Fault level determination method and device of communication equipment and electronic equipment

Abstract

The invention belongs to the technical field of fault diagnosis, and particularly discloses a method and device for determining the fault level of communication equipment and electronic equipment, and the method comprises the steps: obtaining historical operation fault data of communication equipment of the same type, and building a fault data set; constructing a circuit simulation model of each circuit board in the communication equipment of the same type, and expanding the fault data set based on the circuit simulation model; training a communication equipment residual life prediction model based on the fault data set; inputting the electric signal data of the target communication equipment into the trained communication equipment residual life prediction model to obtain a life prediction value; and determining the fault level of the target communication equipment based on the life prediction value and a preset threshold, and the method can improve the accuracy and reliability of determining the fault level of the communication equipment.

Description

Technical Field

[0001] The present application belongs to the technical field of fault diagnosis, and more specifically, relates to a method, device and electronic device for determining a fault level of communication equipment. Background Art

[0002] The existing technology for fault degree classification diagnosis generally requires multiple quantitative and qualitative classification indicators, and determines the fault level based on the fault type. However, for communication equipment, its component composition structure is complex, and there are many circuit boards for each functional module. Its failure mode and cause are diverse and uncertain, and the fault type cannot be fully predicted. Therefore, the accuracy and reliability of using the existing fault level determination method to determine the fault level of communication equipment are low. Summary of the invention

[0003] In view of the defects of the prior art, the purpose of the present application is to provide a method, device and electronic device for determining the fault level of communication equipment, aiming to solve the problem of low accuracy and reliability caused by the fault level determination method of the prior art being not suitable for communication equipment.

[0004] To achieve the above object, the present application provides a method for determining a fault level of a communication device, comprising:

[0005] Obtain historical operational fault data of the same type of communication equipment and establish a fault data set;

[0006] Constructing a circuit simulation model of each circuit board inside the same type of communication equipment, and expanding the fault data set based on the circuit simulation model;

[0007] Based on the fault data set, train the communication equipment remaining life prediction model;

[0008] Inputting the electrical signal data of the target communication equipment into the trained communication equipment remaining life prediction model to obtain a life prediction value;

[0009] Based on the life prediction value and a preset threshold, a failure level of the target communication equipment is determined.

[0010] According to the method for determining the fault level of communication equipment provided by the present invention, the method for obtaining the preset threshold value includes:

[0011] Obtaining a fault degree evaluation index value of the target communication equipment and a weight coefficient of each evaluation index;

[0012] Based on the fault degree evaluation index value and the weight coefficient, obtaining a comprehensive rating value of the fault degree of the target communication equipment;

[0013] According to the comprehensive rating index value of the degree of failure of each communication equipment of the same type, a fault degree classification threshold diagram is drawn to obtain two classification threshold inflection points, and the remaining life value of the communication equipment corresponding to each inflection point is used as the preset threshold.

[0014] According to the method for determining the fault level of communication equipment provided by the present invention, the method for obtaining the weight coefficient of each evaluation index includes:

[0015] Based on the number of the same type of communication equipment and the number of fault degree evaluation indicators, a weight coefficient of each evaluation indicator is obtained.

[0016] According to the method for determining the fault level of communication equipment provided by the present invention, the fault level includes three levels: severe, moderate and slight, the preset threshold includes a first preset threshold and a second preset threshold, wherein the first preset threshold is greater than the second preset threshold, and the method for determining the fault level of the target communication equipment based on the life prediction value and the preset threshold includes:

[0017] If the life prediction value is not greater than the second preset threshold, the fault level of the target communication equipment is a serious level; or,

[0018] If the life prediction value is greater than the second preset threshold value but not greater than the first preset threshold value, the fault level of the target communication equipment is a moderate level; or,

[0019] If the life prediction value is greater than the first preset threshold, the failure level of the target communication equipment is a minor level.

[0020] According to the method for determining the fault level of communication equipment provided by the present invention, the circuit simulation model of each circuit board inside the communication equipment of the same type is constructed, and the fault data set is expanded based on the circuit simulation model, including:

[0021] Building a circuit simulation model based on the circuit schematic drawings of each circuit board inside the same type of communication equipment;

[0022] Multiple types of faults are injected into the circuit simulation model, and fault data of the circuit simulation model under multiple fault types are collected and added to the fault data set.

[0023] According to the method for determining the fault level of communication equipment provided by the present invention, the remaining life prediction model of the communication equipment is a deep learning model based on a neural network.

