A method and system for diagnosing faults in a cable and its accessories on-line

Abstract

The application relates to the technical field of electrical engineering, in particular to an online fault diagnosis method and system for a cable and accessories thereof, which comprises the following steps: constructing a target function of an inversion model based on the distance from any unit in the inversion model to a measuring point of the cable and accessories thereof; determining a sensitivity matrix of the inversion model based on a stiffness matrix corresponding to a temperature field of the cable and accessories thereof; determining an initial heat source distribution of the cable and accessories thereof based on the sensitivity matrix and the target function; determining an initial temperature distribution of the cable and accessories thereof based on the initial heat source distribution by using a forward model; iteratively updating the initial heat source distribution based on the temperature difference between the initial temperature distribution and a measured temperature distribution until a target heat source distribution meeting a preset condition is obtained; and performing fault diagnosis on the cable and accessories thereof based on the target heat source distribution and the forward model. The method can accurately realize fault diagnosis on the cable and accessories thereof and improve the accuracy of fault diagnosis on the cable and accessories thereof.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electrical engineering, in particular to an online fault diagnosis method and system for a cable and its accessories. BACKGROUND

[0002] In order to determine the running state of the cable, including normal or fault, whether full load, the temperature field inside the cable and its accessories needs to be obtained, and the temperature field is used for evaluation. The inversion algorithm is currently used to solve whether the cable is full load. The commonly used method is mostly completed on the basis of the equivalent thermal circuit model. The method equivalent each layer of the cable and its accessories to a circuit element. The core temperature is inversely deduced from the external temperature through the functional relationship between the internal and external temperatures. Such a method is relatively simple in algorithm construction and convenient to implement. However, the real cable is a three-dimensional structure. The above method cannot consider the locality of the fault, so that the judgment result deviates seriously. SUMMARY

[0003] The purpose of the present application is to provide an intelligent expectation control method with limit stability. The technical solution adopted is as follows:

[0004] In a first aspect, the present application provides an online fault diagnosis method for a cable and its accessories, which comprises:

[0005] A target function of the inversion model is constructed based on the distance from any unit in the inversion model to the measurement point of the cable and its accessories;

[0006] A sensitivity matrix of the inversion model is determined based on the stiffness matrix corresponding to the temperature field of the cable and its accessories;

[0007] An initial heat source distribution of the cable and its accessories is determined based on the sensitivity matrix and the target function;

[0008] An initial temperature distribution of the cable and its accessories is determined based on the initial heat source distribution by using a forward model;

[0009] The initial heat source distribution is iteratively updated based on the temperature difference between the initial temperature distribution and the measured temperature distribution until a target heat source distribution meeting a preset condition is obtained;

[0010] The cable and its accessories are diagnosed for faults based on the target heat source distribution and the forward model.

[0011] In a second aspect, an online fault diagnosis system for a cable and its accessories is provided, which comprises:

[0012] A construction module is configured to construct a target function of an inversion model based on the distance from any unit in the inversion model to the measurement point of the cable and its accessories;

[0013] a first determining module, configured to determine a sensitivity matrix of the inversion model based on a stiffness matrix corresponding to a temperature field of the cable and the accessories thereof;

[0014] a second determining module, configured to determine an initial heat source distribution of the cable and the accessories thereof based on the sensitivity matrix and the objective function;

[0015] a forward modeling module, configured to determine an initial temperature distribution of the cable and the accessories thereof based on the initial heat source distribution by using a forward model;

[0016] an iterative updating module, configured to iteratively update the initial heat source distribution based on a temperature difference between the initial temperature distribution and a measured temperature distribution until a target heat source distribution satisfying a preset condition is obtained;

[0017] a diagnosing module, configured to perform fault diagnosis on the cable and the accessories thereof based on the target heat source distribution and the forward model.

[0018] In a third aspect, a computer program product is provided, which includes computer program code, when the computer program code is run on a computer, causes the computer to execute the method in the first aspect or any possible implementation manner of the first aspect.

[0019] In a fourth aspect, a computer readable storage medium is provided, which stores computer program code, when the computer program code is run on a computer, causes the computer to execute the method in the first aspect or any possible implementation manner of the first aspect.

