Fault repair guidance method, device, system, and storage medium

Abstract

The present invention discloses a fault repair guidance method, device and system, and storage medium. The method comprises: monitoring the working parameters of a target electrical appliance in real time, and judging whether the working parameters are within a preset working parameter threshold range; if so, inputting the working parameters into a fault category judgment model, and determining the fault category of the target electrical appliance, so as to determine whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault category of the target electrical appliance; when the fault of the target electrical appliance is a self-repairable fault, providing a maintenance operation guide corresponding to the fault; when the fault of the target electrical appliance is a non-self-repairable fault, providing maintenance personnel information corresponding to the fault, thereby realizing judging whether the electrical appliance fault is a user-repairable fault based on the electrical appliance fault data analysis, guiding the user to manually repair or report the fault, and being able to repair the fault more timely and accurately.

Description

Technical Field

[0001] The present invention belongs to the technical field of electrical appliance maintenance application, and in particular relates to a fault maintenance guidance method, device and system, and a storage medium. Background Art

[0002] Electrical appliances have changed people's lives, freeing humans from tedious and repetitive housework; and with the development of technology, smart home appliances are increasingly involved in people's lives, bringing people a smarter, easier to use, and more personalized life experience. The functions of home appliances are constantly innovating, but the way to deal with electrical appliance failures has not made much progress - when an electrical appliance fails, users are unclear about the cause of the failure and have no idea how to solve it, so they can only report it for repair; if users are allowed to repair it themselves, on the one hand, users will hardly have the opportunity and motivation to learn how to repair electrical appliances, and on the other hand, even if users learn how to repair electrical appliances, they may not be able to accurately determine the cause of the failure.

[0003] Patent number CN 110909891 A discloses a method and device for repairing electrical appliance failures. The method includes: obtaining a structural image of the target electrical appliance; analyzing the structural image using a fault model to obtain the fault problem; determining a repair plan based on the fault problem, wherein the repair plan at least includes: repair tools used to repair the target electrical appliance. This patent solves the technical problem that maintenance personnel need to spend a lot of time to determine the repair method when repairing electrical appliances in related technologies. However, for electrical appliance failures, it only reduces the time for maintenance personnel to determine the repair method. For users, as long as the electrical appliance fails, they still need to contact maintenance personnel. Even if the failure is not serious, they have to wait for the maintenance personnel to repair the appliance before they can use the appliance. This not only delays the user's timely use of the appliance, but also requires the user to pay for the repair. At the same time, merchants selling electrical appliances need to bear a lot of maintenance work, resulting in a poor experience for both users and merchants in electrical appliance repair.

[0004] There is an urgent need for a fault repair guidance method, device, system, and storage medium. Summary of the invention

[0005] The technical problem to be solved by the present invention is how to guide users to quickly solve the problem of repair failure when an electrical appliance fails.

[0006] In view of the above problems, the present invention provides a fault repair guidance method, device and system, and storage medium.

[0007] In a first aspect, the present invention provides a fault repair guidance method, comprising the following steps:

[0008] Monitor the operating parameters of the target electrical appliance in real time and determine whether the operating parameters are within a preset operating parameter threshold range:

[0009] When the operating parameter is not within a preset operating parameter threshold range, the operating parameter is input into a fault category judgment model to determine the fault category of the target electrical appliance;

[0010] Provide different maintenance guidance information according to different fault types.

[0011] According to an embodiment of the present invention, preferably, providing different maintenance guidance information according to different fault categories includes the following steps:

[0012] Determine, according to the fault type of the target electrical appliance, whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault;

[0013] When the fault of the target electrical appliance is a self-repairable fault, a maintenance operation guide corresponding to the fault is provided;

[0014] When the fault of the target electrical appliance is a fault that cannot be repaired by itself, maintenance personnel information corresponding to the fault is provided.