[0024] In a second aspect, the present application provides a device for determining a fault level of communication equipment, comprising:

[0025] An acquisition module is used to acquire historical operation fault data of the same type of communication equipment and establish a fault data set;

[0026] An expansion module, used to construct a circuit simulation model of each circuit board inside the same type of communication equipment, and expand the fault data set based on the circuit simulation model;

[0027] A training module, used to train a communication equipment remaining life prediction model based on a fault data set;

[0028] A prediction module, used for inputting the electrical signal data of the target communication equipment into the trained communication equipment remaining life prediction model to obtain a life prediction value;

[0029] A determination module is used to determine the failure level of the target communication equipment based on the life prediction value and a preset threshold.

[0030] In a third aspect, the present application provides an electronic device comprising: at least one memory for storing programs; and at least one processor for executing the programs stored in the memory. When the programs stored in the memory are executed, the processor is used to execute the method for determining the fault level of communication equipment described in the first aspect or any possible implementation of the first aspect.

[0031] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method for determining the fault level of communication equipment described in the first aspect or any possible implementation of the first aspect.

[0032] In a fifth aspect, the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method for determining the fault level of communication equipment described in the first aspect or any possible implementation of the first aspect.

[0033] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0034] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the prior art:

[0035] (1) By training the remaining life prediction model based on fault data and using the remaining life to comprehensively characterize the multiple failure modes of communication equipment, the fault level is divided according to the predicted remaining life value, which can improve the accuracy and reliability of determining the fault level of communication equipment.

[0036] (2) By using the circuit simulation model to expand the fault data set, the difficulty in obtaining a large number of fault data samples during the actual operation of communication equipment can be solved, thereby improving the accuracy of the life prediction model. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 It is a flowchart of a method for determining a fault level of communication equipment provided in an embodiment of the present application;

[0039] Figure 2 It is a structural schematic diagram of a device for determining a fault level of communication equipment provided in an embodiment of the present application;

[0040] Figure 3 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0042] The term "and / or" in this article is a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The symbol " / " in this article indicates that the associated objects are in an or relationship, for example, A / B means A or B.

[0043] The terms "first" and "second" in the specification and claims herein are used to distinguish different objects rather than to describe a specific order of the objects. For example, a first response message and a second response message are used to distinguish different response messages rather than to describe a specific order of the response messages.

[0044] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0045] In the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more than two. For example, multiple processing units refer to two or more processing units, etc.; multiple elements refer to two or more elements, etc.

[0046] First, the following contents are introduced:

[0047] Communication equipment is a kind of equipment that uses electrical signals as the transmission medium. Its various functional modules are connected by multiple circuit boards in series and parallel to achieve the corresponding functions. Due to the complex and changeable working environment, high requirements are placed on its stability, reliability and safety during operation. Especially with the increase of running time, communication equipment is prone to frequent failures. Usually, the failure occurs on the circuit board, and it is not just a single failure. When a compound failure occurs, due to the high integration of the circuit board, it is often necessary to directly replace the circuit board. This post-maintenance method not only delays the equipment's mission execution, but also wastes a lot of manpower and material resources. If the occurrence of failures can be predicted in advance and the expected degree of failure can be judged, corresponding maintenance measures can be taken in time to carry out maintenance according to the situation, which is of great significance to the safe and reliable operation of communication equipment.

[0048] The existing technology for fault degree classification diagnosis generally requires multiple quantitative and qualitative classification indicators, and determines the fault level based on the fault type. However, for communication equipment, its component composition structure is complex, and there are many circuit boards for each functional module. Its failure mode and cause are diverse and uncertain, and the fault type cannot be fully predicted. Therefore, the accuracy and reliability of determining the fault level of communication equipment using the existing fault level determination method are low, and there is a lack of a method and system for accurately grading communication equipment faults.

[0049] In view of the above-mentioned defects, the purpose of the present application is to provide a method, device and electronic device for determining the fault level of communication equipment, aiming to solve the problem of low accuracy and reliability caused by the fault level determination method of the prior art being not applicable to communication equipment.

[0050] Next, combine Figure 1 A method for determining the fault level of communication equipment provided in an embodiment of the present application is introduced.

[0051] Figure 1 is a flow chart of a method for determining a fault level of a communication device provided in an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0052] Step 100, obtaining historical operation fault data of the same type of communication equipment and establishing a fault data set;

[0053] Optionally, the same type of communication equipment may be a plurality of vehicle-mounted communication equipment, or a plurality of other types of communication equipment, which is not limited in the present application.

[0054] Optionally, the historical operation fault data may be various electrical signal data of the communication equipment, such as voltage, current, power and other related parameters known to those skilled in the art, which is not limited in the present application.

