Fault diagnosis method for communication countermeasure equipment
By smoothly filtering and short-time Fourier transforming the fault monitoring data of communication countermeasure equipment, converting it into frequency domain data and arranging and averaging, the problem of low fault detection rate in the prior art is solved, and more efficient fault diagnosis is achieved.
Patent Information
- Application Number
- CN202510240267.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2024-12-30
- Filing Date
- 2025-03-03
- Publication Date
- 2025-06-20
AI Technical Summary
The fault detection rate of existing communications countermeasures equipment is low, the diagnosis is time-consuming and the fault feature extraction is inconvenient.
By obtaining multiple fault monitoring data at multiple test moments, a time domain data matrix is constructed, smooth filtering and short-time Fourier transform are performed, and converted into a frequency domain data matrix, arranged from large to small frequency, and averaged the elements of the arranged frequency domain data matrix to determine the fault diagnosis results.
It improves the fault detection rate and isolation rate of communication countermeasures equipment, shortens the diagnosis time, and enhances the convenience of extracting fault characteristics.
Smart Images
Figure CN120180322A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of fault diagnosis of communication countermeasure equipment, and particularly to a fault diagnosis method for communication countermeasure equipment. Background Art
[0002] When detecting faults in communication countermeasure equipment, the commonly used method is to process the collected data in the time domain to complete fault diagnosis. However, the large amount of data in the time domain will lead to long diagnosis time, inconvenient extraction of fault features, and ultimately problems such as low fault detection rate and low fault isolation rate. Summary of the Invention
[0003] The purpose of this application is to provide a fault diagnosis method for communication countermeasure equipment to solve the problem of low fault detection rate of communication countermeasure equipment.
[0004] To achieve the above purpose, this application provides the following solutions:
[0005] In a first aspect, this application provides a fault diagnosis method for communication countermeasure equipment, including:
[0006] Obtain various fault monitoring data at multiple test times of the communication countermeasure equipment to obtain a time-domain data matrix; the communication countermeasure equipment includes: a reconnaissance unit, an identification unit, and an interference unit; the rows of the fault monitoring data matrix represent test times, the columns represent the types of fault monitoring data, and the elements represent the fault monitoring data; the number of types of fault monitoring data is greater than 55;
[0007] Perform smoothing filtering on each element in the time-domain data matrix to obtain a smoothed time-domain data matrix;
[0008] Perform short-time Fourier transform on each element in the smoothed time-domain data matrix to obtain a frequency-domain data matrix;
[0009] Arrange all the elements in each row of the frequency-domain data matrix in descending order of frequency to obtain an arranged frequency-domain data matrix;
[0010] Calculate the average of all the elements in each column of the arranged frequency-domain data matrix to obtain an average value matrix; the number of rows in the average value matrix is 1;
[0011] Determine the fault diagnosis result of the communication countermeasure equipment according to the average value matrix.
[0012] Optionally, performing smoothing filtering on each element in the time-domain data matrix to obtain a smoothed time-domain data matrix includes:
[0013] Using the smoothing filter formula, perform smoothing filter processing on each element in the time-domain data matrix to obtain the smoothed time-domain data matrix; the smoothing filter formula includes:
[0014]
[0015] Where, is the element in the first row and the k-th column of the smoothed time-domain data matrix; x 1,k is the element in the first row and the k-th column of the time-domain data matrix; n is the number of test times; is the element in the i-th row and the k-th column of the smoothed time-domain data matrix; x i-1,k is the element in the (i - 1)-th row and the k-th column of the time-domain data matrix; x i+1,k is the element in the (i + 1)-th row and the k-th column of the time-domain data matrix; m is the number of types of fault monitoring data; is the element in the m-th row and the k-th column of the smoothed time-domain data matrix; x m,k is the element in the m-th row and the k-th column of the time-domain data matrix.
[0016] Optionally, perform short-time Fourier transform on each element in the smoothed time-domain data matrix to obtain the frequency-domain data matrix, including:
[0017] Using the short-time Fourier transform formula, perform short-time Fourier transform on each element in the smoothed time-domain data matrix to obtain the frequency-domain data matrix; the short-time Fourier transform formula is:
[0018]
[0019] Where, is the element in the i-th row and the p-th column of the frequency-domain data matrix; is the element in the i-th row and the q-th column of the smoothed time-domain data matrix; e is the natural constant; j is the imaginary unit.