[0015] According to an embodiment of the present invention, preferably, judging whether the working parameter is within a preset working parameter threshold range comprises the following steps:

[0016] The different types of working parameters are compared with their corresponding preset working parameter threshold ranges respectively to determine whether each working parameter is within the corresponding preset working parameter threshold range, so as to obtain working parameters that are not within the preset working parameter threshold range.

[0017] According to an embodiment of the present invention, preferably, the method further comprises the following steps:

[0018] Classification training is performed using known working parameters and their corresponding fault categories to obtain a fault category judgment model.

[0019] According to an embodiment of the present invention, preferably, after determining the fault type of the target electrical appliance, the method further comprises the following steps:

[0020] The frequency of occurrence of each fault of the target electrical appliance is counted, and the category of the fault whose frequency exceeds the preset frequency is sent to electrical appliances of the same model as the target electrical appliance to remind them to check the fault regularly.

[0021] According to an embodiment of the present invention, preferably, before determining whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault type of the target electrical appliance, providing different maintenance guidance information according to different fault types, further includes the following steps:

[0022] Each fault category of the target electrical appliance is labeled as self-repairable or non-self-repairable.

[0023] According to an embodiment of the present invention, preferably, after providing the maintenance personnel information corresponding to the fault, providing different maintenance guidance information according to different fault categories, further comprising the following steps:

[0024] Based on the correspondence between the preset fault category and the cause of the fault, all possible causes of the fault are determined according to the fault category and provided to maintenance personnel.

[0025] In a second aspect, the present invention provides a fault repair guidance device, comprising:

[0026] The judgment module is used to monitor the operating parameters of the target electrical appliance in real time and judge whether the operating parameters are within a preset operating parameter threshold range:

[0027] a classification module, for inputting the operating parameter into a fault category judgment model to determine the fault category of the target electrical appliance when the operating parameter is not within a preset operating parameter threshold range, so as to determine whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault category of the target electrical appliance;

[0028] A module is provided for providing a maintenance operation guide corresponding to the fault when the fault of the target electrical appliance is a self-repairable fault; and for providing maintenance personnel information corresponding to the fault when the fault of the target electrical appliance is a non-self-repairable fault.

[0029] In a third aspect, the present invention provides a storage medium having a computer program stored thereon, characterized in that the computer program implements the steps of the above method when executed by a processor.

[0030] In a fourth aspect, the present invention provides a fault repair guidance system, comprising:

[0031] A collection device, used to collect operating parameters of the target electrical appliance;

[0032] The server is connected to the acquisition device and includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the steps of the above method are implemented according to the working parameters collected by the acquisition device.

[0033] According to an embodiment of the present invention, preferably, the system further includes:

[0034] The client is connected to the server and is used to display the maintenance operation guide or maintenance personnel information provided by the server.

[0035] Compared with the prior art, one or more embodiments of the above scheme may have the following advantages or beneficial effects:

[0036] By applying the fault repair guidance method of the present invention, the working parameters of the target electrical appliance are monitored in real time, and it is determined whether the working parameters are within a preset working parameter threshold range. When the working parameters are not within the preset working parameter threshold range, the working parameters are input into a fault category judgment model to determine the fault category of the target electrical appliance, so as to determine whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault category of the target electrical appliance. When the fault of the target electrical appliance is a self-repairable fault, a maintenance operation guide corresponding to the fault is provided. When the fault of the target electrical appliance is a non-self-repairable fault, maintenance personnel information corresponding to the fault is provided, so as to determine whether the electrical appliance fault is a user-repairable fault based on the electrical appliance fault data analysis, guide the user to manually repair or report the fault, and enable the user to understand the electrical appliance fault more timely, repair it more accurately, and have a better understanding of the electrical appliance operating conditions.

