A Modular Cable Status Sensing Method and System

Abstract

The present invention relates to a modular cable status perception method and system, belonging to the field of cable status monitoring, including: verifying the vibration influence of adjacent cable modules based on multiple vibration parameter sequences to obtain multiple vibration perception accuracy parameters; analyzing the contact influence based on multiple vibration parameter sequences to obtain multiple contact influence parameters; performing electrical influence verification based on multiple electrical parameter sequences and multiple contact influence parameters to obtain multiple electrical perception accuracy parameters, and combining multiple vibration perception accuracy parameters to calculate and obtain multiple perception accuracy parameters, and generating a status perception result. Through the present invention, the technical problem that the traditional method lacks comprehensive analysis and accuracy verification of different types of monitoring data, resulting in the inability to effectively identify the accuracy of the monitoring data and causing insufficient accuracy and reliability in cable status judgment can be solved; the rationality of vibration and electrical data can be verified in real time, and comprehensive and accurate cable status perception can be realized.

Description

Technical Field

[0001] The present invention relates to the field of cable condition monitoring, and particularly to a modular cable condition sensing method and system. Background Art

[0002] As an important carrier for power transmission, the reliability of the operating state of cables is crucial for the stability of the entire power grid. During the long-term operation of cables, they may be affected by various factors such as mechanical vibration, current impact, and aging, resulting in problems such as loose cable joints, increased contact resistance, and decreased insulation performance. Eventually, cable failures may be triggered, affecting power supply safety.

[0003] Due to the influence of factors such as environmental noise and electromagnetic interference during the cable monitoring process, the data collected by sensors may be biased or inaccurate, resulting in poor reliability of the monitoring results. Existing methods lack cross-validation and accuracy evaluation of different types of monitoring data, making it difficult to effectively identify the accuracy of the monitoring data, resulting in insufficient precision and reliability in cable condition judgment. Summary of the Invention

[0004] Aiming at the technical problem that traditional cable condition sensing methods lack comprehensive analysis and accuracy verification of different types of monitoring data, resulting in the inability to effectively identify the accuracy of the monitoring data and insufficient precision and reliability in cable condition judgment, the present invention provides a modular cable condition sensing method and system to solve this problem.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] In a first aspect, the present invention provides a modular cable condition sensing method, including: performing vibration monitoring and electrical monitoring on a plurality of connected cable modules to obtain a plurality of vibration parameter sequences and a plurality of electrical parameter sequences; performing vibration influence verification on adjacent cable modules according to the plurality of vibration parameter sequences to obtain a plurality of vibration sensing accuracy parameters; performing contact influence analysis on the plurality of cable modules according to the plurality of vibration parameter sequences to obtain a plurality of contact influence parameters; performing electrical influence verification according to the plurality of electrical parameter sequences and the plurality of contact influence parameters to obtain a plurality of electrical sensing accuracy parameters, and combining the plurality of vibration sensing accuracy parameters to calculate a plurality of sensing accuracy parameters and generate a state sensing result.

[0007] Preferably, the modular cable condition sensing method further includes: dividing a plurality of cable segments connected by cable joints to obtain a plurality of cable modules; monitoring and obtaining vibration parameters and electrical parameters within a recently preset time range through vibration sensors and electrical sensors arranged on the plurality of cable modules; arranging the monitored vibration parameters and electrical parameters in chronological order to obtain a plurality of vibration parameter sequences and a plurality of electrical parameter sequences.

[0008] Preferably, the modular cable status sensing method further includes: extracting amplitude parameters within the multiple vibration parameter sequences to obtain multiple amplitude parameter arrays; extracting the maximum amplitude parameters within the multiple amplitude parameter arrays to obtain multiple maximum amplitude parameters; based on the multiple maximum amplitude parameters, performing amplitude parameter mapping of adjacent cable modules to obtain multiple adjacent amplitude parameter intervals; retrieving multiple groups of adjacent maximum amplitude parameters of the cable modules adjacent to each cable module, calculating the deviation amplitude from the corresponding adjacent amplitude parameter intervals, and calculating to obtain multiple vibration sensing accuracy parameters, where the deviation amplitude is negatively correlated with the vibration sensing accuracy parameters.

[0009] Preferably, the modular cable status sensing method further includes: obtaining the vibration monitoring data of the multiple cable modules within a historical time, and extracting multiple historical amplitude parameter sets of the multiple cable modules; clustering the same historical amplitude parameters of the same cable module within the multiple historical amplitude parameter sets to obtain multiple same amplitude parameter sets; extracting the amplitude parameter ranges of the adjacent cable modules when each same amplitude parameter of each cable module appears as the amplitude parameter intervals to obtain multiple amplitude parameter interval sets; using the multiple same amplitude parameter sets and multiple amplitude parameter interval sets to construct an adjacent amplitude interval mapping table; inputting the multiple maximum amplitude parameters into the adjacent amplitude interval mapping table to map and obtain multiple adjacent amplitude parameter intervals.

