A method for analyzing contact resistance of a single-core cable joint and related device

Abstract

The application discloses a kind of contact resistance analysis method and related device of single-core cable joint, by extending improvement to single-core cable joint contact resistance sensing mode, based on SVM (support vector machine) algorithm development cable contact resistance inversion sensing model, utilize BA (bat) algorithm optimization inversion model parameter, improve the accuracy of model inversion. The surface hotspot temperature of single-core cable joint monitored in real time in actual field is used to quickly judge the interval of cable joint contact resistance, greatly simplify the sensing process and flow of single-core cable joint contact resistance in industrial field, reduce the serious misjudgment or misjudgment of single-core cable joint thermal fault in industrial application. Thus, the technical problems that the existing technology cannot quickly judge the contact resistance of single-core cable joint due to the complexity of the calculation process, resulting in the inability to achieve online monitoring are solved.

Description

Technical Field

[0001] The present application relates to the technical field of power cables, and in particular to a contact resistance analysis method and related device for a single-core cable joint. Background Art

[0002] According to statistics, over 80% of cable failures occur at the cable joints during operation, with excessive temperatures being one of the main causes of intermediate joint failures. Insufficient mechanical or pressure connection strength between the cable conductor and the crimping tube increases the contact resistance between the conductor and the crimping tube. As the current increases, the loss at the joint also increases, and the temperature rises accordingly. The heating of the intermediate joint causes the oxide film at the joint to thicken, further increasing the contact resistance. This repeated cycle leads to increasingly high temperatures, ultimately damaging the insulation layer and creating a major potential accident. Therefore, studying the contact resistance of cable joints is crucial for early warning of cable joint failures.

[0003] Prior art research on the contact resistance of cable joints includes, for example, patent CN110456155B, which discloses a method for measuring the contact resistance of each contact surface of a cable intermediate joint. This method can measure and calculate the contact resistance of each contact surface of a cable intermediate joint, facilitating the discovery and analysis of problems with the cable intermediate joint. For example, patent CN107203688B discloses a method for calculating the contact resistance of the crimping tube of a cable intermediate joint. This method addresses the current dilemma of lacking a theoretical model for calculating the crimping of intermediate joints and connecting tubes in cable transmission lines. This method provides an important basis for achieving safe operation of power cable transmission and a reliable reference for the initial design of the crimping process. The aforementioned technologies all provide different solutions for monitoring and calculating the contact resistance of cable joints.

[0004] However, when it comes to sensing the contact resistance of cable connectors, the above methods have the following serious drawbacks: In actual industrial settings, these single-core cable connector contact resistance measurement methods require multiple parameters to be measured, resulting in complex calculation processes and high time costs. Consequently, they are unable to achieve the goal of rapid contact resistance determination in practical applications, much less meet the industrial demand for online monitoring of the contact resistance of single-core cable connectors. Therefore, targeted research is necessary to rapidly sense the contact resistance of single-core cable connectors. Summary of the Invention

[0005] The present application provides a contact resistance analysis method and related device for a single-core cable connector, which is used to solve the technical problem that the existing technology is complex in measurement and sequencing, cannot quickly determine the contact resistance of a single-core cable connector, and cannot achieve online monitoring.

[0006] In view of this, the first aspect of the present application provides a contact resistance analysis method for a single-core cable connector, the method comprising:

[0007] A temperature field simulation model of a single-core cable joint is constructed by finite element simulation technology. The structural parameters and environmental parameters of the single-core cable joint at the industrial site are simulated based on the temperature field simulation model to obtain a temperature field distribution simulation result of the single-core cable joint;

[0008] Determine temperature sensitive points according to the temperature field distribution simulation results and use them as temperature measurement points, and obtain a large number of hot spot temperature data sets in different contact resistance ranges based on the temperature field simulation model as training data;

[0009] The support vector machine algorithm SVM is used to perform inversion training on different hotspot temperatures according to the training data, and the bat algorithm BA is used to optimize the parameters of the support vector machine algorithm, thereby constructing a BA-SVM inversion model;

[0010] The temperature data of the surface of the single-core cable joint to be tested is obtained through the temperature measuring point and input into the BA-SVM inversion model as an input data set, and the contact resistance interval of the single-core cable joint to be tested is output for online monitoring of the state of the single-core cable joint to be tested.

