperature data sequence and / or strain data sequence. The fault identification module 30 is used to input the insulation state, contact state and mechanical stress state into a preset cable head fault identification model to obtain the fault type of the cable head of the ring main unit. The fault location and early warning module 40 is used to determine the actual location of the fault and issue an early warning based on the fault type and the spatial location of the abnormal data on the optical fiber.

[0104] Furthermore, this embodiment also includes a deployment module for deploying optical fibers at key locations of the ring main unit cable head. The key locations include at least the conductor connection, the end of the insulation shielding layer, the stress control cone, and the cable outer sheath. The optical fibers include temperature-measuring optical fibers and / or strain-measuring optical fibers. The optical fibers are deployed along the axial direction or in a spiral winding manner along the ring main unit cable head. The optical fibers are used to collect temperature field distribution data and / or strain field distribution data along the cable head in real time.

[0105] The signal acquisition and demodulation module 10 specifically includes: The transceiver unit transmits probe light pulses into the optical fiber and receives echo signals generated by backscattering in the optical fiber. The demodulation unit is used to demodulate the echo signal and extract the temperature data sequence and / or strain data sequence.

[0106] Corresponding to the method for detecting the status of cable heads in a ring main unit as described in Embodiment 1 of the present invention, Embodiment 3 of the present invention also provides a device for detecting the status of cable heads in a ring main unit, comprising: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the ring main unit cable head status detection method based on distributed optical fiber sensing technology in Embodiment 1 above.

[0107] Please refer to the following. Figure 4 The diagram illustrates a configuration suitable for implementing the ring main unit cable head status detection device in embodiments of the present invention. The ring main unit cable head status detection device based on distributed optical fiber sensing technology in embodiments of the present invention can include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), vehicle terminals (e.g., vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The illustrated ring main unit cable head status detection device based on distributed optical fiber sensing technology is merely an example and should not impose any limitations on the functionality and scope of application of the embodiments of the present invention.

[0108] Specifically, the ring main unit cable head status detection device of this embodiment may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to the program stored in ROM (Read Only Memory) 1002 or the program loaded from storage device 1003 into RAM (Random Access Memory) 1004. RAM 1004 also stores various programs and data required for the operation of the ring main unit cable head status detection device based on distributed fiber optic sensing technology. The processing device 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, LCDs (Liquid Crystal Displays), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the ring main unit cable head condition detection device based on distributed fiber optic sensing technology to wirelessly or wiredly communicate with other devices to exchange data. Although the figure shows a ring main unit cable head condition detection device based on distributed fiber optic sensing technology with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented alternatively.

[0109] In particular, according to embodiments of the present invention, the processes described in the above-described flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0110] This invention also provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the ring main unit cable head status detection method described in Embodiment 1 above.

[0111] The computer-readable storage medium provided by this invention may be, for example, a USB flash drive, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, RAM (Random Access Memory), ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory or Flash Memory), optical fiber, CD-ROM (CD-Read Only Memory), optical storage device, magnetic storage device, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0112] The aforementioned computer-readable storage medium may be included in the ring main unit cable head status detection device; or it may exist independently and not assembled into the ring main unit cable head status detection device.

[0113] The aforementioned computer-readable storage medium carries one or more programs. When the aforementioned one or more programs are executed by the ring main unit cable head status detection device, the ring main unit cable head status detection device performs the ring main unit cable head status detection method described in Embodiment 1.

[0114] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including LAN (Local Area Network) or WAN (Wide Area Network)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0115] For the working principle and process of the above embodiments, please refer to the description of Embodiment 1 of the present invention, which will not be repeated here.