[0010] Preferably, the modular cable status sensing method further includes: training a contact influence analyzer based on the cable joint vibration influence monitoring data within a historical time; inputting the multiple vibration parameter sequences into the contact influence analyzer respectively, and predicting and outputting to obtain multiple contact influence parameters.

[0011] Preferably, the modular cable status sensing method further includes: according to the cable joint vibration influence monitoring data within a historical time, collecting a sample amplitude parameter sequence set, and collecting the change amount of the cable joint contact resistance after different sample amplitude parameter sequences as a sample contact influence parameter set; using the sample amplitude parameter sequence set and the sample contact influence parameter set, and using machine learning to perform supervised training of the contact influence analyzer and training until convergence to obtain the contact influence analyzer.

[0012] Preferably, the modular cable status perception method further includes: obtaining multiple contact resistances recently recorded by the multiple cable modules, combining the multiple contact influence parameters, calculating to obtain multiple perceived contact resistances, and calculating to obtain multiple cumulative contact resistances according to the connection sequence of the multiple cable modules; obtaining preset electrical parameters of the multiple cable modules, combining the multiple cumulative contact resistances, and calculating to obtain multiple predicted electrical parameters of the multiple cable modules; respectively calculating the cumulative deviation magnitudes between the multiple electrical parameter sequences and the multiple predicted electrical parameters, and calculating to obtain multiple electrical perception accuracy parameters, as shown in the following formula: ; where is the electrical perception accuracy parameter, N is the number of electrical parameters in the electrical parameter sequence, is the i-th electrical parameter in the electrical parameter sequence, is the predicted electrical parameter; according to the multiple electrical perception accuracy parameters and multiple vibration perception accuracy parameters, calculating to obtain multiple perception accuracy parameters, and combining the multiple vibration parameter sequences and multiple electrical parameter sequences to generate a cable status perception result.

[0013] In a second aspect, the present invention provides a modular cable status perception system, including: a cable module monitoring unit for performing vibration monitoring and electrical monitoring on multiple connected cable modules to obtain multiple vibration parameter sequences and multiple electrical parameter sequences; a vibration influence verification unit for performing vibration influence verification on adjacent cable modules according to the multiple vibration parameter sequences to obtain multiple vibration perception accuracy parameters; a contact influence analysis unit for performing contact influence analysis on the multiple cable modules according to the multiple vibration parameter sequences to obtain multiple contact influence parameters; a status perception result generation unit for performing electrical influence verification according to the multiple electrical parameter sequences and multiple contact influence parameters to obtain multiple electrical perception accuracy parameters, combining the multiple vibration perception accuracy parameters, calculating to obtain multiple perception accuracy parameters, and generating a status perception result.

[0014] The beneficial effects of the present invention are as follows: By performing vibration monitoring and electrical monitoring on multiple connected cable modules, multiple vibration parameter sequences and multiple electrical parameter sequences are obtained; then, vibration influence verification of adjacent cable modules is performed based on the multiple vibration parameter sequences to obtain multiple vibration perception accuracy parameters; on the other hand, contact influence analysis of the multiple cable modules is performed according to the multiple vibration parameter sequences to obtain multiple contact influence parameters; further, electrical influence verification is performed based on the multiple electrical parameter sequences and multiple contact influence parameters to obtain multiple electrical perception accuracy parameters; finally, multiple perception accuracy parameters are calculated based on the multiple electrical perception accuracy parameters and multiple vibration perception accuracy parameters, and a cable state perception result is generated by combining the multiple vibration parameter sequences and multiple electrical parameter sequences. That is to say, by combining multi-dimensional monitoring data and using a fusion algorithm to evaluate the accuracy of the monitoring results, the rationality of vibration and electrical data can be verified in real time, comprehensive and accurate cable state perception can be achieved, providing a reliable reference basis for subsequent cable maintenance, and thus improving the safety and stability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic flow chart of a modular cable state perception method provided by the present invention;

[0016] Figure 2 It is a schematic structural diagram of a modular cable state perception system provided by the present invention.

[0017] In the drawings, the components represented by the reference numerals are described as follows:

[0018] Cable module monitoring unit 11, vibration influence verification unit 12, contact influence analysis unit 13, state perception result generation unit 14. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. 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 skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0020] In the description of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the described features. In the description of the present invention, "multiple" means two or more, unless otherwise specifically defined.

[0021] In the description of the present invention, the term "for example" is used to mean "serving as an example, illustration, or explanation". Any embodiment described as "for example" in the present invention is not necessarily construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to implement and use the present invention. In the following description, details are set forth for purposes of explanation. It should be understood that those of ordinary skill in the art can recognize that the present invention can be implemented without the use of these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

[0022] Embodiment 1, as Figure 1 shown, the embodiment of the present invention provides a modular cable status perception method, which specifically includes the following steps:

[0023] S100: Perform vibration monitoring and electrical monitoring on a plurality of connected cable modules to obtain a plurality of vibration parameter sequences and a plurality of electrical parameter sequences.