[0020] The present application has the following beneficial effects: by considering the distance from any unit in the inversion model to the measured point of the cable and the accessories thereof, the objective function of the inversion model is constructed, which can inhibit the multi-solution of the objective function of the inversion model. Then, the sensitivity matrix of the inversion model is calculated based on the stiffness matrix corresponding to the temperature field of the cable and the accessories thereof, so as to accelerate the inversion calculation speed; and the initial heat source distribution of the cable and the accessories thereof is calculated by inversion based on the sensitivity matrix and the objective function; the initial temperature distribution of the cable and the accessories thereof is determined based on the initial heat source distribution by using the forward model; the temperature difference between the initial temperature distribution and the measured temperature distribution is analyzed, and the initial heat source distribution is iteratively updated by the inversion module until the target heat source distribution satisfying the preset condition is obtained, so that the accuracy of the obtained target heat source distribution is high. Finally, the temperature distribution corresponding to the target heat source distribution is calculated by using the forward model, so that the fault diagnosis on the cable and the accessories thereof can be accurately realized, and the accuracy of the fault diagnosis on the cable and the accessories thereof is improved. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, and the advantages thereof, the following will briefly introduce the drawings needed in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 is a flowchart of an implementation process of a cable and accessory online fault diagnosis method provided by an embodiment of the present application;

[0023] Figure 2 is another flowchart of an implementation process of a cable and accessory online fault diagnosis method provided by an embodiment of the present application;

[0024] Figure 3 is still another flowchart of an implementation process of a cable and accessory online fault diagnosis method provided by an embodiment of the present application;

[0025] Figure 4 is a structural schematic diagram of a cable and accessory online fault diagnosis system provided by an embodiment of the present application;

[0026] Figure 5 is a structural schematic diagram of a computer device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to further illustrate the technical means and effects taken by the present application to achieve the predetermined purposes, the following describes a cable and accessory online fault diagnosis method according to the present application, its specific implementation, structure, features and effects in detail, with reference to the drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0028] In the description of the embodiments of the present application, unless otherwise specified, " / " represents the meaning of or, for example, A / B can represent A or B: "and / or" in the text is only a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent: A exists alone, A and B exist together, and B exists alone, in addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0029] The terms "first", "second", "third", etc. are used only for the purpose of description, and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0031] In the related art, few scholars apply the inversion algorithm to the measurement of the internal heat source distribution of the cable and its accessories, and most of them use the thermal circuit model to invert the core temperature. Such an algorithm will be relatively simple, but it is not intuitive and cannot obtain the temperature value at any position of the cable. The device developed in the embodiments of the present application obtains the external temperature value based on infrared or optical fiber, uses this as the convergence condition, and combines the finite element algorithm to invert the internal heat source distribution by using regularization or singular value decomposition method, and at the same time, the temperature distribution at any position inside the cable can be obtained, the position of the heat source is clearly displayed, which is more conducive to evaluating the operation state of the cable based on the field distribution, so as to realize online fault diagnosis.

[0032] The specific scheme of the online fault diagnosis method for the cable and its accessories provided by the present application will be described in detail below with reference to the accompanying drawings. Please refer to Figure 1 , which shows the implementation flowchart of the online fault diagnosis method for the cable and its accessories provided by an embodiment of the present application. The method comprises:

[0033] 101, based on the distance from any unit in the inversion model to the measurement point of the cable and its accessories, constructing the objective function of the inversion model.

[0034] Here, in the heat source inversion model, the heat source at the position close to the measurement point has a greater influence on the potential at the measurement point. When the heat source inversion is performed in the whole space, the sensitivity near the measurement point will be higher, so that the heat source density obtained by inversion is concentrated on the surface, and the result presents "skin effect". Therefore, it is necessary to introduce the distance weighting function in the inversion equation for accurate calculation of the heat source density distribution.

[0035] In some possible implementation manners, the above step 101 can be implemented by Figure 2 as shown in the figure:

[0036] 201, based on the distance from any unit in the inversion model to the measurement point of the cable and its accessories, determining the weighting coefficient.

[0037] Here, the distance weighting factor is calculated by obtaining the maximum distance and the minimum distance from any unit to the measuring point of the cable and its accessories, and the weighting coefficient is obtained by summing the distance weighting factors corresponding to each measuring point.

