Cable damage aging safety assessment method and system

Abstract

The invention discloses a cable damage aging safety assessment method and system, and relates to the technical field of cable aging assessment, and the method comprises the steps: carrying out the performance test of a test sample, constructing a performance test data set of a cable through the test data, constructing a cable quality coefficient through the performance test data set, and carrying out the cable damage aging safety assessment. Judging whether the cable needs to be replaced or not according to the cable quality coefficient, predicting the use state of the cable by using the cable state prediction model, calculating the aging degree of the cable according to prediction data, and if the aging degree exceeds the expectation, performing corresponding processing on the cable; through an accelerated aging test, corresponding aging degrees are constructed according to cable performance data under different test conditions, a conditional influence degree is constructed after linear regression analysis, and if the conditional influence degree exceeds the expectation, an optimization scheme for cable use is output to optimize cable use. A corresponding improvement scheme can be given according to an evaluation result, and the defects of the cable in use are improved in a targeted manner.

Description

Technical Field

[0001] The present invention relates to the technical field of cable aging assessment, and particularly to a method and system for assessing the safety of cable damage and aging. Background Art

[0002] It consists of a tight inner sheath to prevent moisture intrusion or an outer sheath with high mechanical strength, and the structure is relatively complex. The main function of the cable is to connect circuits, electrical appliances and other devices in the power transmission and communication systems to ensure the effective transmission of electric energy or information.

[0003] The assessment of cable damage and aging is a complex process that requires comprehensive consideration of multiple factors. The following are several commonly used assessment methods: Visual inspection: This is the most basic and direct method. By checking the appearance of the cable, it can be initially determined whether there is damage or aging. Electrical parameter testing: This method is more accurate and can evaluate the aging degree by measuring parameters such as the resistance, insulation resistance and capacitance of the cable. Infrared thermal imaging detection: This is a non-contact inspection method. Residual voltage testing: It is also an effective method for evaluating the aging degree of the cable. By testing the residual voltage at the cable terminals, the insulation condition of the cable can be judged, and thus its service life can be further evaluated.

[0004] In the Chinese invention patent with the application publication number CN117313413A, a system and method for assessing the aging degree of a cable are disclosed. The method includes: obtaining the measured usage data, cable attribute information and environmental information of the cable to be assessed, determining similar cables in the detected cable dataset based on the cable attribute information and the environmental information, obtaining the aging degree data and reference usage data of the similar cables, and generating the aging degree information of the cable to be assessed based on the aging degree data of the similar cables, the reference usage data and the measured usage data.

[0005] Combining the above application and the content in the prior art:

[0006] After the cable has been used for a long time, it usually ages gradually by itself. For example, the resistance gradually increases, the voltage loss gradually increases, etc. Therefore, it is necessary to replace or maintain the cable regularly. However, if the cable is in an environment of long-term direct sunlight and high humidity for a long time, the aging degree of the cable may be further accelerated. In the existing cable aging assessment schemes, usually several different test conditions are set for the cable, the cable is tested under different test conditions, and based on the obtained test data, the production of the next batch of cables is adjusted. Therefore, the coverage of the cable aging assessment is relatively low, and these improvements are difficult to form corresponding optimization effects on the current use of the cable.

[0007] Therefore, the present invention provides a method and system for assessing the safety of cable damage and aging. Summary of the Invention

[0008] (1) Technical Problems to be Solved

[0009] In view of the deficiencies of the prior art, the present invention provides a method and system for evaluating the safety of cable damage and aging. The method uses a cable status prediction model to predict the usage status of the cable, calculates the aging degree of the cable from the prediction data, and performs corresponding processing on the cable if the aging degree exceeds the expectation. Through accelerated aging tests, the corresponding aging degrees are constructed from the cable performance data under different test conditions, and the condition influence degree is constructed after linear regression analysis. If the condition influence degree exceeds the expectation, an optimized cable usage plan is output to optimize the cable usage. Corresponding improvement plans can be given according to the evaluation results to specifically improve the deficiencies in cable usage, thus solving the technical problems described in the background art.

[0010] (2) Technical Solutions

[0011] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0012] A method for evaluating the safety of cable damage and aging includes monitoring the usage environment data of the cable and constructing an environmental condition set, constructing an environmental anomaly degree Yo from the environmental condition set, and if the obtained environmental anomaly degree Yo exceeds the expectation, sending an alarm command and selecting some cables as test samples.