[0024] Further, step S100 of the present invention further includes:

[0025] S110: Divide a plurality of cable segments connected by cable joints to obtain a plurality of cable modules; S120: Monitor and acquire vibration parameters and electrical parameters within a recently preset time range through vibration sensors and electrical sensors arranged on the plurality of cable modules; S130: Arrange the monitored vibration parameters and electrical parameters in chronological order to obtain a plurality of vibration parameter sequences and a plurality of electrical parameter sequences.

[0026] Specifically, first, according to the positions of the cable joints and the structural characteristics of the cables, the cable system is divided into a plurality of cable modules as required. Each module corresponds to an independent cable connection part and has a clear monitoring boundary. Among them, each cable module can be monitored in real time by arranging a plurality of sensors (such as vibration sensors and electrical sensors) on it to ensure that the status information of the module can be accurately obtained.

[0027] Next, vibration sensors installed on the multiple cable modules are used to monitor the vibration parameters of the multiple cable modules within a recently preset time range (such as the most recent 10 minutes). The vibration parameters include amplitude, etc.; electrical sensors installed on the multiple cable modules are used to monitor the electrical parameters of the multiple cable modules in real time within a recently preset time range (such as the most recent 10 minutes). The electrical parameters include resistance, etc. Then, according to the monitored timestamps, the monitored vibration parameters and electrical parameters are arranged in ascending order of monitoring sequence from early to late, obtaining multiple vibration parameter sequences and multiple electrical parameter sequences. Among them, each vibration parameter sequence represents the vibration state of the cable module within a certain specific time period, and each electrical parameter sequence represents the electrical performance of the cable module within a certain specific time period. Through the collection of vibration and electrical data of multiple cable modules, the health status of the cable can be comprehensively and real-time monitored, and changes in the cable state can be identified.

[0028] S200: Verify the vibration influence of adjacent cable modules according to the multiple vibration parameter sequences, and obtain multiple vibration perception accuracy parameters.

[0029] Furthermore, step S200 of the present invention further includes:

[0030] S210: Extract the amplitude parameters within the multiple vibration parameter sequences to obtain multiple amplitude parameter arrays; S220: Extract the maximum amplitude parameters within the multiple amplitude parameter arrays to obtain multiple maximum amplitude parameters.

[0031] Specifically, extract the amplitude parameters of multiple cable modules in the multiple vibration parameter sequences at the same monitored timestamp, and arrange the multiple amplitude parameters at the same monitored timestamp according to the position coordinates of the cable modules. That is, for the multiple amplitude parameters collected at the same timestamp, they need to be arranged according to the physical position coordinates of the cable modules because the position of the cable module in physical space has different effects on the propagation of vibration influence; then combine the multiple amplitude parameters arranged according to the position coordinates together to form an amplitude parameter array. Each amplitude parameter array contains the amplitude information of multiple cable modules at the same timestamp. For a given monitored timestamp, the array composed of the amplitude parameters of the cable modules can completely reflect the vibration state of each cable module at that moment. Use the same method to obtain multiple amplitude parameter arrays at multiple monitored timestamps in turn. Then extract the maximum amplitude parameter of each amplitude parameter array in the multiple amplitude parameter arrays. This represents the module with the maximum vibration intensity among all cable modules at this timestamp, and obtain multiple maximum amplitude parameters.

[0032] S230: Perform amplitude parameter mapping of adjacent cable modules according to the multiple maximum amplitude parameters to obtain multiple adjacent amplitude parameter intervals.

[0033] Further, step S230 of the present invention further includes:

[0034] S231: Obtain the vibration monitoring data of the multiple cable modules within a historical time, and extract multiple historical amplitude parameter sets of the multiple cable modules; S232: Cluster the same historical amplitude parameters of the same cable module within the multiple historical amplitude parameter sets to obtain multiple sets of the same amplitude parameters; S233: Extract the amplitude parameter ranges of adjacent cable modules when each same amplitude parameter of each cable module appears, as amplitude parameter intervals, to obtain multiple sets of amplitude parameter intervals; S234: Use the multiple sets of the same amplitude parameters and the multiple sets of amplitude parameter intervals to construct an adjacent amplitude interval mapping table; S235: Input the multiple maximum amplitude parameters into the adjacent amplitude interval mapping table, and map to obtain multiple adjacent amplitude parameter intervals.

[0035] Specifically, first, obtain the vibration monitoring data of the multiple cable modules within a historical time (such as the most recent half year), and these historical data include all vibration parameters within the past time period; then, extract the parameters related to the amplitude from the historical vibration monitoring data to obtain multiple historical amplitude parameter sets of the multiple cable modules, and each historical amplitude parameter set represents the amplitude change of a specific cable module within the historical time. Next, cluster the same historical amplitude parameters of the same cable module within the multiple historical amplitude parameter sets, that is, group the same historical amplitude parameters of the same cable module into one group, set as the same amplitude parameter, to obtain multiple sets of the same amplitude parameters, and each set of the same amplitude parameters contains multiple same amplitude parameters of a specific cable module within the historical time period.