[0038] In some possible implementations, the above step 201 can be implemented by the following steps 211 to 213 (not shown in the figure):

[0039] 211, determine the maximum distance and the minimum distance from any unit to the measuring point of the cable and its accessories.

[0040] 212, determine the weighting factor based on the maximum distance and the minimum distance.

[0041] 213, fuse the distance from multiple units to the measuring point of the cable and its accessories with the weighting factor to obtain the weighting coefficient.

[0042] In the above steps 211 to 213,

[0043] Thus, the inversion model adopts triangular mesh division, assuming that the model has M units, and the distance of the i-th unit to the measuring point is shown in formula (1):

[0044] (1);

[0045] wherein, , represents the coordinates of the center point of the i-th unit, represents the coordinates of the measuring point. According to the distance from the measuring point to the inner electrode, the sensitivity matrix of the heat source to the electric field is adjusted. After distance weighting, the sensitivity of the position close to the measuring point should be suppressed, and the distance weighting factor (i.e. the weighting coefficient) is shown in formula (2):

[0046] (2);

[0047] wherein, .

[0048] wherein, is defined as formula (3):

[0049] (3);

[0050] wherein, d iA,max represents the maximum value of the distance from the inversion point to the electrode; d iA,min represents the minimum value of the distance from the inversion point to the electrode. When d iA is close to d iA,min , the distance weighting factor is close to 1. When d iA is close to d iA,maxThe distance weighting factor is close to 0 when the distance is small. Therefore, the distance weighting factor increases when the distance is close to the measurement point, and the distance weighting factor decreases when the distance is far away from the electrode. The comprehensive weighting factor w i of the i th unit in the inversion model is shown in formula (4) i The comprehensive weighting factor is shown in formula (4), where j represents the position of the measurement point, and K represents the number of measurement points.

[0051] (4).

[0052] 202, based on the weighting coefficient, constructing a target function of the inversion model.

[0053] Here, the sensitivity matrix of the inversion model, the temperature of the measurement point, and the regularization factor are obtained, and the sensitivity matrix, the temperature of the measurement point, and the regularization factor are adjusted by the weighting coefficient to obtain the target function. In some possible implementation manners, the weighting coefficient in formula (4) is applied to the target function of the inversion model, and the target function of the inversion model is shown in formula (5):

[0054] (5).

[0055] Where W represents a matrix composed of distance weighting functions, u represents the temperature of the measurement point. represents the sensitivity matrix. In this way, solving formula (5) is equivalent to solving formula (6):

[0056] (6).

[0057] Where, .

[0058] In the embodiment of the present application, by introducing the distance weighting, the multi-solution of the target function of the inversion model can be effectively suppressed.

[0059] 102, based on the stiffness matrix corresponding to the temperature field of the cable and its accessories, determining the sensitivity matrix of the inversion model.

[0060] Here, the temperature measurement platform is built on the measuring cable or accessories to obtain the surface temperature of the device, and the sensitivity matrix of the surface temperature measurement value deviation to the heat source distribution is calculated. Based on the finite element, the stiffness matrix is introduced, and the sensitivity matrix is calculated through the stiffness matrix. In some possible implementation manners, first, the temperature field of the cable and its accessories is calculated based on the finite element to obtain the stiffness matrix.

[0061] Here, when the temperature field of the cable and its accessories is calculated by using the finite element, the corresponding stiffness matrix equation is shown in formula (7):

[0062] (7);

[0063] Where K represents the stiffness matrix, each element of which is related to the relative permittivity of the model and the grid properties; V represents the temperature at the grid point; and S represents the source term, which is related to the heat source density.

[0064] Secondly, based on the stiffness matrix, the derivative of the temperature of any measurement point with respect to the heat source density is determined.