[0013] Performing performance tests on the test samples, constructing a cable performance test data set from the test data, constructing a cable quality coefficient Qt from the cable performance test data set, and determining whether the cable needs to be replaced based on the cable quality coefficient Qt. If it does not need to be replaced, maintenance is performed on it.

[0014] Using a cable status prediction model to predict the usage status of the cable, calculating the aging degree Lo of the cable from the prediction data, and performing corresponding processing on the cable if the aging degree Lo exceeds the expectation. Among them, the method for calculating the aging degree Lo of the cable is as follows: linearly normalizing the voltage loss value Uu and the resistance increase value Ur in the following manner:

[0015]

[0016] Weight coefficients: 0 ≤ ρ ≤ 1, 0 ≤ ζ ≤ 1;

[0017] Through accelerated aging tests, the corresponding aging degrees Lo are constructed from the cable performance data under different test conditions, and the condition influence degree is constructed after linear regression analysis. If the condition influence degree exceeds the expectation, an optimized cable usage plan is output to optimize the cable usage.

[0018] Further, monitor the temperature and sunlight irradiation in the area where the cable is located during the environmental monitoring period; generate the environmental temperature Ht and the irradiation duration St, summarize the environmental data in several consecutive environmental monitoring periods to construct an environmental condition set, and construct the environmental anomaly degree Yo from the environmental condition set.

[0019] Further, the environmental anomaly degree Yo is generated as follows: perform linear normalization on the environmental temperature Ht and the irradiation duration St, where,

[0020]

[0021] Weight coefficient: 0 ≤ F1 ≤ 1, 0 ≤ F2 ≤ 1 and F2 + F1 = 1; i = 1, 2, …, k, where k is the number of monitoring periods; Ht i is the environmental temperature in the i-th monitoring period, Ht avg is the average value of the environmental temperature, St i is the irradiation duration in the i-th monitoring period, St avg is the average value of the irradiation duration.

[0022] Further, perform a performance test on the selected test samples, summarize the obtained test data to construct a performance test data set of the cable; construct the current cable quality coefficient Qt based on the performance test data set of the cable. If the cable quality coefficient Qt is lower than the quality threshold, send an alarm instruction to the outside.

[0023] Further, the cable quality coefficient Qt is obtained as follows: perform linear normalization on the operating temperature Xt and the resistance Xr of the cable according to the following method:

[0024]

[0025] where i = 1, 2, …, n, n is the number of test nodes, Xt i is the charging efficiency of the i-th test node, Xr i is the resistance of the i-th test node, and the weight coefficient: 0 ≤ F1 ≤ 1, 0 ≤ F2 ≤ 1, and F1 + F2 = 1.

[0026] Further, replace the cable after receiving the alarm instruction; if the alarm instruction is not received, continue to maintain the current usage status; identify the current usage status data of the cable to obtain the corresponding status features; obtain several cable operation and maintenance plans, summarize the cable operation and maintenance plans to construct a post-maintenance plan library; based on the correspondence between the status features and the operation and maintenance plans, match the corresponding operation and maintenance plan for the cable to maintain the use of the cable.

[0027] Furthermore, after maintaining the operation of the cable, train to obtain a cable status prediction model. During the observation period, use the cable status prediction model to predict the usage status of the cable. At the prediction node, obtain the predicted data of the cable usage; compare the predicted data of the cable with the standard reference value, obtain the voltage loss value Uu and the resistance increase value Ur when the cable is used at the prediction node, calculate to obtain the aging degree Lo. If the aging degree Lo exceeds the expectation, after the observation period ends, take corresponding maintenance or replacement measures.

[0028] Furthermore, use an unused cable as a standard sample, set several groups of different test conditions for the standard sample, and conduct accelerated aging tests on the standard sample under different test conditions to obtain cable performance detection data under different test conditions. After summarizing, construct a test performance test set;

[0029] Obtain several groups of aging degrees Lo from the test performance test set. Use the test conditions as independent variables and the aging degree Lo as the dependent variable to conduct linear regression analysis and construct the corresponding linear regression equation. Use the regression coefficient corresponding to the independent variable in the linear regression equation as the influencing factor.