[0036] Then, extract the multiple adjacent amplitude parameters of adjacent cable modules when each identical amplitude parameter of each cable module appears, and extract the minimum adjacent amplitude parameter and the maximum adjacent amplitude parameter among the multiple adjacent amplitude parameters. Set the amplitude parameter range according to the minimum adjacent amplitude parameter and the maximum adjacent amplitude parameter as the amplitude parameter interval, and sequentially analyze to obtain multiple sets of amplitude parameter intervals for multiple cable modules. Next, use the multiple sets of identical amplitude parameters and multiple sets of amplitude parameter intervals to construct an adjacent amplitude interval mapping table. The main purpose of this mapping table is to find and map the amplitude parameter interval of the adjacent cable module related to it according to the amplitude parameter of a specific cable module. Among them, each set of identical amplitude parameters contains the monitoring data of multiple cable modules under the same amplitude condition. By matching with multiple sets of amplitude parameter intervals, find the amplitude intervals adjacent in time and space for these parameters. For example, if the amplitude parameter of a certain cable module is the maximum amplitude parameter, the mapping table will help find the amplitude interval range of this maximum amplitude parameter in the adjacent cable module. Finally, input the multiple maximum amplitude parameters into the adjacent amplitude interval mapping table for mapping and matching. Each maximum amplitude parameter will be mapped to the amplitude interval of the adjacent cable module according to its association with the adjacent cable module, and multiple adjacent amplitude parameter intervals will be obtained. For example, if the maximum amplitude parameter of a certain cable module is A, then find the adjacent amplitude parameter interval range related to A through the mapping table. In this way, it can ensure that the mutual relationship between the amplitude parameters of each cable module is accurately reflected and the overall consistency of the cable module state perception is guaranteed.

[0037] By constructing the adjacent amplitude interval mapping table, the vibration information between multiple cable modules in the cable system can be effectively fused, the connection between each amplitude parameter and the vibration behavior of its adjacent module can be clarified, and thus a more accurate vibration state perception can be obtained.

[0038] S240: Retrieve multiple groups of adjacent maximum amplitude parameters of the cable modules adjacent to each cable module, calculate the deviation amplitude from the corresponding adjacent amplitude parameter interval, and calculate to obtain multiple vibration perception accuracy parameters, where the deviation amplitude is negatively correlated with the vibration perception accuracy parameter.

[0039] Specifically, multiple groups of adjacent maximum amplitude parameters of adjacent cable modules are retrieved, and the adjacent amplitude parameter interval corresponding to the cable module is obtained. Then, for each group of adjacent amplitude parameters, the deviation amplitude from the corresponding adjacent amplitude parameter interval is calculated. The deviation amplitude refers to the ratio of the absolute value of the difference between each group of adjacent amplitude parameters and the median value of the adjacent amplitude parameter interval to the median value of the adjacent amplitude parameter interval. For example, assume the adjacent amplitude parameter is 0.8 mm, the adjacent amplitude parameter interval is from 0.6 mm to 1.4 mm, then the median value of the adjacent amplitude parameter interval is 1 mm, and the deviation amplitude is (1 - 0.8) / 1 = 0.2, that is, 20%. Multiple deviation amplitudes of multiple cable modules are obtained, and 1 is subtracted from each of the multiple deviation amplitudes respectively, and the difference between the two is used as the vibration perception accuracy parameter, obtaining multiple vibration perception accuracy parameters of multiple cable modules. These vibration perception accuracy parameters provide a reliable reference basis for subsequent cable state perception and maintenance, and can accurately reflect the reliability of the vibration monitoring results of each cable module.

[0040] S300: According to the multiple vibration parameter sequences, perform contact influence analysis on the multiple cable modules to obtain multiple contact influence parameters.

[0041] Furthermore, step S300 of the present invention further includes:

[0042] S310: Train a contact influence analyzer according to the cable joint vibration influence monitoring data within a historical time.

[0043] Furthermore, step S310 of the present invention further includes:

[0044] S311: According to the cable joint vibration influence monitoring data within a historical time, collect a set of sample amplitude parameter sequences, and collect the change in the contact resistance of the cable joint after different sample amplitude parameter sequences as a set of sample contact influence parameters; S312: Use the set of sample amplitude parameter sequences and the set of sample contact influence parameters, and through machine learning, perform supervised training on the contact influence analyzer until convergence to obtain the contact influence analyzer.

[0045] Specifically, cable joints are usually connected by bolts, welding, etc. However, during long-term operation, vibration will cause mechanical fatigue and displacement, which will further lead to the loosening of the cable joints. After the cable joints are loosened, the contact pressure between the contact surfaces decreases, resulting in incomplete contact between the contact surfaces. In this way, the path of the current passing through the joint will be blocked, and the contact resistance will increase accordingly, which means that the resistance of the current flowing through the joint increases, causing energy loss and temperature rise.