[0011] Optionally, the method of simultaneously optimizing the parameters of the support vector machine algorithm using the bat algorithm BA specifically includes:

[0012] Determine the parameters of the bat algorithm and initialize the population. Randomly generate an initial population of size N. At this time, the evolutionary generation is 0, and the data is normalized.

[0013] The support vector machine algorithm SVM is trained by randomly generating C and g values, and the error value is used as the fitness function to evaluate the fitness value;

[0014] Determine whether the maximum number of iterations has been reached or the termination condition has been met. If so, output the optimal C, g value. Otherwise, iteratively update the bat's position, speed, and pulse frequency until the global optimal solution and minimum fitness value are generated, and the optimal C, g value is obtained.

[0015] The optimal C,g values ​​are used as parameters of the support vector machine algorithm SVM.

[0016] Optionally, performing inversion training on different hotspot temperatures according to the training data using a support vector machine algorithm SVM specifically includes:

[0017] The training data generates a sample set {(S i , L i )|S i ∈R w , L i ∈{-1, +1}, i=1, 2, ..., N}, where S i is a W-dimensional sample, Li is the category label;

[0018] Construct several binary classifiers, and use each classifier to separate one type of samples from other samples, so that all samples can be classified.

[0019] Optionally, constructing the temperature field simulation model of the single-core cable joint by using finite element simulation technology specifically includes: constructing the temperature field simulation model of the single-core cable joint by using ANSYS finite element simulation calculation software.

[0020] A second aspect of the present application provides a contact resistance analysis system for a single-core cable connector, the system comprising:

[0021] A simulation module is used to construct a temperature field simulation model of a single-core cable joint using finite element simulation technology, simulate the structural parameters and environmental parameters of the single-core cable joint at the industrial site based on the temperature field simulation model, and obtain a temperature field distribution simulation result of the single-core cable joint;

[0022] an acquisition module, configured to determine temperature-sensitive points as temperature measurement points based on the temperature field distribution simulation results, and to acquire a large number of hotspot temperature data sets in different contact resistance intervals as training data based on the temperature field simulation model;

[0023] A construction module is used to perform inversion training on different hotspot temperatures according to the training data using a support vector machine algorithm SVM, and simultaneously perform parameter optimization on the support vector machine algorithm using a bat algorithm BA, thereby constructing a BA-SVM inversion model;

[0024] The analysis module is used to obtain the temperature data of the surface of the single-core cable joint to be tested through the temperature measuring point, and input it into the BA-SVM inversion model as an input data set, and output the contact resistance interval of the single-core cable joint to be tested for online monitoring of the state of the single-core cable joint to be tested.

[0025] Optionally, the performing parameter optimization on the support vector machine algorithm by using the bat algorithm BA specifically includes:

[0026] Determine the parameters of the bat algorithm and initialize the population. Randomly generate an initial population of size N. At this time, the evolutionary generation is 0, and the data is normalized.

[0027] The support vector machine algorithm SVM is trained by randomly generating C and g values, and the error value is used as the fitness function to evaluate the fitness value;

[0028] Determine whether the maximum number of iterations has been reached or the termination condition has been met. If so, output the optimal C, g value. Otherwise, iteratively update the bat's position, speed, and pulse frequency until the global optimal solution and minimum fitness value are generated, and the optimal C, g value is obtained.

[0029] The optimal C,g values ​​are used as parameters of the support vector machine algorithm SVM.

[0030] Optionally, performing inversion training on different hotspot temperatures according to the training data using a support vector machine algorithm SVM specifically includes:

[0031] The training data generates a sample set {(S i , L i )|S i ∈R w , L i ∈{-1, +1}, i=1, 2, ..., N}, where S i is a W-dimensional sample, L i is the category label;

[0032] Construct several binary classifiers, and use each classifier to separate one type of samples from other samples, so that all samples can be classified.

[0033] Optionally, constructing the temperature field simulation model of the single-core cable joint by using finite element simulation technology specifically includes: constructing the temperature field simulation model of the single-core cable joint by using ANSYS finite element simulation calculation software.

