Industrial control motherboard multi-interface management method, device, equipment and storage medium

Abstract

The present application relates to the technical field of data processing, and provides a multi-interface management method, device, equipment and storage medium for industrial control mainboards. Obtain an interface operation data information set within a preset time period; determine whether there is an interface fault based on the interface operation data information set; if there is, perform multi-dimensional feature extraction on the interface operation data information set to generate an interface feature matrix; generate first correlation coefficient information and second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generation method; generate a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information and the second correlation coefficient information. This method solves the problem in the prior art that multi-interface associated faults cannot be detected through multi-dimensional feature extraction and correlation analysis, and significantly improves the accuracy of interface fault detection and diagnosis.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly relates to a multi-interface management method, device, equipment and storage medium for industrial control mainboards. Background Technique

[0002] With the continuous improvement of industrial automation, industrial control mainboards, as the core components of industrial control systems, play an increasingly important role. Industrial control mainboards usually have various types of interfaces, such as serial ports, USB interfaces, Ethernet interfaces, PCIe interfaces, etc., for connecting various external devices and sensors. The stable operation of these interfaces directly affects the reliability and efficiency of the entire industrial control system.

[0003] In a complex industrial environment, industrial control mainboards often face adverse conditions such as high temperature, high humidity, and electromagnetic interference, resulting in an increased probability of interface failures. Interface failures may cause data transmission interruptions, equipment malfunctions, and even serious safety accidents. Therefore, how to detect and diagnose interface failures in a timely and accurate manner has become an urgent problem to be solved in the field of industrial control. Existing interface management methods usually use simple threshold detection to detect interface failures and cannot detect failures caused by the correlation between multiple interfaces. Summary of the Invention

[0004] This application provides a multi-interface management method, device, equipment and storage medium for industrial control mainboards to solve the problems raised in the above background technique.

[0005] In a first aspect, this application provides a multi-interface management method for industrial control mainboards, including:

[0006] Obtain an interface operation data information set within a preset time period; wherein, the interface operation data information set includes the operation data information of each interface of the industrial control mainboard;

[0007] Based on the interface operation data information set, determine whether there is an interface failure;

[0008] If there is, perform multi-dimensional feature extraction on the interface operation data information set to generate an interface feature matrix;

[0009] Generate first correlation coefficient information and second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generation method; wherein, the first correlation coefficient information is the correlation coefficient information corresponding to the row vectors of the interface feature matrix, and the second correlation coefficient information is the correlation coefficient information corresponding to the column vectors of the interface feature matrix;

[0010] Generate a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information and the second correlation coefficient information.

[0011] In a possible implementation, the operation data information of each of the interfaces includes the operation parameter values of multiple parameters within the preset time period. The multi-dimensional feature extraction of the interface operation data information set to generate an interface feature matrix includes:

[0012] For each of the interfaces, perform multi-dimensional feature extraction on each parameter of the operation data information corresponding to the interface to obtain the feature vectors corresponding to the parameters of the operation data information, and arrange the feature vectors in sequence based on a preset sorting method to obtain the target feature vector corresponding to the interface;

[0013] Arrange the target feature vectors in sequence from top to bottom to obtain the interface feature matrix.

[0014] In a possible implementation, the performing multi-dimensional feature extraction on each parameter of the operation data information corresponding to the interface to obtain the feature vectors corresponding to the parameters of the operation data information includes:

[0015] For each of the parameters, perform normalization processing on the operation parameter value corresponding to the parameter to obtain the normalized data corresponding to the parameter, and perform multi-dimensional feature extraction on the normalized data to obtain the feature vector corresponding to the parameter;

[0016] Wherein, the performing multi-dimensional feature extraction on the normalized data to obtain the feature vector corresponding to the parameter includes:

[0017] Obtain the average value of the normalized data;

[0018] Perform Fourier transform on the normalized data to obtain the fundamental frequency amplitude corresponding to the normalized data;

[0019] Perform wavelet transform on the normalized data to obtain the wavelet detail energy corresponding to the normalized data;

[0020] Arrange the average value, the fundamental frequency amplitude, and the wavelet detail energy in sequence to obtain the feature vector corresponding to the parameter.