[0020] Optionally, calculate the average of all elements in each column of the arranged frequency-domain data matrix respectively to obtain the average value matrix, including:
[0021] Using the average value calculation formula, calculate the average of all elements in each column of the arranged frequency-domain data matrix respectively to obtain the average value matrix; the average value calculation formula is:
[0022]
[0023] Where, is the element in the p-th column of the average value matrix; is the element in the i-th row and the p-th column of the arranged frequency-domain data matrix.
[0024] Optionally, determining the fault diagnosis result of the communication countermeasure equipment according to the average value matrix includes:
[0025] Judging whether the number of first fault elements in the elements of the first column to the fifth column of the average value matrix is greater than 3 to obtain a first judgment result; the first fault element is an element with a value greater than 12;
[0026] If the first judgment result is yes, there is a fault in the reconnaissance unit;
[0027] Judging whether the number of second fault elements in the elements of the sixth column to the 27th column of the average value matrix is greater than 16 to obtain a second judgment result; the second fault element is an element with a value greater than 13;
[0028] If the second judgment result is yes, there is a fault in the recognition unit;
[0029] Judging whether the number of third fault elements in the elements of the 28th column to the nth column of the average value matrix is greater than 28 to obtain a third judgment result; the third fault element is an element with a value greater than 15;
[0030] If the first judgment result is yes, there is a fault in the interference unit.
[0031] In a second aspect, the present application provides a fault diagnosis system for a communication countermeasure equipment, which is used to implement the fault diagnosis method of the communication countermeasure equipment described in any one of the above, and the fault diagnosis system of the communication countermeasure equipment includes:
[0032] A data acquisition module, configured to obtain various fault monitoring data at multiple test times of the communication countermeasure equipment to obtain a time-domain data matrix; the communication countermeasure equipment includes: a reconnaissance unit, an identification unit, and an interference unit; the rows of the fault monitoring data matrix represent test times, the columns represent the types of fault monitoring data, and the elements represent the fault monitoring data; the number of types of fault monitoring data is greater than 55;
[0033] A filtering processing module, configured to perform smoothing filtering processing on each element in the time-domain data matrix to obtain a smoothed time-domain data matrix;
[0034] A Fourier transform module, configured to perform short-time Fourier transform on each element in the smoothed time-domain data matrix to obtain a frequency-domain data matrix;
[0035] An arrangement module, configured to arrange all the elements in each row of the frequency-domain data matrix in descending order of frequency to obtain an arranged frequency-domain data matrix;
[0036] An averaging module, which is used to average all elements of each column in the arranged frequency-domain data matrix respectively to obtain an average value matrix; the number of rows in the average value matrix is 1;
[0037] A fault diagnosis module, which is used to determine the fault diagnosis result of the communication countermeasure equipment according to the average value matrix.
[0038] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the fault diagnosis method of the communication countermeasure equipment described in any one of the above.
[0039] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the fault diagnosis method of the communication countermeasure equipment described in any one of the above.
[0040] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the fault diagnosis method of the communication countermeasure equipment described in any one of the above.
[0041] According to the specific embodiments provided by the present application, the following technical effects are disclosed in the present application:
[0042] The present application discloses a fault diagnosis method for a communication countermeasure equipment. First, multiple types of fault monitoring data at multiple test times of the communication countermeasure equipment are obtained to obtain a time-domain data matrix; then, each element in the time-domain data matrix is subjected to a smoothing filter process to obtain a smoothed time-domain data matrix; secondly, each element in the smoothed time-domain data matrix is subjected to a short-time Fourier transform to obtain a frequency-domain data matrix; subsequently, all elements of each row in the frequency-domain data matrix are arranged in descending order of frequency to obtain an arranged frequency-domain data matrix; again, all elements of each column in the arranged frequency-domain data matrix are averaged respectively to obtain an average value matrix; finally, the fault diagnosis result of the communication countermeasure equipment is determined according to the average value matrix. The present application transforms the smoothed time-domain data matrix into the frequency domain by means of a short-time Fourier transform to obtain a frequency-domain data matrix, utilizes the corresponding relationship between the frequency points and faults in the frequency-domain data, arranges all elements of each row in the frequency-domain data matrix in descending order of frequency respectively to obtain an arranged frequency-domain data matrix, and has the advantages of short diagnosis time, high fault detection rate, and high isolation rate for fault location to the reconnaissance unit, identification unit, and interference unit of the communication countermeasure equipment. Description of the Drawings
[0043] To more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the following will briefly introduce the accompanying drawings required for use in the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.