[0030] Furthermore, determine the corresponding weight coefficient for each independent variable according to the analytic hierarchy process, obtain the product of the influencing factor and the weight coefficient, sum up the products to construct the condition influence degree. If the condition influence degree exceeds the influence degree threshold, collect the environmental conditions and working conditions of the test sample and obtain the corresponding usage data;

[0031] Identify the current usage data of the cable, determine the corresponding optimization features, construct a cable optimization knowledge graph with the cable usage optimization as the target word. According to the correspondence between the cable usage optimization plan and the optimization features, give an optimization plan for the cable usage of the test sample to extend the service life of the cable.

[0032] A cable damage and aging safety assessment system, including: an environment analysis unit, which monitors the usage environment data of the cable and constructs an environment condition set, constructs an environment abnormality degree Yo from the environment condition set. If the obtained environment abnormality degree Yo exceeds the expectation, issue an alarm instruction and select some cables as test samples;

[0033] A performance evaluation unit, which conducts performance tests on the test samples, constructs a cable performance test data set from the test data, constructs a cable quality coefficient Qt from the performance test data set, and judges whether the cable needs to be replaced according to the cable quality coefficient Qt. If it does not need to be replaced, maintain it;

[0034] An aging prediction unit, which uses a cable status prediction model to predict the usage status of the cable, calculates the aging degree Lo of the cable from the predicted data. If the aging degree Lo exceeds the expectation, perform corresponding processing on the cable;

[0035] Maintenance unit: Through accelerated aging tests, construct the corresponding aging degree Lo based on the cable performance data under different test conditions, and construct the condition influence degree after linear regression analysis. If the condition influence degree exceeds the expectation, output an optimized cable usage plan to optimize the cable usage.

[0036] (III) Beneficial effects

[0037] The present invention provides a method and system for evaluating the safety of cable damage and aging, having the following beneficial effects:

[0038] 1. Judge whether the current environmental conditions are suitable for cable usage based on the environmental abnormality Yo. If it is suitable, the cable can continue to work under the current environmental conditions; monitor whether there are abnormalities in the cable usage environment and make adaptive adjustments during abnormalities to extend the cable service life.

[0039] 2. Construct the corresponding cable quality coefficient Qt based on the performance data obtained from tests, judge whether the cable meets the usage requirements according to the cable quality coefficient Qt, and conduct a preliminary assessment of cable aging to confirm whether the cable can continue to be used; after obtaining the current state characteristics of the cable, quickly give an operation and maintenance plan. Through the operation and maintenance of the cable, when there is a risk that the cable is no longer available, after completing the aging assessment of the cable, extend the cable service life.

[0040] 3. Compare the predicted data with the standard data to construct the aging degree of the cable after maintenance, conduct an aging evaluation of the cable again, and judge the next aging degree of the cable based on this. If the cable is about to age, further in-depth maintenance or direct replacement is required to ensure the safety of cable usage.

[0041] 4. Based on each influencing factor, judge the influence degree of different independent variables on cable aging. If the influence degree is relatively high, it can be used as a target feature for targeted processing to narrow the optimization scope, and improve the efficiency when delaying the cable aging process. After determining that the cable aging is accelerated due to environmental conditions and usage conditions, targeted processing can be carried out.

[0042] 5. Obtain several optimization features, and the cable optimization knowledge graph gives an optimization plan. Optimize the cable usage according to the optimization plan, so as to improve the cable service life by optimizing and improving the working environment and working state of the cable when it is not necessary to replace the cable temporarily. After repeatedly completing the aging assessment of the cable, corresponding improvement plans can be given according to the assessment results to specifically improve the deficiencies in cable usage. Description of the drawings

[0043] Figure 1 Schematic diagram of the process for the method of evaluating the safety of cable damage and aging of the present invention;

[0044] Figure 2 Schematic diagram of the structure of the system for evaluating the safety of cable damage and aging of the present invention. Specific embodiments

[0045] Next, in combination with the accompanying drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0046] Please refer to Figure 1 , the present invention provides a method for evaluating the safety of cable damage and aging, including:

[0047] Step 1: Monitor the usage environment data of the cable and construct an environmental condition set. Construct an environmental abnormality degree Yo from the environmental condition set. If the obtained environmental abnormality degree Yo exceeds the expectation, send an alarm instruction and select some cables as test samples;