[0021] In a possible implementation, the generating the first correlation coefficient information and the second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generation method includes:

[0022] Perform two-dimensional combination on each row vector of the interface feature matrix to obtain multiple two-dimensional combinations of row vectors, and respectively obtain the Pearson correlation coefficients of each two-dimensional combination of row vectors to obtain the first correlation coefficient information;

[0023] Perform two-dimensional combinations on each column vector of the interface feature matrix to obtain multiple two-dimensional combinations of column vectors, and respectively obtain the Pearson correlation coefficients of each two-dimensional combination of column vectors to obtain the second correlation coefficient information.

[0024] In a possible implementation manner, generating a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information, and the second correlation coefficient information includes:

[0025] Generate initial potential fault diagnosis information based on the interface operation data information set;

[0026] For each of the interfaces, based on the initial potential fault diagnosis information, determine whether the interface has a fault. If so, determine a target first correlation coefficient in the first correlation coefficient information, where the target first correlation coefficient is the correlation coefficient between the target feature vector corresponding to the interface and the target feature vectors corresponding to other interfaces;

[0027] For each of the target first correlation coefficients, compare the absolute value of the target first correlation coefficient with a preset absolute value; if the absolute value of the target first correlation coefficient is not less than the preset absolute value, determine the interface corresponding to the target first correlation coefficient as the target interface;

[0028] For each of the target interfaces, based on the initial potential fault diagnosis information and the second correlation coefficient information, determine the potential fault diagnosis information of the target interface; the potential fault diagnosis information of each of the target interfaces constitutes the potential fault diagnosis report.

[0029] In a possible implementation manner, determining the potential fault diagnosis information of the target interface based on the initial potential fault diagnosis information and the second correlation coefficient information includes:

[0030] For each fault type of the initial potential fault diagnosis information, determine a target second correlation coefficient corresponding to the fault type in the second correlation coefficient; where the target second correlation coefficient is the correlation coefficient between the column vector corresponding to the fault type and the column vectors corresponding to other fault types;

[0031] For each of the target second correlation coefficients, compare the absolute value of the target second correlation coefficient with a preset absolute value; if the absolute value of the target second correlation coefficient is not less than the preset absolute value, determine the fault type corresponding to the column vector corresponding to the target second correlation coefficient as a potential fault; each of the potential faults constitutes the potential fault diagnosis information of the target interface.

[0032] In a second aspect, the present application provides an industrial control motherboard multi-interface management device, including:

[0033] An acquisition module, configured to acquire a set of interface operation data information within a preset time period; wherein, the set of interface operation data information includes operation data information of each interface of an industrial control main board;

[0034] A judgment module, configured to judge whether there is an interface fault based on the set of interface operation data information;

[0035] A feature extraction module, configured to perform multi-dimensional feature extraction on the set of interface operation data information to generate an interface feature matrix if there is an interface fault;

[0036] A first generation module, configured to generate first correlation coefficient information and second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generation method; wherein, the first correlation coefficient information is the correlation coefficient information corresponding to the row vectors of the interface feature matrix, and the second correlation coefficient information is the correlation coefficient information corresponding to the column vectors of the interface feature matrix;

[0037] A second generation module, configured to generate a potential fault diagnosis report based on the set of interface operation data information, the first correlation coefficient information, and the second correlation coefficient information.

[0038] In a third aspect, the present application provides a terminal device, which includes a processor, a memory, and a computer program stored on the memory and executable by the processor. When the computer program is executed by the processor, the multi-interface management method for an industrial control main board described in any one of the above is implemented.

[0039] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the multi-interface management method for an industrial control main board described in any one of the above is implemented.

[0040] The present application provides a multi-interface management method, device, equipment and storage medium for an industrial control mainboard. The method includes: obtaining an interface operation data information set within a preset time period; wherein, the interface operation data information set includes the operation data information of each interface of the industrial control mainboard; determining whether there is an interface fault based on the interface operation data information set; if so, performing multi-dimensional feature extraction on the interface operation data information set to generate an interface feature matrix; generating first correlation coefficient information and second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generation method; wherein, the first correlation coefficient information is the correlation coefficient information corresponding to the row vectors of the interface feature matrix, and the second correlation coefficient information is the correlation coefficient information corresponding to the column vectors of the interface feature matrix; generating a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information and the second correlation coefficient information. This method successfully solves the problem in the prior art that multi-interface associated faults cannot be detected through multi-dimensional feature extraction and correlation analysis, and significantly improves the accuracy of interface fault detection and diagnosis. This method meets the application requirements in a complex industrial environment, reduces labor costs, enhances the reliability and security of the system, and has important practical significance and application value in the field of industrial automation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0042] Figure 1 It is a schematic flowchart of the multi-interface management method for the industrial control mainboard provided by the embodiment of the present application;

[0043] Figure 2 It is a schematic block diagram of the structure of the multi-interface management device for the industrial control mainboard provided by the embodiment of the present application;

[0044] Figure 3 It is a schematic block diagram of the structure of the terminal device provided by the embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the protection scope of the present invention.