[0065] Here, the sensitivity matrix can be derived by calculating the partial derivative of the temperature with respect to the heat source. Therefore, by taking the partial derivative of formula (7) with respect to the heat source density, formula (8) is obtained:

[0066] (8);

[0067] Where the stiffness matrix K, the source term S, and the temperature V have been obtained in the forward modeling, and the derivative of the stiffness matrix with respect to the heat source is 0. Formula (8) can be converted to formula (9) as shown:

[0068] (9);

[0069] Where the derivative D of the source term with respect to the heat source density can be directly obtained in the forward modeling, and D = [d1, d2, …d m ] T Formula (9) is written in the form of formula (10):

[0070] (10);

[0071] [1, 0, 0, …, 0] T is regarded as a new source term, and the partial derivative of the temperature of M points with respect to the heat source in formula (10) is converted to formula (11) as shown:

[0072] (11);

[0073] In the formula: V(k, M) represents the temperature at M point when the heat source is placed at k node. According to the reciprocity theorem, formula (11) can be transformed into formula (12) as shown:

[0074] (12);

[0075] Where V(M, k) represents the temperature at k point when the heat source is placed at M node. When the measurement point is much smaller than the inversion parameter, the application of this method will greatly reduce the workload of constructing the sensitivity matrix.

[0076] Finally, based on the derivative of the temperature of any measurement point with respect to the heat source density, a sensitivity matrix of the inversion model is determined; in this way, by combining the finite element method, the sensitivity matrix is derived by calculating the partial derivative of the temperature with respect to the heat source density, and the sensitivity matrix of the inversion model can be quickly and accurately constructed.

[0077] 103, based on the sensitivity matrix and the objective function, an initial heat source distribution of the cable and its accessories is determined.

[0078] Here, after the sensitivity matrix is constructed, the objective function of the inversion model is substituted, and by transposing the sensitivity matrix, a processed matrix is obtained; then, based on the weighting coefficient in the objective function and the processed matrix, the initial heat source distribution of the cable and its accessories is calculated. As shown in formula (6), by the processed matrix A T , the weighting coefficient W and the measured temperature u, the initial heat source distribution of the cable and its accessories can be calculated.

[0079] 104, using the forward model, based on the initial heat source distribution, an initial temperature distribution of the cable and its accessories is determined.

[0080] Here, after the initial heat source distribution is calculated, the initial heat source distribution is taken as the input of the forward model, and the temperature distribution of the entire calculation domain is calculated by the forward model, that is, the initial temperature distribution is obtained.

[0081] 105, based on the temperature difference between the initial temperature distribution and the measured temperature distribution, the initial heat source distribution is iteratively updated until a target heat source distribution satisfying a preset condition is obtained.

[0082] Here, for any measurement point in the cable and its accessories, the temperature thereof is measured to obtain a measured temperature distribution. The temperature difference between the initial temperature distribution and the measured temperature distribution is calculated, and it is judged whether the temperature difference is greater than a preset temperature difference threshold; if the temperature difference is greater than the preset temperature difference threshold, a regularization or singular value decomposition algorithm is used to iteratively update the initial heat source distribution until a target heat source distribution satisfying a preset condition is obtained.

[0083] In some possible implementations, after the initial heat source distribution is iteratively updated, the forward model is used to calculate a target temperature distribution of the cable and its accessories based on the target heat source distribution; if the temperature difference between the target temperature distribution and the measured temperature distribution is less than or equal to the preset temperature difference threshold, it is determined that the target heat source distribution satisfies the preset condition.

[0084] In some possible implementations, the target heat source distribution can be calculated by Figure 3The steps shown achieve an iterative updating process of the target heat source distribution:

[0085] 301. Distance weighting is performed based on the distance from the i th element of the inversion model to the measurement point, and a target function of the inversion model is constructed.

[0086] 302. A temperature measurement platform is built on the cable or accessory to obtain the surface temperature of the device, and the sensitivity matrix of the surface temperature measurement value deviation to the charge density is calculated.

[0087] 303. An initial heat source distribution in the device is set.

[0088] 304. The initial temperature distribution of the entire calculation domain is calculated through the forward model.

[0089] 305. It is judged whether the deviation of the temperature at the measurement point obtained by inversion from the measurement value is less than the requirement, and if the requirement is met, the inversion is ended.

[0090] Here, it is judged whether the deviation of the temperature at the measurement point obtained by inversion from the measurement value is less than the requirement, that is, whether the temperature difference between the target temperature distribution and the measured temperature distribution is less than or equal to the preset temperature difference threshold value, wherein the preset temperature difference threshold value can be a self-defined smaller value.

[0091] 306. If the temperature difference does not meet the requirement, the initial heat source distribution is corrected through a regularization or singular value decomposition algorithm, and step 303 is returned.

[0092] 307. If the temperature difference meets the requirement, the inversion is ended, and the target heat source distribution is output.