[0048] The content of the above step 1 includes the following:

[0049] Step 101: After defining the usage area of the cable, monitor the usage environment data of the cable in the following way: Set an environmental monitoring period, for example, one day as an environmental monitoring period, and monitor the temperature and sunlight irradiation in the area where the cable is located within the environmental monitoring period; Obtain the average temperature and the direct sunlight duration within each environmental monitoring period, generate the environmental temperature Ht and the irradiation duration St, and construct an environmental condition set after summarizing the environmental data within several consecutive environmental monitoring periods;

[0050] Step 102: Construct an environmental abnormality degree Yo from the environmental condition set. Among them, perform linear normalization processing on the environmental temperature Ht and the irradiation duration St in the following way:

[0051]

[0052] Weight coefficient: 0 ≤ F1 ≤ 1, 0 ≤ F2 ≤ 1 and F2 + F1 = 1; i = 1, 2,..., k, where k is the number of monitoring periods; Ht i is the environmental temperature within the i-th monitoring period, Ht avg is the average value of the environmental temperature, St i is the irradiation duration within the i-th monitoring period, St avg is the average value of the irradiation duration;

[0053] Based on historical data and management expectations for the cable usage environment, an abnormality threshold is set in advance; if the obtained environmental abnormality degree Yo exceeds the expectation, that is, the environmental abnormality degree Yo exceeds the abnormality threshold, it indicates that in the current usage environment and usage area, if the cable still maintains its current usage state for a long time, the service life of the cable will be affected to a certain extent. At this time, an alarm instruction is sent to the outside to facilitate timely adjustment of the cable usage environment, and a part of the cables in the current usage area are selected as test samples;

[0054] When in use, combine the content in Steps 101 and 102:

[0055] When the cable is in a continuous use state, especially considering long-term direct sunlight and long-term exposure to a high-humidity environment, its service life and performance will be affected to a greater extent. Therefore, by constructing a corresponding environmental abnormality degree Yo for its usage environmental conditions, and judging whether the current environmental conditions are suitable for the use of the cable based on the environmental abnormality degree Yo. If it is suitable, the cable can continue to work under the current environmental conditions; at this time, by monitoring whether there are abnormalities in the cable usage environment and making adaptive adjustments when there are abnormalities, such as dehumidifying and cooling the area where the cable is located, etc., it can effectively avoid cable aging and extend the service life of the cable.

[0056] Combine the above application and the content in the prior art:

[0057] After the cable is used for a long time, it usually ages gradually by itself. For example, the resistance gradually increases, the voltage loss gradually increases, etc. Therefore, it is necessary to regularly replace or maintain the cable. However, if the cable is in an environment of long-term direct sunlight and relatively high humidity for a long time, the aging degree of the cable may be further accelerated; in the existing cable aging assessment schemes, usually several groups of different test conditions are set for the cable, the cable is tested under different test conditions, and based on the obtained test data, the production of the next batch of cables is adjusted. Therefore, the coverage of the cable aging assessment is relatively low, and these improvements are difficult to form corresponding optimization effects on the current use of the cable.

[0058] Step Two: Conduct performance tests on the test samples, construct a cable performance test data set from the test data, construct a cable quality coefficient Qt from the performance test data set, and judge whether the cable needs to be replaced based on the cable quality coefficient Qt. If it does not need to be replaced, perform maintenance on it;

[0059] The said Step Two includes the following content:

[0060] Step 201, perform a performance test on the selected test sample in the following manner: connect the test sample to the experimental device and turn on the power supply, after setting the test nodes, measure the voltage, current, resistance and temperature of the cable at each test node, and summarize the obtained test data to construct a performance test data set of the cable; wherein the resistance of the cable is usually expressed in ohm / meter (Ω / m);

[0061] Step 202: construct the current cable quality coefficient Qt based on the cable performance test data set, in the following manner: perform linear normalization processing on the cable operating temperature Xt and resistance Xr, in the following manner:

[0062]

[0063] Where i = 1, 2, ..., n, n is the number of test nodes, Xt i is the charging efficiency of the i-th test node, Xr i is the resistance of the i-th test node, the weight coefficient is: 0≤F1≤1, 0≤F2≤1, and F1+F2=1; wherein, the values of the weight coefficient F1 and F2 appearing in the above text can be consistent;