[0046] First, according to the cable joint vibration impact monitoring data within a historical time period (such as the most recent month), the amplitude parameter sequences of multiple sample cable modules are collected. These amplitude parameters reflect the vibration conditions of the cable joint at different time periods, and a set of sample amplitude parameter sequences is obtained. Then, the change in the contact resistance of the cable joint after collecting different sample amplitude parameter sequences is measured, which is set as the sample contact impact parameter. That is, after each sample amplitude parameter sequence, the change in the contact resistance of the cable joint is recorded. The change in the contact resistance is due to the poor contact of the cable joint caused by vibration, which in turn affects the electrical transmission performance. The change in the contact resistance can be obtained by actually measuring electrical parameters (such as current, voltage) and contact resistance sensors; a set of sample contact impact parameters is obtained, where the sample amplitude parameter sequences and the sample contact impact parameters correspond one by one.

[0047] Next, a contact impact analyzer is constructed based on machine learning. For example, a contact impact analyzer is constructed based on a BP neural network. Among them, the contact impact analyzer is a BP neural network model in machine learning that can be iteratively optimized, including an input layer, multiple hidden layers, and an output layer. The input data of its input layer is the amplitude parameter sequence, and the output data of the output layer is the contact impact parameter. Then, using the sample amplitude parameter sequences as the input and the sample contact impact parameters as the supervision, the set of sample amplitude parameter sequences and the set of sample contact impact parameters are used as training data to perform supervised training on the contact impact analyzer. During the training process, first, the weights and biases of the neural network are randomly initialized, usually using small random values to avoid the network being overly dependent on the initial conditions; then, each group of sample amplitude parameter sequences is input into the input layer of the neural network. For each hidden layer, the input data is multiplied by the weight matrix, the bias is added, and after passing through an activation function (such as ReLU), it is passed to the next layer, and the output of the hidden layer is passed to the output layer to obtain the predicted contact impact parameter (the change in the contact resistance); then, the predicted contact impact parameter is compared with the actual contact impact parameter, and the loss function is calculated. Usually, the mean square error is used as the loss function. The loss function measures the prediction accuracy of the model, and the smaller the value, the better the prediction effect of the model. Further, the chain rule is used to calculate the gradients of each network weight and bias. The backpropagation algorithm calculates the gradients according to the partial derivatives of the loss function with respect to each weight and bias, propagating from the output layer to the input layer. According to the calculated gradients, an optimization algorithm (such as gradient descent or Adam optimizer) is used to update the weights and biases of the neural network. The entire process is trained through multiple iterations. Each iteration gradually optimizes the model through the processes of forward propagation, loss calculation, backpropagation, and parameter update until the loss function converges, and a trained contact impact analyzer is obtained.

[0048] Through multiple iterations of training, gradually optimize the prediction ability of the contact impact analyzer, enabling it to accurately predict the change in contact resistance caused by vibration and provide a reliable reference for cable maintenance.

[0049] S320: Input the multiple vibration parameter sequences into the contact impact analyzer respectively, and obtain multiple contact impact parameters through prediction output.

[0050] Specifically, finally input the multiple vibration parameter sequences into the contact impact analyzer for prediction. The input vibration parameter sequences will pass through each layer of the neural network, undergo operations such as weighted summation and activation function processing, and be transmitted layer by layer. Finally, contact impact parameters are output. The contact impact parameters are the change amounts of contact resistance predicted based on the input vibration data, and multiple contact impact parameters are obtained.

[0051] S400: Perform electrical impact verification based on the multiple electrical parameter sequences and multiple contact impact parameters to obtain multiple electrical perception accuracy parameters. Combine the multiple vibration perception accuracy parameters, calculate to obtain multiple perception accuracy parameters, and generate a status perception result.

[0052] Furthermore, step S400 of the present invention further includes:

[0053] S410: Obtain the multiple contact resistances recently recorded by the multiple cable modules, combine the multiple contact impact parameters, calculate to obtain multiple perceived contact resistances, and calculate to obtain multiple cumulative contact resistances according to the connection order of the multiple cable modules; S420: Obtain the preset electrical parameters of the multiple cable modules, combine the multiple cumulative contact resistances, and calculate to obtain the multiple predicted electrical parameters of the multiple cable modules; S430: Calculate the cumulative deviation magnitudes between the multiple electrical parameter sequences and the multiple predicted electrical parameters respectively, and calculate to obtain multiple electrical perception accuracy parameters, as shown in the following formula: ; where is the electrical perception accuracy parameter, N is the number of electrical parameters in the electrical parameter sequence, is the i-th electrical parameter in the electrical parameter sequence, is the predicted electrical parameter; S440: Calculate to obtain multiple perception accuracy parameters based on the multiple electrical perception accuracy parameters and multiple vibration perception accuracy parameters, combine the multiple vibration parameter sequences and multiple electrical parameter sequences, and generate a cable status perception result.