[0093] In some possible implementations, the heat source distribution in the solution domain is obtained from the temperature inversion of the measurement point, and the functional relationship between the measured temperature and the heat source density needs to be determined. Let the relationship between the measured temperature and the heat source density at the position to be inverted be , ignoring the first-order infinitesimal, the first-order Taylor expansion of the function at the measurement point a is shown in formula (13):

[0094] (13);

[0095] If the inversion parameter is the heat source density in N elements, then:

[0096] (14);

[0097] On the basis that the forward FEM model is established, the quantitative relationship between the deviation of the surface temperature measurement value and the calculated value at point j and the heat source density increment of the t th element is shown in formula (15):

[0098] (15);

[0099] Among them, u cej This represents the temperature measurement value at point j; u mj This represents the calculated temperature value at point j. This represents the correction amount for the heat source density at element t in the inversion model; It represents the partial derivative of the deviation between the measured and calculated temperature value at point j with respect to the heat source density at cell t.

[0100] The temperature residual corresponding to measurement point j is shown in formula (16):

[0101] (j = 1, 2,..., M) (16);

[0102] According to formula (15), the sensitivity of the temperature deviation (i.e., temperature difference) at point j to the heat source density at unit t is defined as shown in formula (17):

[0103] (17);

[0104] Extending formula (15) to the entire structural unit model, we obtain the linear equation set of the heat source distribution inversion model as shown in formula (18):

[0105] (18);

[0106] in, d This represents the residual between the measured value and the theoretically calculated value. ; p This represents the heat source density increment to be corrected in the model. ; A The sensitivity matrix of the model ; u ce Represents measurement data; u This represents calculated data. Because... dimensionality and d Since the dimensions are different, formula (18) is an ill-conditioned equation.

[0107] In the realm of mathematics, the inversion problem of heat source density can be viewed as solving an inverse problem, that is, taking the deviation between the temperature measurement result and the calculation result as input and the heat source density correction value as output, to obtain formula (19):

[0108] (19);

[0109] In order to obtain an electric field FEM calculation model consistent with the measurement results, the heat source distribution in the FEM model needs to be continuously updated, resulting in formula (20):

[0110] (20);

[0111] wherein, represents the updated heat source density on the tth unit; represents the heat source density on the tth unit before correction. After multiple iterations of correction, the heat source density distribution satisfying the minimum temperature deviation is obtained, i.e., the target heat source distribution is obtained.

[0112] 106, based on the target heat source distribution and the forward model, fault diagnosis is performed on the cable and its accessories.

[0113] Here, after the target heat source distribution is obtained by inversion calculation, the target heat source distribution is input into the forward model (such as the forward FEM model), and the target temperature distribution at each position obtained by forward calculation is recorded; by the target temperature distribution and the position information where the target temperature distribution is located, fault diagnosis is performed on the cable and its accessories.

[0114] Here, the judged fault type is sent to the customer through infrared / optical fiber, for example, two infrareds and multiple optical fibers are laid outside the equipment, and the target temperature distribution and the position information where the target temperature distribution is located are uploaded to the cloud, the cloud judges the fault type and sends it to the user.

[0115] In some possible implementations, using the equipment developed by the embodiments of the present application, the three-dimensional structure of the cable can be considered, the internal heat source distribution is inverted through the external temperature condition, the internal temperature distribution is calculated by using the forward model, the area of abnormal heating is directly displayed, and the fault type is judged according to the heating degree and the position, as shown in Table 1.

[0116] Table 1: Correspondence table of heat source distribution abnormal characteristics and fault types

[0117]

[0118] In the embodiment of the present application, the multi-solution of the objective function of the inversion model is suppressed by constructing the objective function of the inversion model by considering the distance from any unit in the inversion model to the measuring point of the cable and its accessories. Then, the sensitivity matrix of the inversion model is calculated by the stiffness matrix corresponding to the temperature field of the cable and its accessories, so as to accelerate the inversion calculation speed; and the initial heat source distribution of the cable and its accessories is calculated by inversion based on the sensitivity matrix and the objective function; the initial temperature distribution of the cable and its accessories is determined based on the initial heat source distribution by the forward model; the initial heat source distribution is iteratively updated by analyzing the temperature difference between the initial temperature distribution and the measured temperature distribution, until the target heat source distribution satisfying the preset condition is obtained, so that the accuracy of the obtained target heat source distribution is higher. Finally, the temperature distribution corresponding to the target heat source distribution is calculated by the forward model, so that the fault diagnosis of the cable and its accessories can be accurately realized, and the accuracy of the fault diagnosis of the cable and its accessories is improved.