[0064] The quality threshold is set in advance based on the historical usage data of the cable and the management expectations for the cable usage. If the cable quality coefficient Qt is lower than the quality threshold, it means that the quality of the cable during use is poor, which may bring certain safety hazards to subsequent use. At this time, an alarm command is issued to the outside;

[0065] When using the cable, if there is an abnormality in the environment where the cable is located, select some cables as test samples and conduct tests, and build the corresponding cable quality coefficient Qt based on the performance data obtained from the test. Based on the cable quality coefficient Qt, judge whether the cable meets the use requirements, complete a preliminary assessment of cable aging, and confirm whether the cable can continue to be used;

[0066] Step 203: Replace the cable after receiving the alarm command; if no alarm command is received, it means that the cable can still be used, and the current use state is maintained; identify the current use state data of the cable, such as the temperature and voltage when powered on, and obtain the corresponding state characteristics;

[0067] Step 204: obtain a number of cable operation and maintenance plans through online retrieval or offline collection, and construct a post-maintenance plan library after aggregating the cable operation and maintenance plans; match the corresponding operation and maintenance plan for the cable according to the correspondence between the state characteristics and the operation and maintenance plan, and maintain the use of the cable;

[0068] When using, combine the contents in steps 201 and 203:

[0069] When the cable can still be used, it is necessary to maintain the use of the cable. By identifying and obtaining the current status data of the cable, and based on the pre-constructed maintenance plan library, after obtaining the current status characteristics of the cable, a running maintenance plan can be quickly given. By performing running maintenance on the cable, when there is a risk that the cable is already unavailable, after completing the aging assessment of the cable, the service life of the cable can be extended.

[0070] Step 3: Use the cable status prediction model to predict the usage status of the cable. Calculate the aging degree Lo of the cable from the prediction data. If the aging degree Lo exceeds the expectation, corresponding treatment is performed on the cable.

[0071] The said Step 3 includes the following contents:

[0072] Step 301: After maintaining the cable operation, set an observation period; collect the environmental condition data during cable operation, such as light and environmental temperature, and the operation status data of the cable, such as the temperature during operation, etc., to construct a cable usage data set; extract part of the data from the cable usage data set as sample data, and use the sample data to train and obtain a cable status prediction model. During the observation period, use the cable status prediction model to predict the usage status of the cable. At the prediction node, obtain the prediction data of cable usage.

[0073] Step 302: Compare the prediction data of the cable with the standard reference value to obtain the voltage loss value Uu and the resistance increase value Ur when the cable is used at the prediction node, and calculate the aging degree Lo of the cable. Among them, linear normalization is performed on the voltage loss value Uu and the resistance increase value Ur in the following manner:

[0074]

[0075] Weight coefficients: 0 ≤ ρ ≤ 1, 0 ≤ ζ ≤ 1; The weight coefficients can be obtained by referring to the analytic hierarchy process.

[0076] According to historical data and the management expectation of cable quality, an aging threshold is set in advance; if the aging degree Lo exceeds the expectation, that is, the obtained aging degree Lo exceeds the aging threshold, it means that the aging degree of the cable is relatively serious and the remaining service life is short. After the observation period ends, corresponding maintenance or replacement measures are taken.

[0077] When in use, combine the contents in Steps 301 and 302:

[0078] After implementing the operation and maintenance plan, the operating status of the cable is predicted through the constructed cable status prediction model, and the prediction data is compared with the standard data. Thus, the aging degree of the cable is constructed after maintenance, and the cable is aged again. evaluated, and based on this, the next aging degree of the cable is judged. If the cable is about to age, further in-depth maintenance or direct replacement is required to ensure the safety of cable use.