[0044] Figure 1 Schematic flow diagram of the fault diagnosis method for communication countermeasure equipment provided by an embodiment of the present application;
[0045] Figure 2 Schematic structural diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners
[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.
[0047] The purpose of the present application is to provide a fault diagnosis method for communication countermeasure equipment, aiming to improve the fault detection rate of communication countermeasure equipment.
[0048] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below with reference to the accompanying drawings and specific implementation manners.
[0049] In an exemplary embodiment, as Figure 1 shown, a fault diagnosis method for communication countermeasure equipment is provided, including:
[0050] Step 1: Obtain various fault monitoring data at multiple test times of the communication countermeasure equipment to obtain a time-domain data matrix.
[0051] Among them, the communication countermeasure equipment includes: a reconnaissance unit, an identification unit, and an interference unit; the rows of the fault monitoring data matrix represent the test times, the columns represent the types of fault monitoring data, and the elements represent the fault monitoring data; the number of types of fault monitoring data is greater than 55.
[0052] Specifically, the time-domain data matrix is expressed as:
[0053]
[0054] Among them, x i,p(i = 1, 2, …, m; p = 1, 2, …, n) is the element in the i-th row and p-th column of the time-domain data matrix, that is, the i-th type of fault monitoring data at the p-th test moment; m is the number of types of fault monitoring data; n is the number of test moments.
[0055] The fault monitoring data includes: scanning range, transmit power, receiver sensitivity, etc., and the fault monitoring data can be adjusted according to the actual situation.
[0056] Step 2: Perform smoothing filtering on each element in the time-domain data matrix to obtain the smoothed time-domain data matrix.
[0057] As an optional implementation manner, Step 2 includes:
[0058] Using the smoothing filter formula, perform smoothing filtering on each element in the time-domain data matrix to obtain the smoothed time-domain data matrix; the smoothing filter formula includes:
[0059]
[0060] Among them, is the element in the 1st row and k-th column of the smoothed time-domain data matrix; x 1,k is the element in the 1st row and k-th column of the time-domain data matrix; n is the number of test moments; is the element in the i-th row and k-th column of the smoothed time-domain data matrix; x i-1,k is the element in the (i - 1)-th row and k-th column of the time-domain data matrix; x i+1,k is the element in the (i + 1)-th row and k-th column of the time-domain data matrix; m is the number of types of fault monitoring data; is the element in the m-th row and k-th column of the smoothed time-domain data matrix; x m,k is the element in the m-th row and k-th column of the time-domain data matrix.
[0061] Specifically, the smoothed time-domain data matrix X 1 is expressed as:
[0062]
[0063] Among them, is the element in the i-th row and p-th column of the smoothed time-domain data matrix.
[0064] Step 3: Perform short-time Fourier transform on each element in the smoothed time-domain data matrix to obtain the frequency-domain data matrix.
[0065] As an optional implementation manner, Step 3 includes:
[0066] Using the short-time Fourier transform formula, perform the short-time Fourier transform on each element in the time-domain data matrix after smoothing filtering to obtain the frequency-domain data matrix; the short-time Fourier transform formula is:
[0067]
[0068] where, is the element in the \(i\)-th row and \(p\)-th column of the frequency-domain data matrix; is the element in the \(i\)-th row and \(q\)-th column of the time-domain data matrix after smoothing filtering; \(e\) is the natural constant; \(j\) is the imaginary unit.
[0069] Specifically, the frequency-domain data matrix \(X\) 2 is expressed as:
[0070]
[0071] where, is the element in the \(i\)-th row and \(p\)-th column of the frequency-domain data matrix.
[0072] Step 4: Arrange all the elements in each row of the frequency-domain data matrix in descending order of frequency to obtain the arranged frequency-domain data matrix.
[0073] Specifically, the arranged frequency-domain data matrix \(X\) 3 is expressed as:
[0074]
[0075] where, is the element in the \(i\)-th row and \(p\)-th column of the arranged frequency-domain data matrix.
[0076] Step 5: Calculate the average of all the elements in each column of the arranged frequency-domain data matrix to obtain the average value matrix.
[0077] Among them, the number of rows in the average value matrix is 1.
[0078] As an optional implementation manner, Step 5 includes:
[0079] Using the average value calculation formula, calculate the average of all the elements in each column of the arranged frequency-domain data matrix to obtain the average value matrix; the average value calculation formula is:
[0080]
[0081] where, is the element in the \(p\)-th column of the average value matrix; is the element in the \(i\)-th row and \(p\)-th column of the arranged frequency-domain data matrix.