[0034] A third aspect of the present application provides a contact resistance analysis device for a single-core cable connector, the device comprising a processor and a memory:

[0035] The memory is used to store program code and transmit the program code to the processor;

[0036] The processor is configured to execute the steps of the contact resistance analysis method for a single-core cable connector as described in the first aspect according to the instructions in the program code.

[0037] In a fourth aspect, the present application provides a computer-readable storage medium, which is used to store program code, and the program code is used to execute the contact resistance analysis method of the single-core cable connector described in the first aspect.

[0038] It can be seen from the above technical solutions that this application has the following advantages:

[0039] The present application provides a contact resistance analysis method for a single-core cable joint, comprising: constructing a temperature field simulation model of the single-core cable joint through finite element simulation technology, simulating the structural parameters and environmental parameters of the single-core cable joint at the industrial site based on the temperature field simulation model, and obtaining a temperature field distribution simulation result of the single-core cable joint; determining a temperature sensitive point according to the temperature field distribution simulation result and using it as a temperature measurement point, and obtaining a large number of hot spot temperature data sets in different contact resistance ranges based on the temperature field simulation model as training data; performing inversion training on different hot spot temperatures according to the training data through a support vector machine algorithm SVM, and optimizing the parameters of the support vector machine algorithm through a bat algorithm BA, thereby constructing a BA-SVM inversion model; obtaining the temperature data of the surface of the single-core cable joint to be tested through the temperature measurement point, and inputting it into the BA-SVM inversion model as an input data set, and outputting the contact resistance range of the single-core cable joint to be tested for online monitoring of the state of the single-core cable joint to be tested.

[0040] Compared with the existing technology, this application expands and improves the single-core cable joint contact resistance sensing method, develops a cable contact resistance inversion sensing model based on the SVM (support vector machine) algorithm, and uses the BA (bat) algorithm to optimize the inversion model parameters to improve the accuracy of the model inversion. By using the surface hot spot temperature of the single-core cable joint monitored in real time on the actual site, the cable joint contact resistance is quickly judged within an interval, which greatly simplifies the sensing process and process of the contact resistance of the single-core cable joint in the industrial site, and reduces the serious missed or misjudgment of single-core cable joint thermal faults in industrial applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of an embodiment of a contact resistance analysis method for a single-core cable connector provided in an embodiment of the present application;

[0042] Figure 2 This is a schematic structural diagram of an embodiment of a contact resistance analysis system for a single-core cable connector provided in an embodiment of the present application;

[0043] Figure 3 A schematic diagram of a sample set provided in an embodiment of the present application;

[0044] Figure 4 This is a classification principle diagram of a "one-to-many" support vector machine algorithm provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to help those skilled in the art better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0046] See also Figure 1 A contact resistance analysis method for a single-core cable connector provided in an embodiment of the present application includes:

[0047] Step 101: construct a temperature field simulation model of a single-core cable connector using finite element simulation technology, simulate structural parameters and environmental parameters of a single-core cable connector at an industrial site based on the temperature field simulation model, and obtain a temperature field distribution simulation result of the single-core cable connector;

[0048] It should be noted that this embodiment is first carried out mainly using finite element simulation calculation software such as ANSYS. The main purpose is to build a temperature field simulation model of a single-core cable joint to simulate the structural parameters of the industrial field cable joint and the actual environment to the maximum extent; then, based on the temperature field simulation model, the temperature field distribution simulation results of the single-core cable joint are obtained, including: the structural parameters and environmental parameters of the single-core cable joint.

[0049] Step 102: determining temperature sensitive points according to the temperature field distribution simulation results and using them as temperature measurement points, and obtaining a large number of hotspot temperature data sets in different contact resistance ranges based on the temperature field simulation model as training data;

[0050] It should be noted that temperature-sensitive points are selected based on the temperature field distribution simulation results of step 101, eliminating the influence of environmental changes and determining the temperature measurement points in actual industrial field applications. Furthermore, a single-core cable connector finite element simulation model is used to obtain a large number of hotspot temperature data sets in different contact resistance ranges, providing the required training data for the contact resistance inversion calculation model. The related equation solving, coefficient setting, and condition setting methods vary depending on the finite element simulation software used. These are software operation issues and are unrelated to the main concept conveyed by this invention. Since the different software used does not affect the core concept conveyed by this invention, they are not explained in detail.