[0079] Step 4: Through accelerated aging tests, construct the corresponding aging degree Lo from the cable performance data under different test conditions, and construct the condition influence degree after linear regression analysis. If the condition influence degree exceeds the expectation, output an optimized cable usage plan to optimize cable usage;

[0080] Step 4 includes the following content:

[0081] Step 401: Use an unused cable as a standard sample, set several groups of different test conditions for the standard sample. The test conditions include: environmental conditions: environmental temperature, environmental humidity, sunlight direct irradiation, etc.; working conditions: voltage, current, etc. when powered on. Under different test conditions, conduct accelerated aging tests on the standard sample, obtain the cable performance detection data under different test conditions, and summarize to construct a test performance test set;

[0082] Step 402: Obtain several groups of aging degrees Lo from the test performance test set. Use the test conditions as independent variables and the aging degree Lo as the dependent variable to conduct linear regression analysis and construct the corresponding linear regression equation. Use the regression coefficient corresponding to the independent variable in the linear regression equation as the influence factor;

[0083] When in use, after selecting several test conditions, conduct regression analysis based on the test data and obtain the corresponding influence factors. Thus, based on each influence factor, it is possible to judge the influence degree of different independent variables on cable aging. If the influence degree is relatively high, it can be used as a target feature for targeted processing to narrow the optimization range and improve the efficiency when delaying cable aging.

[0084] Step 403: Determine the corresponding weight coefficient for each independent variable according to the analytic hierarchy process, obtain the product of the influence factor and the weight coefficient, sum up the products to construct the condition influence degree. According to historical data and the management expectation of cable quality, preset the influence degree threshold. If the condition influence degree exceeds the influence degree threshold, it means that when the cable is actually used under the currently selected test conditions, there will be a situation of accelerated aging. At this time, send an optimization instruction to the outside;

[0085] During use, if there are multiple influencing factors, a conditional influence degree is constructed overall to determine whether the cable aging is due to its own quality problems or poor environmental conditions and actual use conditions. After determining that the cable aging is accelerated due to environmental conditions and use conditions, corresponding treatment can be carried out.

[0086] Step 404: After receiving the optimization instruction, collect the environmental conditions and working conditions of the test sample, and obtain the corresponding usage data; after setting the optimization criteria, identify the current usage data of the cable to determine the corresponding optimization features; construct a cable optimization knowledge graph with the cable usage optimization as the target word, and based on the correspondence between the cable usage optimization plan and the optimization features, give an optimization plan for the cable usage of the test sample to extend the service life of the cable.

[0087] During use, combine the content in Steps 401 to 404:

[0088] After identifying the current working environment and working condition data of the cable, obtain several optimization features. The cable optimization knowledge graph gives an optimization plan, and the cable usage is optimized according to the optimization plan. Thus, when it is not necessary to replace the cable temporarily, the service life of the cable can be improved by optimizing and improving the working environment and working state of the cable. Therefore, after repeatedly completing the aging assessment of the cable, corresponding improvement plans can be given according to the assessment results to specifically improve the deficiencies in the cable usage.

[0089] Please refer to Figure 2 , the present invention provides a cable damage and aging safety assessment system, including:

[0090] An environmental analysis unit monitors the usage environment data of the cable and constructs an environmental condition set, constructs an environmental abnormality degree Yo from the environmental condition set. If the obtained environmental abnormality degree Yo exceeds the expectation, an alarm instruction is issued and some cables are selected as test samples.

[0091] A performance evaluation unit performs a performance test on the test sample, constructs a cable performance test data set from the test data, constructs a cable quality coefficient Qt from the performance test data set, and determines whether the cable needs to be replaced according to the cable quality coefficient Qt. If it does not need to be replaced, it is maintained.

[0092] An aging prediction unit uses a cable state prediction model to predict the usage state of the cable, calculates the aging degree Lo of the cable from the prediction data. If the aging degree Lo exceeds the expectation, corresponding treatment is carried out on the cable.

[0093] The maintenance unit constructs the corresponding aging degree Lo based on the cable performance data under different test conditions through accelerated aging tests, and constructs the condition influence degree after linear regression analysis. If the condition influence degree exceeds the expectation, it outputs an optimized cable usage plan to optimize the cable usage.

[0094] It should be noted that the analytic hierarchy process is an analytical method that combines qualitative and quantitative methods. It can decompose complex problems into multiple levels. By comparing the importance of factors at each level, it can help decision-makers make decisions on complex problems and determine the final decision-making plan. In this process, the analytic hierarchy process can be used to determine the weight coefficients of these indicators.

[0095] The construction of the cable optimization knowledge graph is a systematic project, involving multiple levels and steps, including:

[0096] Requirement analysis and goal setting: First, clarify the purpose and requirements for constructing the cable optimization knowledge graph, such as improving cable performance, optimizing cable design, reducing cable failure rates, etc. According to the goal setting, determine the content and scope that the knowledge graph needs to cover.

