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

Abstract

The invention relates to the technical field of data processing, and provides an industrial control mainboard multi-interface management method and device, equipment and a storage medium. Obtaining an interface operation data information set in a preset time period; judging whether an interface fault exists or not based on the interface operation data information set; if yes, 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; and 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. According to the method, through multi-dimensional feature extraction and correlation analysis, the problem that multi-interface associated faults cannot be detected in the prior art is solved, and the accuracy of interface fault detection and diagnosis is remarkably improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a method, device, equipment and storage medium for managing multiple interfaces of an industrial control motherboard. Background Art

[0002] With the continuous improvement of industrial automation, industrial control motherboards, as the core components of industrial control systems, play an increasingly important role. Industrial control motherboards usually have multiple types of interfaces, such as serial ports, USB ports, Ethernet ports, PCIe ports, etc., which are used to connect 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 complex industrial environments, industrial control motherboards often face adverse conditions such as high temperature, high humidity, and electromagnetic interference, which increase the probability of interface failure. Interface failure may cause data transmission interruption, equipment failure, and even cause 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, which cannot detect failures caused by the correlation between multiple interfaces. Summary of the invention

[0004] The present application provides a method, device, equipment and storage medium for managing multiple interfaces of an industrial control motherboard to solve the problems raised by the above background technology.

[0005] In a first aspect, the present application provides a method for managing multiple interfaces of an industrial control motherboard, comprising: Acquire 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 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; 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; A potential fault diagnosis report is generated based on the interface operation data information set, the first correlation coefficient information, and the second correlation coefficient information.

[0006] In a possible implementation, 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 of the interface operation data information set to generate an interface feature matrix includes: 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.

[0007] In a possible implementation, 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.

[0008] 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 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.

[0009] In a possible implementation manner, the 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: 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.

[0010] 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: 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.

[0011] In a second aspect, the present application provides an industrial control motherboard multi-interface management device, comprising: An acquisition module, used to acquire 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 mainboard; A judgment module, used for judging whether there is an interface fault based on the interface operation data information set; A feature extraction module, used for performing multi-dimensional feature extraction on 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 a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information and the second correlation coefficient information.

[0012] In a third aspect, the present application provides a terminal device, comprising 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 multi-interface management method for an industrial control motherboard as described in any one of the above items is implemented.

[0013] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the multi-interface management method for an industrial control motherboard as described in any one of the above items is implemented.

[0014] The present application provides a method, device, equipment and storage medium for managing multiple interfaces of an industrial control motherboard. The method includes: obtaining 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 motherboard; judging whether there is an interface fault based on the interface operation data information set; if so, performing multidimensional 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 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 a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information and the second correlation coefficient information. The method successfully solves the problem of being unable to detect multi-interface associated faults in the prior art through multidimensional feature extraction and correlation analysis, and significantly improves the accuracy of interface fault detection and diagnosis. The method adapts to 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0016] Figure 1 A schematic diagram of a process flow of a multi-interface management method for an industrial control motherboard provided in an embodiment of the present application; Figure 2 A schematic block diagram of the structure of the multi-interface management device for an industrial control motherboard provided in an embodiment of the present application; Figure 3 A schematic block diagram of the structure of a terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0019] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0020] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0021] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0022] See also Figure 1 , Figure 1 A flow chart of a multi-interface management method for an industrial control motherboard provided in an embodiment of the present application is shown in FIG. Figure 1As shown, the multi-interface management method for an industrial control motherboard provided in the embodiment of the present application includes steps S1 to S6.

[0023] Step S1, obtaining 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 mainboard.

[0024] Among them, for each of the interfaces, the operating data information of the interface includes but is not limited to voltage, current, signal strength and data transmission rate.

[0025] Step S2: determine whether there is an interface fault based on the interface operation data information set.

[0026] Specifically, for each of the interfaces, standard operating data information of the interface is obtained from the database, the standard operating data information including operating parameter thresholds of various parameters, and for the operating parameter values ​​of each parameter of the operating data information of the interface, it is determined whether the operating parameter values ​​of the parameters are all within the operating parameter thresholds corresponding to the parameters; if not, it is determined that an interface fault exists.

[0027] Step S3: If it exists, perform multi-dimensional feature extraction on the interface operation data information set to generate an interface feature matrix.

[0028] Specifically, the operation data information of each of the interfaces includes operation parameter values ​​of multiple parameters within the preset time period, and step S3 includes the following steps: 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; the rows of the interface feature matrix represent different interfaces, and the columns represent different features; The step of 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 the following steps: 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 comprises the following steps: 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.

[0029] It can be understood that the method provided in step S3 can comprehensively reflect the operating status of each interface and improve the accuracy of interface fault diagnosis by performing multi-dimensional feature extraction on each of the parameters.

[0030] Step S4, 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 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.