[0051] Step 103: Perform inversion training on different hotspot temperatures using the support vector machine algorithm (SVM) according to the training data, and optimize the parameters of the support vector machine algorithm using the bat algorithm (BA), thereby constructing a BA-SVM inversion model.

[0052] It should be noted that the SVM (support vector machine) algorithm is used to invert different hotspot temperature inputs based on the hotspot temperature data and contact resistance obtained from the simulation of the single-core cable connector, and quickly determine the corresponding contact resistance range under different input states.

[0053] The principle of SVM (support vector machine) algorithm is as follows:

[0054] Support vector machine is a prominent data classification method with a wide range of applications.

[0055] The support vector machine can determine the optimal classification hyperplane and maximize the area on both sides of it. This allows the samples to be classified. Assume that the sample set is represented as follows:

[0056] {(S i , L i )|S i ∈R W ,L i ∈{-1,+1},i=1,2,…,N} (1)

[0057] Where S i is a W-dimensional sample, L i is the category label.

[0058] like Figure 3 As shown in the figure, the support vector machine is the process of finding the optimal classification plane. The circles and squares represent samples of different classes, O represents the optimal classification line between the two classes, and the classification interval is the distance between O1 and O2. The goal of the optimal classification line O is to completely separate the two classes of samples and maximize the classification interval between them. When the classification interval is maximized, the optimal classification line is the optimal classification hyperplane.

[0059] The basic SVM algorithm can only classify samples into two categories: positive and negative. However, most practical problems are multi-classification problems, so it needs to be transformed to adapt to multi-classification problems. The present invention adopts a "one-to-many" method, which is more widely applicable.

[0060] The basic principle is to build multiple binary classifiers, each classifier separates one class of samples from other classes of samples. This can be done multiple times to classify all samples. The principle is shown in the following figure. Figure 4 .

[0061] Furthermore, the following should be explained about the Bat Algorithm BA:

[0062] The idea of ​​the bat algorithm comes from the bat's ability to use echolocation to sense the distance and direction of prey based on the pulse frequency, loudness and emission frequency of ultrasonic waves. The basic bat algorithm adjusts the frequency F iThe bat locks onto its target and emits ultrasonic waves based on the pulse frequency N and loudness A. When it detects prey, it approaches it by increasing the frequency and decreasing the loudness. In the actual optimization process, each bat represents a point in the problem solution space. The algorithm determines the distance of the bat's position based on the fitness function. When the fitness function reaches a minimum, the bat is in the optimal position. Each effective flight of an individual bat represents an iterative update. The update formula is as follows:

[0063]

[0064] In the formula, the pulse frequency F i ∈[F min , F max ], is the bat's flying speed at time T and T-1, is the position of the bat at time T and T-1, X * Represents the current global optimal position, and δ is a random number in the interval [0, 1]. When a bat individual selects an optimal solution during local search, it needs to perturb the optimal solution and generate a new solution:

[0065] X NEW =X * +εA T (3)

[0066] Among them, A T represents the average loudness at time T, and ε is a random number in the interval [0, 1].

[0067] When a bat spots prey, it approaches it by increasing the frequency of its transmission and decreasing its loudness. The formula for updating loudness and frequency is as follows:

[0068]

[0069]

[0070] Among them, f∈[0,1] is the loudness attenuation coefficient, φ is the transmission frequency increase coefficient, represents the maximum pulse emission frequency of bat i. The final result of the algorithm is to find the optimal C,g.

[0071] The steps of the bat algorithm in this embodiment for optimizing parameters of SVM are as follows:

[0072] (1) Determine the bat algorithm parameters;

[0073] (2) Population initialization: randomly generate an initial population of size N and evolve generation 0;

[0074] (3) Data normalization;

[0075] (4) SVM reads randomly generated C and g values ​​to train the network, uses the error value as the fitness function, and evaluates the fitness value;

[0076] (5) Determine whether the maximum number of iterations has been reached or the termination condition has been met. If so, output the optimal ξ value. Otherwise, iteratively update the bat's position, speed, and pulse frequency until a global optimal solution and minimum fitness value are generated.