[0054] Specifically, first, obtain the multiple contact resistances recently recorded for the multiple cable modules, that is, obtain the most recently recorded contact resistance for each cable module. These contact resistance values are usually obtained based on historical monitoring data or a real-time sensing system. Then, map and sum the multiple contact resistances and the multiple contact influence parameters, that is, sum the contact resistance and the contact influence parameter for each cable module, and use the sum as the sensed contact resistance to obtain multiple sensed contact resistances. Next, calculate the cumulative contact resistance for each cable module. The cumulative contact resistance reflects the influence of the cumulative contact resistance on the electrical signal when passing through the multiple cable modules. The first cable module is only affected by its own contact resistance. The second cable module is affected by its own contact resistance and the contact resistance of the first cable module, and so on. That is, in the order of each cable module, sum up the contact resistances of all the previously connected cable modules as the cumulative contact resistance of this cable module. Calculate the multiple cumulative contact resistances of the multiple cable modules in sequence.

[0055] Next, obtain the preset electrical parameters of the multiple cable modules. The preset electrical parameters are usually set during cable installation and commissioning, representing the electrical transmission capacity of the cable under ideal conditions, such as the standard voltage and standard current, and calculate the standard resistance based on the standard voltage and standard current. Then, sum the preset electrical parameters (standard resistance) and the multiple cumulative contact resistances respectively, and use the sum as the predicted electrical parameter to calculate the multiple predicted electrical parameters of the multiple cable modules.

[0056] Then, construct an electrical sensing accuracy calculation formula. In the electrical sensing accuracy calculation formula, is the electrical sensing accuracy parameter, which characterizes the accuracy of the electrical monitoring data. The larger the electrical sensing accuracy parameter, the higher the accuracy rate of the electrical monitoring data. N is the number of electrical parameters in the electrical parameter sequence. is the i-th electrical parameter in the electrical parameter sequence. is the predicted electrical parameter. By constructing the electrical sensing accuracy calculation formula, the efficiency and accuracy of the electrical monitoring data accuracy evaluation can be improved, and the accurate evaluation of the electrical parameter accuracy can be realized. Further, use the electrical sensing accuracy calculation formula to calculate multiple electrical sensing accuracy parameters based on the multiple electrical parameter sequences and the multiple predicted electrical parameters.

[0057] Next, based on the multiple electrical perception accuracy parameters and multiple vibration perception accuracy parameters, calculate the average values of the electrical perception accuracy parameters and vibration perception accuracy parameters of the same cable module, and use the average calculation results as the perception accuracy parameters to obtain the multiple perception accuracy parameters of multiple cable modules. Finally, use the multiple perception accuracy parameters, multiple vibration parameter sequences, and multiple electrical parameter sequences as the cable state perception results for subsequent cable state analysis and maintenance decision-making.

[0058] By combining multiple perception accuracy parameters, multiple vibration parameter sequences, and multiple electrical parameter sequences, you can accurately evaluate the state of each cable module; this result provides strong data support for the operation and maintenance decision-making of the power system and can be used to determine whether a cable needs maintenance, repair, or replacement, as well as how to optimize the operation and management of the power system.

[0059] A modular cable state perception method provided by an embodiment of the present invention has at least the following technical effects:

[0060] By performing vibration monitoring and electrical monitoring on multiple connected cable modules, multiple vibration parameter sequences and multiple electrical parameter sequences are obtained; then, based on the multiple vibration parameter sequences, vibration influence verification of adjacent cable modules is performed to obtain multiple vibration perception accuracy parameters; on the other hand, based on the multiple vibration parameter sequences, contact influence analysis of the multiple cable modules is performed to obtain multiple contact influence parameters; further, based on the multiple electrical parameter sequences and multiple contact influence parameters, electrical influence verification is performed to obtain multiple electrical perception accuracy parameters; finally, based on the multiple electrical perception accuracy parameters and multiple vibration perception accuracy parameters, multiple perception accuracy parameters are calculated, and combined with the multiple vibration parameter sequences and multiple electrical parameter sequences, a cable state perception result is generated. That is to say, by combining multi-dimensional monitoring data and using a fusion algorithm to evaluate the accuracy of the monitoring results, the rationality of vibration and electrical data can be verified in real time, comprehensive and accurate cable state perception can be achieved, providing a reliable reference basis for subsequent cable maintenance, and thus improving the safety and stability of the power system.

[0061] Embodiment 2, as Figure 2As shown, based on the same inventive concept as the modular cable status perception method provided in Embodiment 1, an embodiment of the present invention further provides a modular cable status perception system, including: a cable module monitoring unit 11, configured to perform vibration monitoring and electrical monitoring on a plurality of connected cable modules to obtain a plurality of vibration parameter sequences and a plurality of electrical parameter sequences; a vibration influence verification unit 12, configured to perform vibration influence verification on adjacent cable modules according to the plurality of vibration parameter sequences to obtain a plurality of vibration perception accuracy parameters; a contact influence analysis unit 13, configured to perform contact influence analysis on the plurality of cable modules according to the plurality of vibration parameter sequences to obtain a plurality of contact influence parameters; a status perception result generation unit 14, configured to perform electrical influence verification according to the plurality of electrical parameter sequences and the plurality of contact influence parameters to obtain a plurality of electrical perception accuracy parameters, and combine the plurality of vibration perception accuracy parameters to calculate and obtain a plurality of perception accuracy parameters, and generate a status perception result.