[0037] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0039] Figure 1 A flowchart of a fault repair guidance method according to an embodiment of the present invention is shown;

[0040] Figure 2 A flowchart of a fault repair guidance method according to a second embodiment of the present invention is shown;

[0041] Figure 3 A flowchart of a fault repair guidance method according to a third embodiment of the present invention is shown;

[0042] Figure 4 A flowchart of a fault category determination model training process in Embodiment 3 of the present invention is shown;

[0043] Figure 5 The flowchart of the specific implementation of step S303 in the fault repair guidance method of the third embodiment of the present invention is shown. DETAILED DESCRIPTION

[0044] The following will describe the implementation methods of the present invention in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that as long as there is no conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0045] Embodiment 1

[0046] In order to solve the above technical problems existing in the prior art, an embodiment of the present invention provides a fault repair guidance method.

[0047] Reference Figure 1 The fault repair guidance method of this embodiment includes the following steps:

[0048] S110, real-time monitoring of operating parameters of the target electrical appliance;

[0049] S120, determining whether the operating parameter is within a preset operating parameter threshold range:

[0050] If so, no response will be given;

[0051] If not, execute step S130;

[0052] S130, inputting the operating parameters into a fault category judgment model to determine the fault category of the target electrical appliance;

[0053] S140, judging whether the fault of the target electrical appliance is a self-repairable fault according to the fault type of the target electrical appliance;

[0054] If yes, execute step S150;

[0055] If not, execute step S160;

[0056] S150, providing a maintenance operation guide corresponding to the fault;

[0057] S160, providing maintenance personnel information corresponding to the fault.

[0058] Before step S130, the method further includes the following steps:

[0059] Classification training is performed using known working parameters and the corresponding fault categories to obtain a fault category judgment model. The fault category judgment model can be any one of a pattern recognition model, a neural network model, and a model combining pattern recognition and neural network.

[0060] After determining the fault type of the target electrical appliance in step S130, the method further includes the following steps:

[0061] The frequency of occurrence of each fault of the target electrical appliance is counted, and the category of the fault whose frequency exceeds the preset frequency is sent to electrical appliances of the same model as the target electrical appliance to remind them to check the fault regularly.

[0062] Before determining whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault type of the target electrical appliance in step S130, the method further includes the following steps:

[0063] Each fault category of the target electrical appliance is labeled as self-repairable or non-self-repairable.

[0064] After providing the maintenance personnel information corresponding to the fault in step S150, the method further includes the following steps:

[0065] Based on the correspondence between the preset fault category and the cause of the fault, all possible causes of the fault are determined according to the fault category and provided to maintenance personnel.

[0066] The fault repair guidance method of this embodiment can intelligently identify the fault category through the fault category judgment model, so as to timely discover the fault, and can efficiently and accurately judge the fault category by using pattern recognition technology;

[0067] The fault repair guidance method of this embodiment analyzes the electrical appliance fault data, determines whether the electrical appliance fault is a user-repairable fault, and guides the user to manually repair or report the fault, which can help the user better use the electrical appliance and obtain more considerate electrical appliance use services.

[0068] The fault repair guidance method of this embodiment divides faults into "user-repairable faults" and "user-unrepairable faults", and assigns minor faults to users to solve, which can reduce the company's burden of repairing faults. Moreover, users can repair the faults themselves, reducing the time of contacting repair personnel, and can effectively repair faulty electrical appliances, and can also save repair costs for users.

[0069] The fault repair guidance method of this embodiment obtains the faults that are likely to occur in the target appliance by counting the frequency of a certain fault occurring in the target appliance, thereby notifying appliances of the same model as the target appliance to pay attention to the fault, thereby optimizing the user experience of using the appliance.

[0070] The fault repair guidance method of this embodiment determines whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault by labeling the fault type, and can quickly determine a repair plan for the fault.

[0071] The fault repair guidance method of this embodiment can guide the maintenance personnel to quickly repair the faults that the users cannot repair by themselves by providing the maintenance personnel with possible causes of the faults that the users cannot repair by themselves.

[0072] Embodiment 2

[0073] In order to solve the above technical problems existing in the prior art, the embodiment of the present invention provides a fault repair guidance method based on the first embodiment, wherein the method of the embodiment of the present invention improves step S120 in the first embodiment.