[0077] (6) The optimal C,g values ​​are used as SVM parameters.

[0078] Step 104: obtain the surface temperature data of the single-core cable joint to be tested through the temperature measuring point, and input it into the BA-SVM inversion model as an input data set, and output the contact resistance range of the single-core cable joint to be tested for online monitoring of the state of the single-core cable joint to be tested.

[0079] Finally, based on the temperature field sensitive points selected by simulation in step 101, the temperature data of the corresponding points on the cable joint surface 1 are obtained on-site using the existing temperature monitoring method to obtain the BA-SVM inversion model input data set; and based on the BA-SVM inversion model and the input data set, the contact resistance of the single-core cable joint is quickly inverted to determine the interval, monitor the status of the cable joint online, and realize fault warning.

[0080] The above is a contact resistance analysis method for a single-core cable connector provided in an embodiment of the present application, and the following is a contact resistance analysis system for a single-core cable connector provided in an embodiment of the present application.

[0081] See also Figure 2 , a contact resistance analysis system for a single-core cable connector provided in an embodiment of the present application includes:

[0082] A simulation module 201 is used to construct a temperature field simulation model of a single-core cable joint using finite element simulation technology, simulate the structural parameters and environmental parameters of the single-core cable joint at an industrial site based on the temperature field simulation model, and obtain a temperature field distribution simulation result of the single-core cable joint;

[0083] An acquisition module 202 is configured to determine temperature-sensitive points based on the temperature field distribution simulation results and use them as temperature measurement points, and to acquire a large number of hotspot temperature data sets in different contact resistance ranges based on the temperature field simulation model as training data;

[0084] A construction module 203 is used to perform inversion training on different hotspot temperatures using a support vector machine algorithm (SVM) according to training data, and simultaneously optimize the parameters of the support vector machine algorithm using a bat algorithm (BA), thereby constructing a BA-SVM inversion model;

[0085] The analysis module 204 is used to obtain the temperature data of the surface of the single-core cable joint to be tested through the temperature measurement point, and input it into the BA-SVM inversion model as an input data set, and output the contact resistance range of the single-core cable joint to be tested for online monitoring of the state of the single-core cable joint to be tested.

[0086] Furthermore, an embodiment of the present application also provides a contact resistance analysis device for a single-core cable connector, the device comprising a processor and a memory:

[0087] The memory is used to store program code and transmit the program code to the processor;

[0088] The processor is configured to execute the steps of the contact resistance analysis method for a single-core cable connector as described in the above method embodiment according to the instructions in the program code.

[0089] Furthermore, a computer-readable storage medium is provided in an embodiment of the present application, wherein the computer-readable storage medium is used to store program code, and the program code is used to execute the contact resistance analysis method of the single-core cable connector described in the above method embodiment.

[0090] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0091] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0092] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0093] In the several embodiments provided in this 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 schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0094] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0095] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0096] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling 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 method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (English full name: Read-Only Memory, English abbreviation: ROM), random access memory (English full name: Random Access Memory, English abbreviation: RAM), disk or optical disk and other media that can store program code.

[0097] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A contact resistance analysis method for a single-core cable connector, characterized in that: include: A temperature field simulation model of a single-core cable joint is constructed by finite element simulation technology. The structural parameters and environmental parameters of the single-core cable joint at the industrial site are simulated based on the temperature field simulation model to obtain a temperature field distribution simulation result of the single-core cable joint; Determine temperature sensitive points according to the temperature field distribution simulation results and use them as temperature measurement points, and obtain a large number of hot spot temperature data sets in different contact resistance ranges based on the temperature field simulation model as training data; The support vector machine algorithm SVM is used to perform inversion training on different hotspot temperatures according to the training data, and the bat algorithm BA is used to optimize the parameters of the support vector machine algorithm, thereby constructing a BA-SVM inversion model; The temperature data of the surface of the single-core cable joint to be tested is obtained through the temperature measuring point and input into the BA-SVM inversion model as an input data set, and the contact resistance interval of the single-core cable joint to be tested is output for online monitoring of the state of the single-core cable joint to be tested.