[0055] Optionally, a fault data set may be established, and after acquiring historical operation fault data of the same type of communication equipment, the data may be stored in the fault data set.

[0056] Step 110, constructing a circuit simulation model of each circuit board inside the same type of communication equipment, and expanding the fault data set based on the circuit simulation model;

[0057] In order to solve the problem of difficulty in obtaining a large number of fault data samples during the actual operation of communication equipment, the present application constructs a circuit simulation model of each circuit board inside the same type of communication equipment, and expands the fault data set based on the circuit simulation model, thereby improving the accuracy of the life prediction model.

[0058] Step 120, training a communication equipment remaining life prediction model based on the fault data set;

[0059] The present application constructs a communication equipment remaining life prediction model, uses voltage, current, power and other data in a fault data set as input to the remaining life prediction model, and outputs the remaining life prediction value to train the communication equipment remaining life prediction model.

[0060] Through the communication equipment remaining life prediction model, the remaining life can be used to comprehensively characterize the multiple failure modes of the communication equipment to improve the accuracy and reliability of determining the failure level of the communication equipment.

[0061] Optionally, the communication equipment remaining life prediction model can be any deep learning model, which is not limited in this application.

[0062] Step 130, inputting the electrical signal data of the target communication equipment into the trained communication equipment remaining life prediction model to obtain a life prediction value;

[0063] After the communication equipment remaining life prediction model is trained, the electrical signal data of the communication equipment whose fault level is to be determined, such as current, voltage, power, etc., can be input into the trained communication equipment remaining life prediction model to obtain its output life prediction value.

[0064] Step 140: Determine the fault level of the target communication equipment based on the life prediction value and the preset threshold.

[0065] After obtaining the life prediction value, it can be compared with the preset threshold value, and the failure level of the target communication equipment can be determined based on the comparison result.

[0066] The method for determining the fault level of communication equipment provided by the present invention can improve the accuracy and reliability of determining the fault level of communication equipment by training a remaining life prediction model based on fault data, using the remaining life to comprehensively characterize the multiple fault modes of the communication equipment, and dividing the fault level by the predicted remaining life value. By expanding the fault data set using a circuit simulation model, the difficulty in obtaining a large number of fault data samples during the actual operation of the communication equipment can be solved, thereby improving the accuracy of the life prediction model.

[0067] In some embodiments, the method for obtaining the preset threshold in step 140 includes:

[0068] Step 141, obtaining the fault degree evaluation index value of the target communication equipment and the weight coefficient of each evaluation index;

[0069] Optionally, the fault degree evaluation index values ​​of the communication equipment may include combat readiness, mission success, maintenance costs, resource support costs, and the like.

[0070] After obtaining the fault degree evaluation index values, it is also necessary to obtain the weight coefficients corresponding to each evaluation index.

[0071] Step 142, based on the fault degree evaluation index value and the weight coefficient, obtaining a comprehensive rating value of the fault degree of the target communication equipment;

[0072] Specifically, the calculation formula for the comprehensive rating value of the fault degree is as follows:

[0073]

[0074] Among them, Q is the comprehensive index value, X j is the evaluation index value, r j is the weight coefficient, and n is the number of evaluation indicators.

[0075] Step 143, based on the comprehensive rating index value of the degree of failure of each communication equipment of the same type, a fault degree classification threshold diagram is drawn to obtain two classification threshold inflection points, and the remaining life value of the communication equipment corresponding to each inflection point is used as a preset threshold.

[0076] In some embodiments, the method of obtaining the weight coefficient of each evaluation indicator in step 141 includes:

[0077] Based on the number of communication equipment of the same type and the number of fault degree evaluation indicators, a weight coefficient of each evaluation indicator is obtained.

[0078] Specifically, the calculation formula for the weight coefficient of each evaluation index is as follows:

[0079]

[0080] Among them, r j is the weight coefficient, m is the number of communication devices of the same type, n is the number of fault degree evaluation indicators, and ξ ij is the correlation coefficient between the j-th indicator of the i-th communication device and the optimal value of this indicator, ρ is the discrimination coefficient, is the reference index sequence, is the sequence of indicators to be compared.

[0081] In some embodiments, the fault levels include three levels: severe, moderate, and minor, and the preset thresholds include a first preset threshold and a second preset threshold, where the first preset threshold is greater than the second preset threshold. Step 140 includes:

[0082] Step 1401, if the life prediction value is not greater than the second preset threshold, the fault level of the target communication device is the severe level; or,

[0083] Step 1402, if the life prediction value is greater than the second preset threshold but not greater than the first preset threshold, the fault level of the target communication device is the moderate level; or,

[0084] Step 1403, if the life prediction value is greater than the first preset threshold, the fault level of the target communication device is the minor level.