[0031] Specifically, step S4 includes the following steps: 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; it can be understood that the plurality of two-dimensional combinations of row vectors include all possible two-dimensional combinations between each row vector; 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; it can be understood that the multiple two-dimensional combinations of column vectors include all possible two-dimensional combinations between the column vectors.

[0032] 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.

[0033] Specifically, step S5 includes the following steps: Generate initial potential fault diagnosis information based on the interface operation data information set; specifically, for each of the interfaces, 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 result of each of the interfaces constitutes the initial potential fault diagnosis information; wherein the fault diagnosis model is a pre-trained neural network model; 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.

[0034] Wherein, determining the potential fault diagnosis information of the target interface based on the initial potential fault diagnosis information and the second correlation coefficient information comprises the following steps: For each fault type of the initial potential fault diagnosis information, a target second correlation coefficient corresponding to the fault type is determined 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; 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; 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.

[0035] It can be understood that, in step S5, on the one hand, by analyzing the first correlation coefficient information between multiple interfaces, it is helpful to timely discover the fault propagation caused by the mutual influence between the interfaces, and avoid missed detection and misjudgment. On the other hand, by analyzing the second correlation coefficient information between each column vector, it is possible to identify the correlation between different fault types, reveal the causes and possible evolution trends of complex faults, and provide a more comprehensive reference for fault diagnosis.

[0036] The method provided in this embodiment successfully solves the problem that the prior art cannot detect multi-interface related faults through multi-dimensional feature extraction and correlation analysis, and significantly improves the accuracy of interface fault detection and diagnosis. The method is adapted to 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.

[0037] See also Figure 2 , Figure 2 A schematic block diagram of the structure of the industrial control motherboard multi-interface management device 100 provided in the embodiment of the present application is shown in FIG. Figure 2 As shown, the industrial control motherboard multi-interface management device 100 provided in the embodiment of the present application includes: The acquisition module 110 is used to acquire 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 mainboard.

[0038] The judgment module 120 is used to judge whether there is an interface fault based on the interface operation data information set.

[0039] The feature extraction module 130 is used to extract multi-dimensional features from the interface operation data information set to generate an interface feature matrix if an interface fault exists.

[0040] The first generation module 140 is used 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 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.

[0041] The second generating module 150 is used 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.

[0042] It should be noted that technical personnel in the relevant technical field can clearly understand that for the convenience and conciseness of description, the specific working process of the above-described device and each module can refer to the corresponding process in the aforementioned industrial control motherboard multi-interface management method embodiment, and will not be repeated here.

[0043] The industrial control motherboard multi-interface management device 100 provided in the above embodiment can be implemented in the form of a computer program. The computer program can be used in Figure 3 The system is run on the terminal device 200 shown.

[0044] See also Figure 3 , Figure 3The present invention provides a schematic block diagram of the structure of a terminal device 200 according to an 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 via a device bus 203, wherein the memory 202 may include a non-volatile storage medium and an internal memory.

[0045] The non-volatile storage medium can store a computer program. The computer program includes program instructions, and when the program instructions are executed by the processor 201, the processor 201 can execute any of the above-mentioned industrial control motherboard multi-interface management methods.

[0046] The processor 201 is used to provide computing and control capabilities to support the operation of the entire terminal device 200.

[0047] 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 execute any of the above-mentioned industrial control motherboard multi-interface management methods.

[0048] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the terminal device 200 involved in the scheme of the present application. The specific terminal device 200 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0049] 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 (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) 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.

[0050] In some embodiments, the processor 201 is used to run a computer program stored in the memory to implement the following steps: Acquire 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 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; 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; A potential fault diagnosis report is generated based on the interface operation data information set, the first correlation coefficient information, and the second correlation coefficient information.

[0051] It should be noted that technicians in the relevant field can clearly understand that for the convenience and simplicity of description, the specific working process of the terminal device 200 described above can refer to the corresponding process of the aforementioned industrial control motherboard multi-interface management method, and will not be repeated here.

[0052] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by one or more processors, the one or more processors implement the industrial control motherboard multi-interface management method provided in the embodiment of the present application.

[0053] The computer-readable storage medium may be an internal storage unit of the terminal device 200 in the aforementioned embodiment, such as a 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 memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped with the terminal device 200.

[0054] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for managing multiple interfaces of an industrial control motherboard, characterized in that: include: Acquire 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 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; 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; A potential fault diagnosis report is generated based on the interface operation data information set, the first correlation coefficient information, and the second correlation coefficient information.

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 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: 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.

6. The method for managing multiple interfaces of an industrial control motherboard according to claim 5, 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.

7. A multi-interface management device for an industrial control motherboard, characterized in that: include: An acquisition module, used to acquire 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 mainboard; 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 a potential fault diagnosis report based on the interface operation data information set, the first correlation coefficient information and the second correlation coefficient information.

8. 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 6 is implemented.

9. 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 industrial control motherboard multi-interface management method according to any one of claims 1 to 6 is implemented.

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