[0119] The embodiment of the present application provides an online fault diagnosis system for a cable and its accessories, please refer to Figure 4 which shows the component structure schematic diagram of the online fault diagnosis system for a cable and its accessories provided by the embodiment of the present application, the system 400 comprises:

[0120] The construction module 401 is configured to construct the objective function of the inversion model based on the distance from any unit in the inversion model to the measuring point of the cable and its accessories; the first determination module 402 is configured to determine the sensitivity matrix of the inversion model based on the stiffness matrix corresponding to the temperature field of the cable and its accessories; the second determination module 403 is configured to determine the initial heat source distribution of the cable and its accessories based on the sensitivity matrix and the objective function; the forward module 404 is configured to determine the initial temperature distribution of the cable and its accessories based on the initial heat source distribution by the forward model; the iterative updating module 405 is configured to iteratively update the initial heat source distribution based on the temperature difference between the initial temperature distribution and the measured temperature distribution, until the target heat source distribution satisfying the preset condition is obtained; and the diagnosis module 406 is configured to perform fault diagnosis on the cable and its accessories based on the target heat source distribution and the forward model.

[0121] In some possible implementation manners, the construction module 401 is further configured to determine a weighting coefficient based on the distance from any unit in the inversion model to the measuring point of the cable and its accessories; and construct the objective function of the inversion model based on the weighting coefficient.

[0122] In some possible implementation manners, the construction module 401 is further configured to determine a maximum distance and a minimum distance from any unit to a measuring point of the cable and its accessories, determine a weighting factor based on the maximum distance and the minimum distance, and fuse distances from multiple units to the measuring point of the cable and its accessories with the weighting factor to obtain the weighting coefficient.

[0123] In some possible implementation manners, the construction module 401 is further configured to determine a sensitivity matrix of the inversion model, a temperature of a measuring point, and a regularization factor, and adjust the sensitivity matrix of the inversion model, the temperature of the measuring point, and the regularization factor based on the weighting coefficient to obtain the objective function.

[0124] In some possible implementation manners, the first determination module 402 is further configured to calculate a temperature field of the cable and its accessories based on finite elements to obtain the stiffness matrix, determine a derivative of a temperature of any measuring point with respect to a heat source density based on the stiffness matrix, and determine the sensitivity matrix of the inversion model based on the derivative of the temperature of any measuring point with respect to the heat source density.

[0125] In some possible implementation manners, the second determination module 403 is further configured to perform transpose processing on the sensitivity matrix to obtain a processed matrix, and calculate an initial heat source distribution of the cable and its accessories based on the weighting coefficient in the objective function and the processed matrix.

[0126] In some possible implementation manners, the iterative updating module 405 is further configured to determine whether the temperature difference is greater than a preset temperature difference threshold, and if the temperature difference is greater than the preset temperature difference threshold, perform inversion calculation on a heat source correction value of the cable and its accessories by using a regularization or singular value decomposition algorithm, and iteratively update the initial heat source distribution based on the heat source correction value until a target heat source distribution that meets a preset condition is obtained.

[0127] In some possible implementation manners, the iterative updating module 405 is further configured to calculate a target temperature distribution of the cable and its accessories based on the target heat source distribution by using the forward model, and if a temperature difference between the target temperature distribution and a measured temperature distribution is less than or equal to the preset temperature difference threshold, determine that the target heat source distribution meets the preset condition.

[0128] In some possible implementation manners, the diagnosis module 406 is further configured to calculate a target temperature distribution corresponding to the target heat source distribution by using the forward model, and perform fault diagnosis on the cable and its accessories based on the target temperature distribution and position information where the target temperature distribution is located.

[0129] Optionally, the transmission medium can be a wired link (for example, but not limited to, a coaxial cable, an optical fiber, a Digital Subscriber Line (DSL), and the like) or a wireless link (for example, but not limited to, Wireless Fidelity (WIFI), Bluetooth, and a mobile device network, and the like). It should be noted that the system provided in the above embodiments is only used as an example for the division of the above functional modules, and in actual applications, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the above described functions. In addition, the method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process is shown in the method embodiments, which will not be described here.