[0082] Specifically, the average value matrix \(X\) 4Expressed as:
[0083]
[0084] Step 6: Determine the fault diagnosis result of the communication countermeasure equipment according to the average value matrix.
[0085] As an alternative implementation, Step 6 includes:
[0086] Judge whether the number of first fault elements among the elements in the 1st column to the 5th column of the average value matrix is greater than 3 to obtain a first judgment result; the first fault element is an element with a value greater than 12.
[0087] If the first judgment result is yes, the reconnaissance unit has a fault.
[0088] Judge whether the number of second fault elements among the elements in the 6th column to the 27th column of the average value matrix is greater than 16 to obtain a second judgment result; the second fault element is an element with a value greater than 13.
[0089] Step 6: If the second judgment result is yes, the recognition unit has a fault.
[0090] Judge whether the number of third fault elements among the elements in the 28th column to the nth column of the average value matrix is greater than 28 to obtain a third judgment result; the third fault element is an element with a value greater than 15.
[0091] If the first judgment result is yes, the jamming unit has a fault.
[0092] In an exemplary embodiment, a fault diagnosis system for a communication countermeasure equipment is provided, which is used to implement the fault diagnosis method of the communication countermeasure equipment. The fault diagnosis system of the communication countermeasure equipment includes:
[0093] A data acquisition module, configured to acquire various fault monitoring data at multiple test times of the communication countermeasure equipment to obtain a time-domain data matrix; the communication countermeasure equipment includes: a reconnaissance unit, a recognition unit, and a jamming unit; the rows of the fault monitoring data matrix represent the test times, the columns represent the types of fault monitoring data, and the elements represent the fault monitoring data; the number of types of fault monitoring data is greater than 55.
[0094] A filtering processing module, configured to perform smoothing filtering processing on each element in the time-domain data matrix to obtain a smoothed time-domain data matrix.
[0095] A Fourier transform module, configured to perform short-time Fourier transform on each element in the smoothed time-domain data matrix to obtain a frequency-domain data matrix.
[0096] An arrangement module, configured to arrange all elements in each row of a frequency-domain data matrix in descending order of frequency, so as to obtain an arranged frequency-domain data matrix.
[0097] An averaging module, configured to average all elements in each column of the arranged frequency-domain data matrix respectively, so as to obtain an average value matrix; the number of rows in the average value matrix is 1.
[0098] A fault diagnosis module, configured to determine a fault diagnosis result of a communication countermeasure device according to the average value matrix.
[0099] In an exemplary embodiment, a computer device is provided, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement a fault diagnosis method for a communication countermeasure device.
[0100] In an exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, a fault diagnosis method for a communication countermeasure device is implemented.
[0101] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, a fault diagnosis method for a communication countermeasure device is implemented.
[0102] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal, and its internal structure diagram may be as Figure 2 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with an external terminal through a network connection. When the computer program is executed by the processor, a fault diagnosis method for a communication countermeasure device is implemented.
[0103] Those skilled in the art can understand, Figure 2The 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 computer device to which the solution of this application is applied. Specifically, the computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.
[0104] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.
[0105] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.
[0106] The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., and are not limited thereto. The processors involved in the embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., and are not limited thereto.
[0107] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.
[0108] Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.
Claims
1. A method for diagnosing a fault of a communication countermeasure equipment, characterized in that: The fault diagnosis method of the communication countermeasure equipment comprises: Acquire multiple fault monitoring data of multiple test moments of communication countermeasure equipment to obtain a time domain data matrix; the communication countermeasure equipment includes: a reconnaissance unit, an identification unit and an interference unit; the rows of the fault monitoring data matrix represent the test moments, the columns represent the types of fault monitoring data, and the elements represent the fault monitoring data; the number of types of fault monitoring data is greater than 55; Performing smoothing filtering on each element in the time domain data matrix to obtain a smoothed filtered time domain data matrix; Perform short-time Fourier transform on each element in the time-domain data matrix after smoothing and filtering to obtain a frequency-domain data matrix; Arrange all elements of each row in the frequency domain data matrix in descending order of frequency to obtain an arranged frequency domain data matrix; Averaging all elements in each column of the arranged frequency domain data matrix to obtain an average value matrix; the number of rows in the average value matrix is 1; The fault diagnosis result of the communication countermeasure equipment is determined according to the average value matrix.