[0097] Data source collection and processing: Obtain cable-related data through data sources such as crawlers and internal CPs, including the structure, materials, manufacturing processes, performance parameters, application scenarios, etc. of the cable. This data may come from cable manufacturers, research institutions, industry reports, etc. Clean and organize the collected data to ensure the accuracy and consistency of the data.

[0098] Entity recognition and relationship extraction: In the cable optimization knowledge graph, entities may include cable types, materials, processes, performance parameters, etc., and relationships describe the interactions and influences between these entities. Use natural language processing (NLP) technologies, such as named entity recognition (NER) and relationship extraction technologies, to extract cable-related entities and relationships from text data.

[0099] Knowledge graph construction: Based on the extracted entities and relationships, construct the cable optimization knowledge graph. This can be achieved through technologies such as graph databases or knowledge representation learning. During the construction process, it is necessary to consider the structure of the graph, the representation methods of nodes and edges, as well as the query and reasoning capabilities of the graph.

[0100] Knowledge graph optimization and evaluation: Optimize and evaluate the constructed knowledge graph. Optimization may include adding new entities and relationships, correcting incorrect information, improving the structure of the graph, etc. Evaluation can be carried out by comparing the actual data with the data in the knowledge graph, analyzing the coverage and accuracy of the graph, etc.

[0101] Application Development and Integration: Develop applications based on the cable optimization knowledge graph according to requirements, such as cable performance prediction, design optimization suggestions, fault warning, etc. Integrate the knowledge graph with existing systems to achieve data sharing and interoperability.

[0102] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0103] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0104] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be repeated here.

[0105] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only for some logical function divisions. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0106] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0107] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0108] If the above functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0109] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0110] As described above, this is only a specific implementation manner of the present application. However, the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily conceive of changes or substitutions, which should all be covered within the protection scope of the present application.

Claims

1. A method for evaluating the safety of cable damage and aging, characterized in that: including monitoring the usage environment data of the cable and constructing an environmental condition set, constructing an environmental anomaly degree Yo from the environmental condition set, if the obtained environmental anomaly degree Yo exceeds the expectation, issuing an alarm instruction and selecting some cables as test samples conducting performance tests on the test samples, constructing a cable performance test data set from the test data, constructing a cable quality coefficient Qt from the performance test data set, judging whether the cable needs to be replaced according to the cable quality coefficient Qt, if it does not need to be replaced, maintaining it using a cable status prediction model to predict the usage status of the cable, calculating the aging degree Lo of the cable from the prediction data, if the aging degree Lo exceeds the expectation, performing corresponding processing on the cable; among them, the method for calculating the aging degree Lo of the cable is as follows: performing linear normalization processing on the voltage loss value Uu and the resistance increase value Ur, in the following way weight coefficient: 0 ≤ ρ ≤ 1, 0 ≤ ζ ≤ 1 through accelerated aging tests, constructing the corresponding aging degree Lo from the cable performance data under different test conditions, and constructing a condition influence degree after linear regression analysis, if the condition influence degree exceeds the expectation, outputting an optimized cable usage plan to optimize the cable usage 2. A method for evaluating the safety of cable damage and aging according to claim 1, characterized in that monitoring the temperature and sunlight irradiation in the area where the cable is located during the environmental monitoring period; generating the environmental temperature Ht and the irradiation duration St, summarizing the environmental data in several consecutive environmental monitoring periods to construct an environmental condition set, and constructing an environmental anomaly degree Yo from the environmental condition set 3. A method for evaluating the safety of cable damage and aging according to claim 2, characterized in that the generation method of the environmental anomaly degree Yo is as follows: performing linear normalization processing on the environmental temperature Ht and the irradiation duration St, where Weight coefficients: 0 ≤ F1 ≤ 1, 0 ≤ F2 ≤ 1 and F2 + F1 = 1; i = 1, 2, …, k, where k is the number of monitoring periods; Ht i is the environmental temperature in the i-th monitoring period, Ht avg is the average value of the environmental temperature, St i is the irradiation duration in the i-th monitoring period, St avg is the average value of the irradiation duration.