[0046] The flowcharts shown in the accompanying drawings are merely illustrative examples and do not necessarily include all content and operations / steps, nor do they have to be executed in the order described. For example, some operations / steps can be decomposed, combined, or partially merged, so the actual execution order may change according to the actual situation.

[0047] It should also be understood that the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. As used in the specification of this application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0048] It should be further understood that the term "and / or" used in the specification of this application and the appended claims refers to any combination and all possible combinations of one or more of the related listed items, and includes these combinations.

[0049] The following will, with reference to the accompanying drawings, elaborate on some embodiments of this application. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0050] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of the multi-interface management method for an industrial control mainboard provided by an embodiment of this application. As Figure 1 shown, the multi-interface management method for an industrial control mainboard provided by an embodiment of this application includes steps S1 to S6.

[0051] Step S1: Obtain an interface operation data information set within a preset time period; wherein, the interface operation data information set includes the operation data information of each interface of the industrial control mainboard.

[0052] Among them, for each of the interfaces, the operation data information of the interface includes, but is not limited to, voltage, current, signal strength, and data transmission rate.

[0053] Step S2: Based on the interface operation data information set, determine whether there is an interface failure.

[0054] Specifically, for each of the interfaces, obtain the standard operation data information of the interface in the database. The standard operation data information includes the operation parameter thresholds of each parameter. For the operation parameter values of each parameter of the operation data information of the interface, determine whether the operation parameter values of the parameters are all within the corresponding operation parameter thresholds. If not, it is determined that there is an interface failure.

[0055] Step S3: If there is, perform multi-dimensional feature extraction on the interface operation data information set to generate an interface feature matrix.

[0056] Specifically, the operation data information of each of the interfaces includes the operation parameter values of multiple parameters within the preset time period, and step S3 includes the following steps:

[0057] For each of the interfaces, perform multi-dimensional feature extraction on each parameter of the operation data information corresponding to the interface to obtain the feature vectors corresponding to the parameters of the operation data information, and arrange the feature vectors in sequence based on a preset sorting method to obtain the target feature vector corresponding to the interface;

[0058] Arrange the target feature vectors in sequence from top to bottom to obtain the interface feature matrix; the rows of the interface feature matrix represent different interfaces, and the columns represent different features;

[0059] Among them, the performing multi-dimensional feature extraction on each parameter of the operation data information corresponding to the interface to obtain the feature vectors corresponding to the parameters of the operation data information includes the following steps:

[0060] For each of the parameters, perform normalization processing on the operation parameter value corresponding to the parameter to obtain the normalized data corresponding to the parameter, and perform multi-dimensional feature extraction on the normalized data to obtain the feature vector corresponding to the parameter;

[0061] Among them, the performing multi-dimensional feature extraction on the normalized data to obtain the feature vector corresponding to the parameter includes the following steps:

[0062] Obtain the average value of the normalized data;

[0063] Perform Fourier transform on the normalized data to obtain the fundamental frequency amplitude corresponding to the normalized data;

[0064] Perform wavelet transform on the normalized data to obtain the wavelet detail energy corresponding to the normalized data;

[0065] Arrange the average value, the fundamental frequency amplitude, and the wavelet detail energy in sequence to obtain the feature vector corresponding to the parameter.

[0066] It can be understood that the method provided in step S3 can comprehensively reflect the operation status of each interface by performing multi-dimensional feature extraction on each of the parameters, improving the accuracy of interface fault diagnosis.

[0067] Step S4: Generate the first correlation coefficient information and the second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generation method; wherein, the first correlation coefficient information is the correlation coefficient information corresponding to the row vectors of the interface feature matrix, and the second correlation coefficient information is the correlation coefficient information corresponding to the column vectors of the interface feature matrix.

[0068] Specifically, step S4 includes the following steps:

[0069] Perform two-dimensional combinations on each row vector of the interface feature matrix to obtain a plurality of two-dimensional combinations of row vectors, and respectively obtain the Pearson correlation coefficients of each two-dimensional combination of row vectors to obtain the first correlation coefficient information; it can be understood that the plurality of two-dimensional combinations of row vectors include all possible two-dimensional combinations between each row vector;

[0070] Perform two-dimensional combinations on each column vector of the interface feature matrix to obtain a plurality of two-dimensional combinations of column vectors, and respectively obtain the Pearson correlation coefficients of each two-dimensional combination of column vectors to obtain the second correlation coefficient information; it can be understood that the plurality of two-dimensional combinations of column vectors include all possible two-dimensional combinations between each column vector.