2. The method for diagnosing a fault of communication countermeasure equipment according to claim 1, characterized in that: Perform smoothing filtering on each element in the time domain data matrix to obtain a smoothed filtered time domain data matrix, including: Using a smoothing filter formula, each element in the time domain data matrix is smoothed and filtered to obtain a time domain data matrix after smoothing filtering; the smoothing filter formula includes: in, is the element in the 1st row and the kth column in the time domain data matrix after smoothing filtering; x 1,k is the element in the 1st row and the kth column in the time domain data matrix; n is the number of test moments; is the element in the i-th row and k-th column of the time domain data matrix after smoothing filtering; x i-1,k is the element in the i-1th row and kth column of the time domain data matrix; x i+1,k is the element in the i+1th row and kth column in the time domain data matrix; m is the number of types of fault monitoring data; is the element in the mth row and kth column of the time domain data matrix after smoothing filtering; x m,k is the element in the mth row and kth column in the time domain data matrix.
3. The method for diagnosing a fault of communication countermeasure equipment according to claim 2, characterized in that: Perform short-time Fourier transform on each element in the time domain data matrix after smoothing and filtering to obtain the frequency domain data matrix, including: Using the short-time Fourier transform formula, each element in the time domain data matrix after smoothing filtering is short-time Fourier transform to obtain a frequency domain data matrix; the short-time Fourier transform formula is: in, is the element in the i-th row and p-th column of the frequency domain data matrix; is the element in the i-th row and q-th column in the time domain data matrix after smoothing filtering; e is a natural constant; j is an imaginary unit.
4. The method for diagnosing a fault of communication countermeasure equipment according to claim 3, characterized in that: All elements in each column of the arranged frequency domain data matrix are averaged to obtain an average value matrix, including: The average value calculation formula is used to average all elements in each column of the arranged frequency domain data matrix to obtain an average value matrix; the average value calculation formula is: in, is the p-th column element in the mean value matrix; is the element in the i-th row and p-th column in the arranged frequency domain data matrix.
5. The method for diagnosing a fault of communication countermeasure equipment according to claim 1, characterized in that: Determining a fault diagnosis result of the communication countermeasure equipment according to the average value matrix includes: Determine whether the number of first fault elements in the elements of the 1st column to the 5th column of the average value matrix is greater than 3, and obtain a first determination result; the first fault element is an element whose value is greater than 12; If the first judgment result is yes, then the reconnaissance unit is faulty; Determine whether the number of second fault elements in the 6th column to the 27th column of the average value matrix is greater than 16, and obtain a second determination result; the second fault element is an element whose value is greater than 13; If the second judgment result is yes, then the identification unit has a fault; Determine whether the number of third fault elements in the elements of the 28th column to the nth column of the average value matrix is greater than 28, and obtain a third determination result; the third fault element is an element whose value is greater than 15; If the first judgment result is yes, then the interference unit is faulty.
6. A communication countermeasure equipment fault diagnosis system, used to implement the communication countermeasure equipment fault diagnosis method according to any one of claims 1 to 5, characterized in that: The fault diagnosis system of the communication countermeasure equipment includes: A data acquisition module is used to obtain multiple fault monitoring data of multiple test moments of the communication countermeasure equipment to obtain a time domain data matrix; the communication countermeasure equipment includes: a reconnaissance unit, an identification unit and an interference unit; the rows of the fault monitoring data matrix represent the test moments, the columns represent the types of fault monitoring data, and the elements represent the fault monitoring data; the number of types of fault monitoring data is greater than 55; A filtering processing module is used to perform smoothing filtering on each element in the time domain data matrix to obtain a time domain data matrix after smoothing filtering; The Fourier transform module is used to perform short-time Fourier transform on each element in the time domain data matrix after smoothing and filtering to obtain a frequency domain data matrix; An arrangement module is used to arrange all elements of each row in the frequency domain data matrix in descending order of frequency to obtain an arranged frequency domain data matrix; An averaging module is used to average all elements in each column of the arranged frequency domain data matrix to obtain an average value matrix; the number of rows in the average value matrix is 1; A fault diagnosis module is used to determine the fault diagnosis result of the communication countermeasure equipment according to the average value matrix.
7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the fault diagnosis method for the communication countermeasure equipment described in any one of claims 1-5.
8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the fault diagnosis method of the communication countermeasure equipment described in any one of claims 1-5.
9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, it implements the fault diagnosis method of the communication countermeasure equipment described in any one of claims 1-5.