[0116] As explained above, compared with existing technologies, the beneficial effects of this invention are as follows: By introducing distributed optical fiber sensing technology to achieve temperature and strain measurement of cable heads, this invention provides comprehensive optimization for the condition detection and fault management of cable heads in ring main units, bringing multi-dimensional core benefits. From a technical adaptability perspective, distributed optical fiber sensing possesses unique advantages such as resistance to electromagnetic interference, intrinsic safety, and high-precision distributed measurement. It can accurately match the complex electromagnetic environment of the power distribution network, avoiding data deviations caused by electromagnetic interference in traditional detection methods. This ensures the authenticity and continuity of temperature and strain field data acquisition at key parts of the cable head (such as conductor connections and stress control cones), providing reliable data support for subsequent diagnosis. From a fault diagnosis efficiency perspective, this technology can automatically demodulate temperature / strain data sequences. Combined with condition assessment models and fault identification models, it can automatically determine the fault type, eliminating the need for manual point-by-point inspection and significantly shortening fault diagnosis time. Simultaneously, relying on the spatial positioning characteristics of optical fibers, it can map abnormal data to the actual physical location of the cable head, solving the problem of ambiguous traditional positioning and significantly improving the efficiency and accuracy of fault diagnosis. From the perspective of power distribution network operation and maintenance, real-time monitoring and timely early warning functions can identify potential faults such as insulation aging and poor contact in advance, transforming passive emergency repairs into preventive maintenance, effectively reducing the risk of large-scale power outages caused by cable head faults, and reducing the economic losses caused by power outages; at the same time, it reduces unnecessary equipment disassembly and maintenance, lowers operation and maintenance costs, extends the service life of cable heads, and comprehensively ensures the safe, stable and efficient operation of the power distribution network.

[0117] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for detecting the status of cable heads in a ring main unit, characterized in that, include: Step S1: Collect the backscattered signal of the distributed optical fiber that has been pre-deployed at the cable head of the ring network cabinet, and demodulate the temperature data sequence and / or strain data sequence. Step S2: Based on the temperature data sequence and / or strain data sequence, evaluate the insulation state, contact state, and mechanical stress state of the cable head of the ring main unit; Step S3: Input the insulation state, contact state and mechanical stress state into the preset cable head fault identification model to obtain the fault type of the ring main unit cable head; Step S4: Determine the actual location of the fault and issue an early warning based on the fault type and the spatial location of the abnormal data on the optical fiber.

2. The method according to claim 1, characterized in that, Step S1 specifically includes: The backscattered signal is divided into multiple sub-signals, each corresponding to a different frequency range; The corresponding local oscillator signal is determined based on the frequency range of each sub-signal and then mixed to obtain the intermediate frequency signal. Based on the intermediate frequency signal, extract temperature-related Rayleigh scattering signal and / or strain-related Brillouin scattering signal; The Rayleigh scattering signal is processed to obtain a temperature data sequence, and / or the Brillouin scattering signal is processed to obtain a strain data sequence.

3. The method according to claim 1, characterized in that, Step S2 specifically includes: Based on the temperature data sequence and / or strain data sequence, determine at least one of the following: temperature distribution, temperature change rate, and hot spot location along the cable head; and / or at least one of the following: strain distribution and strain change rate. Based on at least one of the temperature distribution, temperature change rate, hot spot location, strain distribution and strain change rate along the cable head, at least one of the contact state assessment model, insulation state assessment model and mechanical stress state assessment model is constructed. Based on at least one of the contact condition assessment model, the insulation condition assessment model, and the mechanical stress condition assessment model, determine at least one of the following: contact condition score, insulation degradation level, and stress risk level of the cable head. The insulation condition, contact condition, and mechanical stress condition of the cable head are determined based on at least one of the following: contact condition score, insulation degradation level, and stress risk level.

4. The method according to claim 1, characterized in that, Step S3 specifically includes: The insulation state, contact state, and mechanical stress state are pre-processed to obtain the pre-processed insulation state, pre-processed contact state, and pre-processed mechanical stress state. The pre-processed insulation state, pre-processed contact state, and pre-processed mechanical stress state are input into the cable head fault identification model, and the cable head fault identification model is used to extract features and perform sequence analysis on the input data to obtain the fault feature vector of the cable head; wherein, the cable head fault identification model is constructed based on a combination structure of convolutional neural network and recurrent neural network; The fault type of the cable head is determined using a preset classification algorithm based on the fault feature vector.