[0085] For example, set the second preset threshold and the first preset threshold to A and B respectively, and A < B. The fault levels are divided according to the following method: if the remaining life value output by the life prediction model is not greater than A, the communication device corresponding to this remaining life value is in the severe fault level; if the remaining life value output by the life prediction model is greater than A but not greater than B, the communication device corresponding to this remaining life value is in the moderate fault level; if the remaining life value output by the life prediction model is greater than B, the communication device corresponding to this remaining life value is in the minor fault level.

[0086] In one embodiment, the fault level results of 10 communication devices of the same type are shown in Table 1 specifically.

[0087] Table 1 Fault level results of 10 communication devices of the same type

[0088] Group Remaining life Failure degree 1 18590 serious 2 78566 slight 3 26574 Moderate 4 73510 slight 5 18598 serious 6 76550 slight 7 64558 slight 8 76534 slight 9 28598 Moderate 10 76574 slight

[0089] In some embodiments, step 110 specifically includes:

[0090] Step 1101, based on the circuit principle diagrams of each circuit board inside the communication devices of the same type, construct a circuit simulation model;

[0091] Step 1102: inject multiple types of faults into the circuit simulation model, collect fault data of the circuit simulation model under multiple fault types, and add the data to the fault data set.

[0092] Specifically, the circuit schematic drawings of each circuit board inside the communication equipment are obtained, and according to the circuit schematic drawings of each circuit board of the communication equipment, the complete circuits of each circuit board are replicated using circuit simulation software such as Multisim, Cadence PSpice or Simulink, and then based on the simulated circuit, fault types are injected, including hard faults such as open resistor, short capacitor, open capacitor, short capacitor, open transistor lead wire, and soft faults that deviate from the nominal value of the component, and then based on the circuit simulation model in the fault state, various electrical signal data are collected and added to the fault data set.

[0093] In one embodiment, according to the circuit schematic drawing of a circuit board of a communication equipment, the characteristics and parameters of various components are obtained, and the circuit is replicated into the Multisim simulation model. Since the circuit board of the communication equipment contains a variety of rectifier circuits, filter circuits, power amplifier circuits, etc., the circuit structure is complex. When replicating, corresponding adjustments and optimizations can be made according to the actual situation, such as arrangement position, component connection lines, etc. After drawing the circuit, add measuring instruments, such as oscilloscopes, multimeters, etc.

[0094] In some embodiments, the communication equipment remaining life prediction model in step 120 or step 130 is a deep learning model based on a neural network.

[0095] Optionally, a long short-term memory network can be used to construct a prediction model. The specific parameters of the model construction can be adjusted in actual application, and this application does not limit this.

[0096] Combine the following Figure 2 The apparatus for determining the fault level of communication equipment provided by the present invention is described. The apparatus for determining the fault level of communication equipment described below and the method for determining the fault level of communication equipment described above can be referred to each other in correspondence.

[0097] Figure 2 is a structural diagram of a device for determining a fault level of communication equipment provided in an embodiment of the present application, such as Figure 2 As shown, the device includes an acquisition module 210, an expansion module 220, a training module 230, a prediction module 240, and a determination module 250, wherein:

[0098] An acquisition module 210 is used to acquire historical operation fault data of the same type of communication equipment and establish a fault data set;

[0099] An expansion module 220 is used to construct a circuit simulation model of each circuit board inside the same type of communication equipment, and expand the fault data set based on the circuit simulation model;

[0100] A training module 230, for training a communication equipment remaining life prediction model based on a fault data set;

[0101] A prediction module 240, configured to input the electrical signal data of the target communication equipment into the trained communication equipment remaining life prediction model to obtain a life prediction value;

[0102] The determination module 250 is used to determine the fault level of the target communication equipment based on the life prediction value and a preset threshold.

[0103] It should be understood that the above-mentioned device is used to execute the method in the above-mentioned embodiment. The implementation principle and technical effect of the corresponding program module in the device are similar to those described in the above-mentioned method. The working process of the device can refer to the corresponding process in the above-mentioned method, which will not be repeated here.

[0104] Based on the method in the above embodiment, Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3 As shown, an embodiment of the present application provides an electronic device, which may include: a processor 310, a communication interface 320, a memory 330 and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other through the communication bus 340. The processor 310 may call the logic instructions in the memory 330 to execute the method for determining the fault level of the communication equipment in the above embodiment.