[0071] Step S5, generate a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information, and the second correlation coefficient information.

[0072] Specifically, step S5 includes the following steps:

[0073] Generate initial potential fault diagnosis information based on the interface operation data information set; specifically, for each interface, input the operation data information corresponding to the interface into the fault diagnosis model corresponding to the interface to obtain the fault diagnosis result corresponding to the interface, and the fault diagnosis results of each interface constitute the initial potential fault diagnosis information; wherein, the fault diagnosis model is a neural network model that has been pre-trained.

[0074] For each interface, determine whether the interface has a fault based on the initial potential fault diagnosis information. If there is a fault, determine a target first correlation coefficient in the first correlation coefficient information, and the target first correlation coefficient is the correlation coefficient between the target feature vector corresponding to the interface and the target feature vectors corresponding to other interfaces;

[0075] For each target first correlation coefficient, compare the absolute value of the target first correlation coefficient with a preset absolute value; if the absolute value of the target first correlation coefficient is not less than the preset absolute value, determine the interface corresponding to the target first correlation coefficient as the target interface;

[0076] For each target interface, determine the potential fault diagnosis information of the target interface based on the initial potential fault diagnosis information and the second correlation coefficient information; the potential fault diagnosis information of each target interface constitutes the potential fault diagnosis report.

[0077] Among them, determining the potential fault diagnosis information of the target interface based on the initial potential fault diagnosis information and the second correlation coefficient information includes the following steps:

[0078] For each fault type of the initial potential fault diagnosis information, determine the target second correlation coefficient corresponding to the fault type in the second correlation coefficient; wherein, the target second correlation coefficient is the correlation coefficient between the column vector corresponding to the fault type and the column vectors corresponding to other fault types; specifically, a fault type sequence table is provided in the database, and each column of the fault type sequence table corresponds to a column vector of the interface feature matrix;

[0079] For each of the target second correlation coefficients, compare the absolute value of the target second correlation coefficient with a preset absolute value; if the absolute value of the target second correlation coefficient is not less than the preset absolute value, determine that the fault type corresponding to the column vector of the target second correlation coefficient is a potential fault; each of the potential faults constitutes the potential fault diagnosis information of the target interface.

[0080] It can be understood that in step S5, on the one hand, by analyzing the first correlation coefficient information between multiple interfaces, it helps to timely detect the fault propagation caused by the mutual influence between interfaces, avoiding missed detection and misjudgment. On the other hand, by analyzing the second correlation coefficient information between each column vector, the association relationship between different fault types can be identified, revealing the causes and possible evolution trends of complex faults, and providing a more comprehensive reference for fault diagnosis.

[0081] The method provided in this embodiment successfully solves the problem in the prior art that multi-interface associated faults cannot be detected through multi-dimensional feature extraction and correlation analysis, and significantly improves the accuracy of interface fault detection and diagnosis. This method meets the application requirements in complex industrial environments, reduces labor costs, enhances the reliability and security of the system, and has important practical significance and application value in the field of industrial automation.

[0082] Please refer to Figure 2 , Figure 2 which is a schematic block diagram of the structure of the industrial control mainboard multi-interface management device 100 provided in the embodiment of the present application. As Figure 2 shown, the industrial control mainboard multi-interface management device 100 provided in the embodiment of the present application includes:

[0083] An acquisition module 110, configured to acquire an interface operation data information set within a preset time period; wherein, the interface operation data information set includes the operation data information of each interface of the industrial control mainboard.

[0084] A judgment module 120, configured to judge whether there is an interface fault based on the interface operation data information set.

[0085] The feature extraction module 130 is configured to perform multi-dimensional feature extraction on the interface operation data information set to generate an interface feature matrix when there is an interface fault.

[0086] The first generation module 140 is configured to generate first correlation coefficient information and second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generation method; wherein, the first correlation coefficient information is the correlation coefficient information corresponding to the row vectors of the interface feature matrix, and the second correlation coefficient information is the correlation coefficient information corresponding to the column vectors of the interface feature matrix.

[0087] The second generation module 150 is configured to generate a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information, and the second correlation coefficient information.