4. A method for evaluating the safety of cable damage and aging according to claim 3, characterized in that performing performance tests on the selected test samples, summarizing the obtained test data to construct a cable performance test data set; constructing the current cable quality coefficient Qt according to the cable performance test data set, if the cable quality coefficient Qt is lower than the quality threshold, sending an alarm instruction to the outside 5. A method for evaluating the safety of cable damage and aging according to claim 4, characterized in that the acquisition method of the cable quality coefficient Qt is as follows: performing linear normalization processing on the operating temperature Xt and the resistance Xr of the cable, in the following way where \(i = 1, 2, \ldots, n\), \(n\) is the number of test nodes, \(X_t\) i is the charging efficiency of the \(i\)-th test node, \(X_r\) i is the resistance of the \(i\)-th test node, weight coefficients: \(0 \leq F_1 \leq 1\), \(0 \leq F_2 \leq 1\), and \(F_1 + F_2 = 1\).

6. A method for evaluating the safety of cable damage and aging according to claim 5, characterized in that replacing the cable after receiving the alarm instruction, if the alarm instruction is not received, continuing to maintain the current usage status; identifying the current usage status data of the cable to obtain the corresponding status features obtaining several cable operation and maintenance plans, summarizing the cable operation and maintenance plans to construct a maintenance plan library; matching the corresponding operation and maintenance plan for the cable according to the correspondence between the status features and the operation and maintenance plans, and maintaining the usage of the cable 7. The method for evaluating the safety of cable damage and aging according to claim 6, wherein: After maintaining the cable operation, train to obtain a cable status prediction model. During the observation period, use the cable status prediction model to predict the usage status of the cable. At the prediction node, obtain the predicted data of the cable usage; compare the predicted data of the cable with the standard reference value, obtain the voltage loss value Uu and the resistance increase value Ur when the cable is used at the prediction node, calculate the aging degree Lo. If the aging degree Lo exceeds the expectation, after the observation period ends, take corresponding maintenance or replacement measures.

8. The method for evaluating the safety of cable damage and aging according to claim 1, wherein: Take an unused cable as a standard sample, set several groups of different test conditions for the standard sample, and conduct accelerated aging tests on the standard sample under different test conditions to obtain the cable performance detection data under different test conditions. After summarizing, construct a test performance test set; Obtain several groups of aging degrees Lo from the test performance test set. Take the test conditions as independent variables and the aging degree Lo as the dependent variable, conduct linear regression analysis and construct the corresponding linear regression equation, and use the regression coefficient corresponding to the independent variable in the linear regression equation as the influencing factor.

9. The method for evaluating the safety of cable damage and aging according to claim 8, wherein: Determine the corresponding weight coefficient for each independent variable according to the analytic hierarchy process, obtain the product of the influencing factor and the weight coefficient, sum up the products to construct the conditional influence degree. If the conditional influence degree exceeds the influence degree threshold, collect the environmental conditions and working conditions of the test sample and obtain the corresponding usage data; Identify the current usage data of the cable, determine the corresponding optimization features, construct a cable optimization knowledge graph with the cable usage optimization as the target word. According to the correspondence between the cable usage optimization plan and the optimization features, give the cable usage optimization plan for the test sample to extend the service life of the cable.

10. A cable damage and aging safety assessment system, characterized in that: Including: An environmental analysis unit that monitors the usage environment data of the cable and constructs an environmental condition set, constructs an environmental anomaly degree Yo from the environmental condition set. If the obtained environmental anomaly degree Yo exceeds the expectation, issue an alarm instruction and select some cables as test samples; A performance evaluation unit that conducts performance tests on the test samples, constructs a cable performance test data set from the test data, constructs a cable quality coefficient Qt from the performance test data set, and determines whether the cable needs to be replaced according to the cable quality coefficient Qt. If it does not need to be replaced, perform maintenance on it; An aging prediction unit that uses the cable status prediction model to predict the usage status of the cable, calculates the aging degree Lo of the cable from the predicted data. If the aging degree Lo exceeds the expectation, perform corresponding processing on the cable; A maintenance unit that constructs the corresponding aging degree Lo from the cable performance data under different test conditions through accelerated aging tests, and constructs the conditional influence degree after linear regression analysis. If the conditional influence degree exceeds the expectation, output the cable usage optimization plan to optimize the cable usage.

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