[0130] Figure 5 is a structural schematic diagram of a computer device provided by an embodiment of the present application. As shown in the example, Figure 5 the computer device 500 includes a memory 501, a processor 502, and a computer program 503 stored in the memory 501 and running on the processor 502, wherein when the processor 502 executes the computer program 503, the computer device can execute the online fault diagnosis method of any one of the above-described cables and accessories.

[0131] In addition, an embodiment of the present application also protects a system, which can include a memory and a processor, wherein the memory stores executable program code, and the processor is used to call and execute the executable program code to execute the online fault diagnosis method of a cable and its accessories provided by an embodiment of the present application. The system can be divided into functional modules according to the above method examples in this embodiment, for example, each functional module can be corresponding, or two or more functions can be integrated in one processing module, and the integrated module can be realized in the form of hardware. It should be noted that the division of the modules in this embodiment is illustrative, and is only a logical function division, and another division mode can be used in actual implementation. It should be noted that all related contents of each step involved in the above method embodiments can be cited to the function description of the corresponding functional module, and will not be described here.

[0132] It should be understood that the system provided by the embodiments is used to execute the above-mentioned cable and its accessories online fault diagnosis method, and thus the same effects as the above-mentioned implementation method can be achieved. In the case of using an integrated unit, the system can include a processing module and a storage module. When the system is applied to a device, the processing module can be used to control and manage the actions of the device. The storage module can be used to support the device to execute mutual program codes and the like. The processing module can be a processor or a controller, which can realize or execute various exemplary logical blocks, modules and circuits described in combination with the disclosure. The processor can also be a combination of computing functions, such as one or more microprocessor combinations, a combination of digital signal processing (DSP) and microprocessor, and the like. The storage module can be a memory.

[0133] In addition, the system provided by the embodiments of the present application can be a chip, a component or a module, which can include a connected processor and a memory. The memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the above-mentioned cable and its accessories online fault diagnosis method provided by the embodiments. The present embodiment also provides a computer readable storage medium, which stores computer program codes. When the computer program codes are run on the computer, the computer can execute the above-mentioned related method steps to realize the above-mentioned cable and its accessories online fault diagnosis method provided by the embodiments.

[0134] The embodiment further provides a computer program product, which, when running on a computer, enables the computer to execute the above related steps to implement the cable and accessory online fault diagnosis method provided by the above embodiment. The system, computer readable storage medium, computer program product or chip provided by the embodiment are used to execute the corresponding method provided above, and thus the beneficial effects achieved thereby can refer to the beneficial effects of the corresponding method provided above, which will not be described here again. Through the above description of the implementation manner, those skilled in the art can understand that, for the convenience and brevity of description, only the division of the above functional modules is taken as an example for illustration, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the system is divided into different functional modules to complete all or part of the functions described above. In the embodiments provided by the present application, it should be understood that the disclosed system and method can be implemented in other ways. For example, the system embodiments described above are only schematic, for example, the division of the modules or units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, system or unit, and can be electrical, mechanical or other forms.

[0135] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multiple task processing and parallel processing are also possible or can be advantageous. Each embodiment in the specification is described in a progressive manner, and the same or similar parts of each embodiment can be referred to each other, and each embodiment mainly describes the differences from other embodiments. The above is only a specific implementation manner of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for diagnosing a fault in a cable and its accessories on-line, characterized in that, The method comprises: constructing an objective function of the inversion model based on distances from any unit in the inversion model to the measuring points of the cable and its accessories, including: determining a weighting coefficient based on distances from any unit in the inversion model to the measuring points of the cable and its accessories; constructing an objective function of the inversion model based on the weighting coefficient; determining a sensitivity matrix of the inversion model based on a stiffness matrix corresponding to a temperature field of the cable and its accessories, including: calculating the temperature field of the cable and its accessories by using finite elements to obtain the stiffness matrix; determining a derivative of temperature of any measuring point with respect to heat source density based on the stiffness matrix; determining a sensitivity matrix of the inversion model based on the derivative of temperature of any measuring point with respect to heat source density; determining an initial heat source distribution of the cable and its accessories based on the sensitivity matrix and the objective function; determining an initial temperature distribution of the cable and its accessories based on the initial heat source distribution by using a forward model; iteratively updating the initial heat source distribution based on a temperature difference between the initial temperature distribution and a measured temperature distribution until a target heat source distribution satisfying a preset condition is obtained, including: determining whether the temperature difference is greater than a preset temperature difference threshold value; if the temperature difference is greater than the preset temperature difference threshold value, inversely calculating a heat source correction value of the cable and its accessories by using a regularization or singular value decomposition algorithm; iteratively updating the initial heat source distribution based on the heat source correction value until a target heat source distribution satisfying a preset condition is obtained; performing fault diagnosis on the cable and its accessories based on the target heat source distribution and the forward model.