[0088] It should be noted that those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described device and each module can refer to the corresponding processes in the foregoing embodiments of the multi-interface management method for an industrial control main board, and will not be elaborated herein.

[0089] The industrial control main board multi-interface management device 100 provided in the foregoing embodiment can be implemented in the form of a computer program, and this computer program can run on a terminal device 200 as Figure 3 shown.

[0090] Please refer to Figure 3 , Figure 3 , which is a schematic block diagram of the structure of the terminal device 200 provided in the embodiment of the present application. The terminal device 200 includes a processor 201 and a memory 202. The processor 201 and the memory 202 are connected through a device bus 203. Among them, the memory 202 may include a non-volatile storage medium and an internal memory.

[0091] The non-volatile storage medium can store a computer program. The computer program includes program instructions. When the program instructions are executed by the processor 201, the processor 201 can be caused to execute any of the above-described multi-interface management methods for an industrial control main board.

[0092] The processor 201 is configured to provide computing and control capabilities to support the operation of the entire terminal device 200.

[0093] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor 201, the processor 201 can be caused to execute any of the above-described multi-interface management methods for an industrial control main board.

[0094] Those skilled in the art can understand that Figure 3The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the terminal device 200 involved in the solution of this application. Specifically, the terminal device 200 may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0095] It should be understood that the processor 201 may be a central processing unit (CPU), and the processor 201 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0096] Among them, in some embodiments, the processor 201 is used to run a computer program stored in the memory to implement the following steps:

[0097] Obtain an interface operation data information set within a preset time period; wherein, the interface operation data information set includes operation data information of each interface of the industrial control main board;

[0098] Based on the interface operation data information set, determine whether there is an interface failure;

[0099] If there is, perform multi-dimensional feature extraction on the interface operation data information set to generate an interface feature matrix;

[0100] Generate first correlation coefficient information and second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generation method; wherein, the first correlation coefficient information is the correlation coefficient information corresponding to the row vector of the interface feature matrix, and the second correlation coefficient information is the correlation coefficient information corresponding to the column vector of the interface feature matrix;

[0101] Generate a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information and the second correlation coefficient information.

[0102] It should be noted that those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the terminal device 200 described above can refer to the corresponding process of the aforementioned multi-interface management method for industrial control main boards, which will not be elaborated here.

[0103] An embodiment of the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by one or more processors, the one or more processors are caused to implement the multi-interface management method for an industrial control main board provided by the embodiment of the present application.

[0104] Among them, the computer-readable storage medium may be an internal storage unit of the terminal device 200 in the foregoing embodiment, such as the hard disk or memory of the terminal device 200. The computer-readable storage medium may also be an external storage device of the terminal device 200, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped with the terminal device 200.

[0105] As described above, the above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for managing multiple interfaces of an industrial control motherboard, characterized in that: include: Obtaining interface operation data information set within a preset time period; Determining whether there is an interface fault based on the interface operation data information set; If so, performing multi-dimensional feature extraction on the interface operation data information set to generate an interface feature matrix; Generate first correlation coefficient information and second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generation method; wherein the first correlation coefficient information is the correlation coefficient information corresponding to the row vector of the interface feature matrix, and the second correlation coefficient information is the correlation coefficient information corresponding to the column vector of the interface feature matrix; generating initial potential fault diagnosis information based on the interface operation data information set; For each of the interfaces, judging whether the interface has a fault based on the initial potential fault diagnosis information, and if so, determining a target first correlation coefficient in the first correlation coefficient information, where the target first correlation coefficient is a correlation coefficient between a target feature vector corresponding to the interface and target feature vectors corresponding to other interfaces; For each of the target first correlation coefficients, comparing the absolute value of the target first correlation coefficient with a preset absolute value; if the absolute value of the target first correlation coefficient is not less than the preset absolute value, determining that the interface corresponding to the target first correlation coefficient is the target interface; For each of the target interfaces, the potential fault diagnosis information of the target interface is determined based on the initial potential fault diagnosis information and the second correlation coefficient information; the potential fault diagnosis information of each of the target interfaces constitutes the potential fault diagnosis report.

2. The method for managing multiple interfaces of an industrial control motherboard according to claim 1, characterized in that: The operation data information of each of the interfaces includes operation parameter values ​​of multiple parameters within the preset time period, and the multi-dimensional feature extraction is performed on the interface operation data information set to generate an interface feature matrix, including: For each of the interfaces, multi-dimensional feature extraction is performed on each parameter of the operation data information corresponding to the interface to obtain a feature vector corresponding to each parameter of the operation data information, and each of the feature vectors is arranged in sequence based on a preset sorting method to obtain a target feature vector corresponding to the interface; Arrange the target feature vectors in order from top to bottom to obtain the interface feature matrix.