[0062] Further, the modular cable status perception system is further configured to: divide a plurality of cable segments connected by cable joints to obtain a plurality of cable modules; monitor and acquire vibration parameters and electrical parameters within a recent preset time range through vibration sensors and electrical sensors disposed on the plurality of cable modules; arrange the monitored vibration parameters and electrical parameters in chronological order to obtain a plurality of vibration parameter sequences and a plurality of electrical parameter sequences.

[0063] Further, the modular cable status perception system is further configured to: extract amplitude parameters within the plurality of vibration parameter sequences to obtain a plurality of amplitude parameter arrays; extract the maximum amplitude parameters within the plurality of amplitude parameter arrays to obtain a plurality of maximum amplitude parameters; perform amplitude parameter mapping on adjacent cable modules according to the plurality of maximum amplitude parameters to obtain a plurality of adjacent amplitude parameter intervals; retrieve multiple groups of adjacent maximum amplitude parameters of the cable modules adjacent to each cable module, calculate the deviation amplitude from the corresponding adjacent amplitude parameter intervals, and calculate and obtain a plurality of vibration perception accuracy parameters, where the deviation amplitude is negatively correlated with the vibration perception accuracy parameters.

[0064] Furthermore, the modular cable status perception system is also used for: obtaining the vibration monitoring data of the multiple cable modules within a historical time period, and extracting multiple historical amplitude parameter sets of the multiple cable modules; clustering the same historical amplitude parameters of the same cable module within the multiple historical amplitude parameter sets to obtain multiple same amplitude parameter sets; extracting the amplitude parameter ranges of adjacent cable modules when each same amplitude parameter of each cable module appears, as amplitude parameter intervals, to obtain multiple amplitude parameter interval sets; constructing an adjacent amplitude interval mapping table by using the multiple same amplitude parameter sets and the multiple amplitude parameter interval sets; inputting the multiple maximum amplitude parameters into the adjacent amplitude interval mapping table to map and obtain multiple adjacent amplitude parameter intervals.

[0065] Furthermore, the modular cable status perception system is also used for: training a contact influence analyzer according to the vibration influence monitoring data of the cable joints within a historical time period; inputting the multiple vibration parameter sequences into the contact influence analyzer respectively, and predicting and outputting to obtain multiple contact influence parameters.

[0066] Furthermore, the modular cable status perception system is also used for: collecting a sample amplitude parameter sequence set according to the vibration influence monitoring data of the cable joints within a historical time period, and collecting the change amount of the contact resistance of the cable joints after different sample amplitude parameter sequences, as a sample contact influence parameter set; using the sample amplitude parameter sequence set and the sample contact influence parameter set, and performing supervised training of the contact influence analyzer by using machine learning and training until convergence to obtain the contact influence analyzer.

[0067] Furthermore, the modular cable status perception system is also used for: obtaining the multiple contact resistances recently recorded by the multiple cable modules, combining the multiple contact influence parameters, calculating to obtain multiple perceived contact resistances, and calculating to obtain multiple cumulative contact resistances according to the connection order of the multiple cable modules; obtaining the preset electrical parameters of the multiple cable modules, combining the multiple cumulative contact resistances, and calculating to obtain the multiple predicted electrical parameters of the multiple cable modules; calculating the cumulative deviation amplitudes between the multiple electrical parameter sequences and the multiple predicted electrical parameters respectively, and calculating to obtain multiple electrical perception accuracy parameters, as shown in the following formula: ; where is the electrical perception accuracy parameter, N is the number of electrical parameters in the electrical parameter sequence, is the i-th electrical parameter in the electrical parameter sequence, is the predicted electrical parameter; calculating multiple perception accuracy parameters according to the multiple electrical perception accuracy parameters and multiple vibration perception accuracy parameters, and combining the multiple vibration parameter sequences and multiple electrical parameter sequences to generate a cable status perception result.

[0068] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made to these embodiments by those skilled in the art once they learn of the basic inventive concept.