5. The method according to claim 1, characterized in that, Step S4 specifically includes: Based on the temperature or strain anomaly characteristics corresponding to the fault type, locate the abnormal data point in the temperature data sequence or the strain data sequence. An abnormal signal is generated based on the located abnormal data points, and the spatial position of the abnormal signal on the optical fiber is obtained. The abnormal signal is determined based on the portion of the temperature data sequence and strain data sequence that exceeds a preset threshold. Based on the spatial layout information of the optical fiber, the spatial location of the abnormal signal is converted into the actual physical location of the ring main unit cable head. Based on the actual physical location, fault location is determined for the cable head of the ring main unit, and fault location information is generated. A fault warning is issued based on the fault location information and fault type.

6. The method according to any one of claims 1-5, characterized in that, The distributed optical fiber is pre-laid at least at the conductor connection of the ring main unit cable head, the end of the insulation shielding layer, the stress control cone, and the outer sheath of the cable; the distributed optical fiber is laid along the axial direction of the ring main unit cable head, or laid in a spiral winding manner along the ring main unit cable head.

7. The method according to claim 6, characterized in that, The deployment of the distributed optical fiber specifically includes: Obtain the three-dimensional structural information of the cable heads in the ring main unit; The initial fiber optic routing path and initial fiber optic routing density are determined based on the three-dimensional structural information. The initial fiber optic deployment path and the initial fiber optic deployment density are optimized using the locust optimization algorithm to obtain the optimal fiber optic deployment scheme. Fiber optic cables were laid at key locations of the ring main unit cable heads according to the optimal fiber optic deployment scheme.

8. The method according to claim 7, characterized in that, The optimization of the initial fiber optic deployment path and the initial fiber optic deployment density using the locust optimization algorithm to obtain the optimal fiber optic deployment scheme specifically includes: Initialize a locust swarm, wherein each locust in the swarm represents a combination of an initial optical fiber deployment path and an initial optical fiber deployment density. The fitness value of each locust is calculated based on the objective function, which is determined according to the rationality of the optical fiber deployment path, the uniformity of the optical fiber deployment density, and the accuracy of the optical fiber acquisition data. The locusts in the locust population are sorted according to the fitness value to obtain the sorted locust population. Select locusts whose fitness values ​​reach a preset fitness value from the sorted locust population as elite locusts. The position of the locust population is updated to obtain an updated locust population. The new position of each locust in the updated locust population is determined based on its current position, the position of the elite locust, and a preset jump intensity and a preset flight direction. Repeat the steps of calculating fitness value, sorting, and updating position until the preset number of iterations or convergence condition is met. Then, take the fiber optic deployment path and fiber optic deployment density corresponding to the locust with the highest current fitness value as the optimal fiber optic deployment scheme.

9. A device for detecting the status of cable heads in a ring main unit, characterized in that, include: The signal acquisition and demodulation module is used to acquire the backscattered signal of the distributed optical fiber that has been pre-deployed in the cable head of the ring network cabinet, and demodulate the temperature data sequence and / or strain data sequence. The condition assessment module is used to assess the insulation condition, contact condition, and mechanical stress condition of the cable head of the ring main unit based on the temperature data sequence and / or strain data sequence. The fault identification module is used to input the insulation state, contact state and mechanical stress state into a preset cable head fault identification model to obtain the fault type of the cable head of the ring main unit. The fault location and early warning module is used to determine the actual location of the fault and issue an early warning based on the fault type and the spatial location of the abnormal data on the optical fiber.

10. A device for detecting the status of cable heads in a ring main unit, characterized in that, include: One or more processors; Memory; One or more computer programs, wherein the one or more computer programs are stored in the memory and configured to be executed by the one or more processors, the one or more computer programs being configured to perform the ring main unit cable head status detection method as described in any one of claims 1 to 8.

11. A computer program product, characterized in that, The method includes computer instructions that instruct computer equipment to perform operations corresponding to the ring main unit cable head status detection method as described in any one of claims 1 to 8.

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