2. The contact resistance analysis method of a single-core cable connector according to claim 1, characterized in that: The method of optimizing the parameters of the support vector machine algorithm by using the bat algorithm BA specifically includes: Determine the parameters of the bat algorithm and initialize the population. Randomly generate an initial population of size N. At this time, the evolutionary generation is 0, and the data is normalized. By randomly generated The network training of the support vector machine algorithm SVM is performed, the error value is used as the fitness function, and the fitness value is evaluated; Determine whether the maximum number of iterations has been reached or the termination condition has been met. If so, output the best Otherwise, iteratively update the bat's position, speed and pulse frequency until the global optimal solution and minimum fitness value are generated, and the optimal value; The best The values ​​are used as parameters of the support vector machine algorithm SVM.

3. The contact resistance analysis method of a single-core cable connector according to claim 1, characterized in that: The inversion training of different hotspot temperatures using the support vector machine algorithm SVM according to the training data specifically includes: Generate a sample set from the training data , where yes dimensional sample, is the category label; Construct several binary classifiers, and use each classifier to separate one type of samples from other samples, so that all samples can be classified.

4. The contact resistance analysis method of a single-core cable connector according to claim 1, characterized in that: The constructing of the temperature field simulation model of the single-core cable joint by using the finite element simulation technology specifically includes: constructing the temperature field simulation model of the single-core cable joint by using ANSYS finite element simulation calculation software.

5. A contact resistance analysis system for a single-core cable connector, characterized in that: include: A simulation module is used to construct a temperature field simulation model of a single-core cable joint using finite element simulation technology, simulate the structural parameters and environmental parameters of the single-core cable joint at the industrial site based on the temperature field simulation model, and obtain a temperature field distribution simulation result of the single-core cable joint; an acquisition module, configured to determine temperature-sensitive points as temperature measurement points based on the temperature field distribution simulation results, and to acquire a large number of hotspot temperature data sets in different contact resistance intervals as training data based on the temperature field simulation model; A construction module is used to perform inversion training on different hotspot temperatures according to the training data using a support vector machine algorithm SVM, and simultaneously perform parameter optimization on the support vector machine algorithm using a bat algorithm BA, thereby constructing a BA-SVM inversion model; The analysis module is used to obtain the temperature data of the surface of the single-core cable joint to be tested through the temperature measuring point, and input it into the BA-SVM inversion model as an input data set, and output the contact resistance interval of the single-core cable joint to be tested for online monitoring of the state of the single-core cable joint to be tested.

6. The contact resistance analysis system for a single-core cable connector according to claim 5, characterized in that: The method of optimizing the parameters of the support vector machine algorithm by using the bat algorithm BA specifically includes: Determine the parameters of the bat algorithm and initialize the population. Randomly generate an initial population of size N. At this time, the evolutionary generation is 0, and the data is normalized. By randomly generated The network training of the support vector machine algorithm SVM is performed, the error value is used as the fitness function, and the fitness value is evaluated; Determine whether the maximum number of iterations has been reached or the termination condition has been met. If so, output the best Otherwise, iteratively update the bat's position, speed and pulse frequency until the global optimal solution and minimum fitness value are generated, and the optimal value; The best The values ​​are used as parameters of the support vector machine algorithm SVM.

7. The contact resistance analysis system for a single-core cable connector according to claim 5, characterized in that: The inversion training of different hotspot temperatures using the support vector machine algorithm SVM according to the training data specifically includes: Generate a sample set from the training data , where yes dimensional sample, is the category label; Construct several binary classifiers, and use each classifier to separate one type of samples from other samples, so that all samples can be classified.

8. The contact resistance analysis system for a single-core cable connector according to claim 5, characterized in that: The constructing of the temperature field simulation model of the single-core cable joint by using the finite element simulation technology specifically includes: constructing the temperature field simulation model of the single-core cable joint by using ANSYS finite element simulation calculation software.

9. A contact resistance analysis device for a single-core cable connector, characterized in that: The device includes a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the contact resistance analysis method of a single-core cable connector according to any one of claims 1 to 4 according to the instructions in the program code.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium is used to store program codes, and the program codes are used to execute the contact resistance analysis method for a single-core cable connector according to any one of claims 1 to 4.

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