[0069] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. A modular cable status sensing method, characterized in that the method Including: Vibration monitoring and electrical monitoring are performed on a plurality of connected cable modules to obtain a plurality of vibration parameter sequences and a plurality of electrical parameter sequences; According to the plurality of vibration parameter sequences, vibration influence verification of adjacent cable modules is performed to obtain a plurality of vibration perception accuracy parameters, including: Amplitude parameters within the plurality of vibration parameter sequences are extracted to obtain a plurality of amplitude parameter arrays; The maximum amplitude parameters within the plurality of amplitude parameter arrays are extracted to obtain a plurality of maximum amplitude parameters; According to the plurality of maximum amplitude parameters, amplitude parameter mapping of adjacent cable modules is performed to obtain a plurality of adjacent amplitude parameter intervals; Multiple groups of adjacent maximum amplitude parameters of the cable modules adjacent to each cable module are retrieved, the deviation amplitude from the corresponding adjacent amplitude parameter intervals is calculated, and a plurality of vibration perception accuracy parameters are calculated, wherein the deviation amplitude is negatively correlated with the vibration perception accuracy parameters; According to the plurality of vibration parameter sequences, contact influence analysis of the plurality of cable modules is performed to obtain a plurality of contact influence parameters, including: According to the vibration influence monitoring data of cable joints within a historical time, a contact influence analyzer is trained, including: According to the vibration influence monitoring data of cable joints within a historical time, a sample amplitude parameter sequence set is collected, and the change amount of the contact resistance of the cable joints after different sample amplitude parameter sequences is collected as a sample contact influence parameter set; Using the sample amplitude parameter sequence set and the sample contact influence parameter set, supervised training of the contact influence analyzer is performed by machine learning and trained until convergence to obtain the contact influence analyzer; The plurality of vibration parameter sequences are respectively input into the contact influence analyzer, and a plurality of contact influence parameters are obtained by prediction output; According to the plurality of electrical parameter sequences and the plurality of contact influence parameters, electrical influence verification is performed to obtain a plurality of electrical perception accuracy parameters, and in combination with the plurality of vibration perception accuracy parameters, a plurality of perception accuracy parameters are calculated to generate a state perception result, including: The plurality of contact resistances recently recorded for the plurality of cable modules are obtained, and in combination with the plurality of contact influence parameters, a plurality of perceived contact resistances are calculated, and in accordance with the connection order of the plurality of cable modules, a plurality of cumulative contact resistances are calculated; The preset electrical parameters of the plurality of cable modules are obtained, and in combination with the plurality of cumulative contact resistances, a plurality of predicted electrical parameters of the plurality of cable modules are calculated; The cumulative deviation amplitudes between the plurality of electrical parameter sequences and the plurality of predicted electrical parameters are respectively calculated, and a plurality of electrical perception accuracy parameters are calculated, as shown in the following formula: ； Wherein, is the electrical sensing accuracy parameter, N is the number of electrical parameters in the electrical parameter sequence, is the i-th electrical parameter in the electrical parameter sequence, is the predicted electrical parameter; According to the plurality of electrical perception accuracy parameters and the plurality of vibration perception accuracy parameters, a plurality of perception accuracy parameters are calculated, and in combination with the plurality of vibration parameter sequences and the plurality of electrical parameter sequences, a cable state perception result is generated.

2. The modular cable status perception method according to claim 1, characterized in that Vibration monitoring and electrical monitoring of a plurality of connected cable modules include: A plurality of cable segments connected through cable joints are divided to obtain a plurality of cable modules; Vibration parameters and electrical parameters within a recently preset time range are monitored and acquired through vibration sensors and electrical sensors arranged on the plurality of cable modules; Arrange the monitored vibration parameters and electrical parameters in chronological order to obtain multiple vibration parameter sequences and multiple electrical parameter sequences.

3. The modular cable status perception method according to claim 1, characterized in that Based on the multiple maximum amplitude parameters, perform amplitude parameter mapping for adjacent cable modules to obtain multiple adjacent amplitude parameter intervals, including: Obtain the vibration monitoring data of the multiple cable modules within the historical time, and extract multiple historical amplitude parameter sets of the multiple cable modules; Cluster the same historical amplitude parameters of the same cable module within the multiple historical amplitude parameter sets to obtain multiple sets of the same amplitude parameters; Extract the amplitude parameter ranges of adjacent cable modules when each same amplitude parameter of each cable module appears as the amplitude parameter intervals to obtain multiple sets of amplitude parameter intervals; Use the multiple sets of the same amplitude parameters and the multiple sets of amplitude parameter intervals to construct an adjacent amplitude interval mapping table; Input the multiple maximum amplitude parameters into the adjacent amplitude interval mapping table to map and obtain multiple adjacent amplitude parameter intervals.

4. A modular cable status sensing system, characterized in that, Steps for implementing a modular cable status perception method according to any one of claims 1 to 3, including: A cable module monitoring unit for performing vibration monitoring and electrical monitoring on multiple connected cable modules to obtain multiple vibration parameter sequences and multiple electrical parameter sequences; A vibration impact verification unit for performing vibration impact verification on adjacent cable modules according to the multiple vibration parameter sequences to obtain multiple vibration perception accuracy parameters; A contact impact analysis unit for performing contact impact analysis on the multiple cable modules according to the multiple vibration parameter sequences to obtain multiple contact impact parameters; A status perception result generation unit for performing electrical impact verification according to the multiple electrical parameter sequences and the multiple contact impact parameters to obtain multiple electrical perception accuracy parameters, and combining the multiple vibration perception accuracy parameters to calculate and obtain multiple perception accuracy parameters, and generate a status perception result.

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