[0105] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method for determining the fault level of the communication equipment described in each embodiment of the present application.

[0106] Based on the method in the above embodiment, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program runs on a processor, the processor executes the method for determining the fault level of the communication equipment in the above embodiment.

[0107] Based on the method in the above embodiment, an embodiment of the present application provides a computer program product. When the computer program product runs on a processor, the processor executes the method for determining the fault level of the communication equipment in the above embodiment.

[0108] It is understandable that the processor in the embodiment of the present application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. The general-purpose processor can be a microprocessor or any conventional processor.

[0109] The method steps in the embodiments of the present application can be implemented by hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, and the software modules can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0110] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions may be transmitted from a website site, a computer, a server or a data center to another website site, a computer, a server or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0111] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0112] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for determining a fault level of communication equipment, characterized in that: include: Obtain historical operational fault data of the same type of communication equipment and establish a fault data set; Constructing a circuit simulation model of each circuit board inside the communication equipment of the same type, and expanding the fault data set based on the circuit simulation model; Based on the fault data set, train the communication equipment remaining life prediction model; Inputting the electrical signal data of the target communication equipment into the trained communication equipment remaining life prediction model to obtain a life prediction value; Based on the life prediction value and a preset threshold, a failure level of the target communication equipment is determined.

2. The method for determining the fault level of communication equipment according to claim 1, characterized in that: The method for obtaining the preset threshold value includes: Obtaining a fault degree evaluation index value of the target communication equipment and a weight coefficient of each evaluation index; Based on the fault degree evaluation index value and the weight coefficient, obtaining a comprehensive rating value of the fault degree of the target communication equipment; According to the comprehensive rating index value of the degree of failure of each communication equipment of the same type, a fault degree classification threshold diagram is drawn to obtain two classification threshold inflection points, and the remaining life value of the communication equipment corresponding to each inflection point is used as the preset threshold.

3. The method for determining the fault level of communication equipment according to claim 2, characterized in that: The method of obtaining the weight coefficient of each evaluation index includes: Based on the number of the same type of communication equipment and the number of fault degree evaluation indicators, a weight coefficient of each evaluation indicator is obtained.

4. The method for determining the fault level of communication equipment according to claim 1, characterized in that: The fault level includes three levels: severe, moderate and slight; the preset threshold includes a first preset threshold and a second preset threshold, wherein the first preset threshold is greater than the second preset threshold; and determining the fault level of the target communication equipment based on the life prediction value and the preset threshold includes: If the life prediction value is not greater than the second preset threshold, the fault level of the target communication equipment is a serious level; or, If the life prediction value is greater than the second preset threshold value but not greater than the first preset threshold value, the fault level of the target communication equipment is a moderate level; or, If the life prediction value is greater than the first preset threshold, the failure level of the target communication equipment is a minor level.

5. The method for determining the fault level of communication equipment according to claim 1, characterized in that: The constructing of the circuit simulation model of each circuit board inside the same type of communication equipment and expanding the fault data set based on the circuit simulation model includes: Building a circuit simulation model based on the circuit schematic drawings of each circuit board inside the same type of communication equipment; Multiple types of faults are injected into the circuit simulation model, and fault data of the circuit simulation model under multiple fault types are collected and added to the fault data set.

6. The method for determining the fault level of communication equipment according to claim 1, characterized in that: The communication equipment remaining life prediction model is a deep learning model based on a neural network.

7. A device for determining a fault level of communication equipment, characterized in that: include: An acquisition module is used to acquire historical operation fault data of the same type of communication equipment and establish a fault data set; An expansion module, used to construct a circuit simulation model of each circuit board inside the communication equipment of the same type, and expand the fault data set based on the circuit simulation model; A training module, used to train a communication equipment remaining life prediction model based on a fault data set; A prediction module, used for inputting the electrical signal data of the target communication equipment into the trained communication equipment remaining life prediction model to obtain a life prediction value; A determination module is used to determine the failure level of the target communication equipment based on the life prediction value and a preset threshold.

8. An electronic device, characterized in that: include: at least one memory for storing a computer program; At least one processor is used to execute the program stored in the memory. When the program stored in the memory is executed, the processor is used to execute the method for determining the fault level of communication equipment as described in any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program runs on a processor, the processor is enabled to execute the method for determining the fault level of communication equipment according to any one of claims 1 to 6.

10. A computer program product, characterized in that When the computer program product runs on a processor, the processor is enabled to execute the method for determining the fault level of communication equipment according to any one of claims 1 to 6.

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