2. A method of diagnosing a fault in a cable and its accessories on-line according to claim 1, characterized in that, The method further comprises: determining a weighting coefficient based on distances from any unit in the inversion model to the measuring points of the cable and its accessories, including: determining a maximum distance and a minimum distance from the any unit to the measuring points of the cable and its accessories; determining a weighting factor based on the maximum distance and the minimum distance; 3. The method of claim 1, wherein the method is characterized by: fusing distances from multiple units to the measuring points of the cable and its accessories with the weighting factor to obtain the weighting coefficient. The method further comprises: determining a sensitivity matrix of the inversion model, temperature of a measuring point, and a regularization factor; 4. The method of claim 1, wherein the method is characterized by: adjusting the sensitivity matrix, temperature of a measuring point, and a regularization factor based on the weighting coefficient to obtain the objective function. The method further comprises: performing transpose processing on the sensitivity matrix to obtain a processed matrix; 5. The method of claim 1, wherein the method is characterized by: calculating the initial heat source distribution of the cable and its accessories based on the weighting coefficient in the objective function and the processed matrix. The method further comprises: calculating a target temperature distribution of the cable and its accessories based on the target heat source distribution by using the forward model; if a temperature difference between the target temperature distribution and a measured temperature distribution is less than or equal to the preset temperature difference threshold value, determining that the target heat source distribution satisfies the preset condition.

6. The method of claim 1, wherein the method is characterized by: The fault diagnosis of the cable and the accessory thereof based on the target heat source distribution and the forward model comprises: calculating a target temperature distribution corresponding to the target heat source distribution by using the forward model; performing fault diagnosis of the cable and the accessory thereof based on the target temperature distribution and position information where the target temperature distribution is located.

7. An on-line fault diagnostic system for cables and their accessories, characterized in that The system comprises: a construction module configured to construct a target function of an inversion model based on distances from any unit in the inversion model to measurement points of the cable and the accessory thereof, comprising: determining a weighting coefficient based on the distances from any unit in the inversion model to the measurement points of the cable and the accessory thereof; constructing the target function of the inversion model based on the weighting coefficient; a first determination module configured to determine a sensitivity matrix of the inversion model based on a stiffness matrix corresponding to a temperature field of the cable and the accessory thereof, comprising: calculating the temperature field of the cable and the accessory thereof by using finite elements to obtain the stiffness matrix; determining a derivative of a temperature of any measurement point with respect to a heat source density based on the stiffness matrix; determining the sensitivity matrix of the inversion model based on the derivative of the temperature of any measurement point with respect to the heat source density; a second determination module configured to determine an initial heat source distribution of the cable and the accessory thereof based on the sensitivity matrix and the target function; a forward module configured to determine an initial temperature distribution of the cable and the accessory thereof based on the initial heat source distribution by using a forward model; an iterative updating module configured to iteratively update the initial heat source distribution based on a temperature difference between the initial temperature distribution and a measured temperature distribution until a target heat source distribution satisfying a preset condition is obtained, comprising: determining whether the temperature difference is greater than a preset temperature difference threshold value; if the temperature difference is greater than the preset temperature difference threshold value, performing inversion calculation of a heat source correction value of the cable and the accessory thereof by using a regularization or singular value decomposition algorithm; iteratively updating the initial heat source distribution based on the heat source correction value until the target heat source distribution satisfying the preset condition is obtained; a diagnosis module configured to perform fault diagnosis of the cable and the accessory thereof based on the target heat source distribution and the forward model.

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