3. The method for managing multiple interfaces of an industrial control motherboard according to claim 2, characterized in that: The performing multi-dimensional feature extraction on each parameter of the operation data information corresponding to the interface to obtain a feature vector corresponding to each parameter of the operation data information includes: For each of the parameters, normalizing the operating parameter value corresponding to the parameter to obtain normalized data corresponding to the parameter, and performing multi-dimensional feature extraction on the normalized data to obtain a feature vector corresponding to the parameter; The step of performing multi-dimensional feature extraction on the normalized data to obtain a feature vector corresponding to the parameter includes: Obtaining an average value of the normalized data; Performing Fourier transform on the normalized data to obtain a fundamental frequency amplitude corresponding to the normalized data; Performing wavelet transform on the normalized data to obtain wavelet detail energy corresponding to the normalized data; The average value, the fundamental frequency amplitude and the wavelet detail energy are arranged in sequence to obtain a feature vector corresponding to the parameter.

4. The method for managing multiple interfaces of an industrial control motherboard according to claim 1, characterized in that: The generating of the first correlation coefficient information and the second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generating method includes: Performing a two-dimensional combination on each row vector of the interface feature matrix to obtain a plurality of two-dimensional combinations of row vectors, and respectively obtaining the Pearson correlation coefficient of each two-dimensional combination of row vectors to obtain the first correlation coefficient information; Perform two-dimensional combinations on the column vectors of the interface feature matrix to obtain multiple two-dimensional combinations of column vectors, and obtain the Pearson correlation coefficient of each two-dimensional combination of column vectors to obtain the second correlation coefficient information.

5. The method for managing multiple interfaces of an industrial control motherboard according to claim 1, characterized in that: The determining the potential fault diagnosis information of the target interface based on the initial potential fault diagnosis information and the second correlation coefficient information includes: For each fault type of the initial potential fault diagnosis information, determine a target second correlation coefficient corresponding to the fault type in the second correlation coefficient; wherein the target second correlation coefficient is a correlation coefficient between a column vector corresponding to the fault type and a column vector corresponding to other fault types; For each of the target second correlation coefficients, the absolute value of the target second correlation coefficient is compared with the preset absolute value; if the absolute value of the target second correlation coefficient is not less than the preset absolute value, the fault type corresponding to the column vector corresponding to the target second correlation coefficient is determined to be a potential fault; each of the potential faults constitutes the potential fault diagnostic information of the target interface.

6. A multi-interface management device for an industrial control motherboard, characterized in that: include: An acquisition module is used to acquire an interface operation data information set within a preset time period; A judgment module, used for judging whether there is an interface fault based on the interface operation data information set; A feature extraction module is used to extract multi-dimensional features from the interface operation data information set to generate an interface feature matrix if an interface fault occurs; A first generating module, used to generate first correlation coefficient information and second correlation coefficient information corresponding to the interface feature matrix based on a preset correlation coefficient generating method; wherein the first correlation coefficient information is the correlation coefficient information corresponding to the row vector of the interface feature matrix, and the second correlation coefficient information is the correlation coefficient information corresponding to the column vector of the interface feature matrix; The second generating module is used to generate initial potential fault diagnosis information based on the interface operation data information set; for each of the interfaces, determine whether the interface has a fault based on the initial potential fault diagnosis information, and if so, determine a target first correlation coefficient in the first correlation coefficient information, wherein the target first correlation coefficient is the correlation coefficient between the target feature vector corresponding to the interface and the target feature vectors corresponding to other interfaces; for each of the target first correlation coefficients, compare the absolute value of the target first correlation coefficient with a preset absolute value; if the absolute value of the target first correlation coefficient is not less than the preset absolute value, determine that the interface corresponding to the target first correlation coefficient is the target interface; for each of the target interfaces, determine the potential fault diagnosis information of the target interface based on the initial potential fault diagnosis information and the second correlation coefficient information; the potential fault diagnosis information of each of the target interfaces constitutes the potential fault diagnosis report.

7. A terminal device, characterized in that: The terminal device includes a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the industrial control motherboard multi-interface management method as described in any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the multi-interface management method for an industrial control motherboard according to any one of claims 1 to 5 is implemented.

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