[0074] Reference Figure 2 The fault repair guidance method of this embodiment includes the following steps:

[0075] S210, real-time monitoring of operating parameters of the target electrical appliance;

[0076] S221, comparing different types of working parameters with their corresponding preset working parameter threshold ranges;

[0077] S222, determining whether each operating parameter is within a corresponding preset operating parameter threshold range:

[0078] If so, no response will be given;

[0079] If not, execute step S230;

[0080] S230, inputting the operating parameters into a fault category judgment model to determine the fault category of the target electrical appliance;

[0081] S240, judging whether the fault of the target electrical appliance is a self-repairable fault according to the fault type of the target electrical appliance;

[0082] If yes, execute step S250;

[0083] If not, execute step S260;

[0084] S250, providing a maintenance operation guide corresponding to the fault;

[0085] S260, providing maintenance personnel information corresponding to the fault.

[0086] The fault repair guidance method of this embodiment can quickly determine whether a target electrical appliance has a fault by determining whether different types of operating parameters are within a preset operating parameter threshold range.

[0087] The fault repair guidance method of this embodiment organically combines fault category judgment and user guidance, improves user participation, expands user's right to know, reduces user's repair cost, saves user's repair waiting time, and improves user's usage experience.

[0088] Embodiment 3

[0089] In order to solve the above technical problems existing in the prior art, the embodiment of the present invention is an application example of the fault repair guidance method of embodiment 1.

[0090] See also Figure 3 The fault repair guidance method of this embodiment includes the following steps:

[0091] S310: sensors built into different types of electrical appliances collect operating parameters of the electrical appliances during operation, and upload the operating parameters to a server when a fault occurs;

[0092] S320: The server calls the fault category judgment model to process the collected fault information. The training process of the model is as follows: Figure 4 As shown. The model is trained by pattern recognition technology. Each set of training data is the working parameters and their corresponding fault information, where the fault information includes the fault category. According to the correspondence between common electrical faults and various parameters, the features with high correlation are manually selected, and the classification model or rules are trained. The performance of the classifier is verified with test data, and the model is continuously optimized.

[0093] S330: Push different information to the user according to the fault type. The processing flow is as follows: Figure 5 If the fault is user-repairable, an operation guide (fault cause, fault analysis, repair method, repair video) is provided to the user to guide the user to manually repair the fault. The operation guide is produced by the merchant and stored on the server according to the type of appliance and fault category, and can be called when handling the corresponding fault; otherwise, the user is guided to report the fault and a possible cause analysis sheet is generated for the user to assist the maintenance personnel in repairing the fault.

[0094] Among them, in step S320, the training process of the pattern recognition model is explained below by taking the training of the air-conditioning fault judgment model as an example.

[0095] First, the following conditions should be met: ① There is a representative indicator set X for the model, X = {x1, x2, x3...., xn} ② The conclusion set of all possible results of the model ③ The method set that can perform pattern recognition and map the indicator set to the conclusion set ④ If the processing results of two or more types of patterns in the method set have an intersection, the algorithm is used to balance and adjust to get the final decision. Then, the training is carried out according to the following process: The model indicator set contains several groups of indicators and several items, which are divided into general indicators and special indicators (all manually labeled and judged according to expert experience). For general indicators, randomly take pairs of values ​​from indicators and conclusions, and use mathematical methods to obtain the regression equation of the conclusion about the indicator and the corresponding weight coefficient; for special indicators, they are constructed into a search algorithm, each special indicator is mapped into a node, and when the node is searched, the conclusion of its mapping is recorded and all the conclusions of this search are connected after the search is completed. Finally, according to the algorithm synthesis, the final conclusion is given.

[0096] The fault repair guidance method of this embodiment identifies the fault type through a fault category judgment model and provides maintenance guidance to the user. Specifically, it detects the operating status of the appliance in real time and obtains the working parameters of the appliance. When abnormal operation of the appliance is detected, the working parameters are input into the fault category judgment model. The model judges the appliance fault category based on the equipment fault data analysis. If the fault is a user-repairable fault, an operation guide is provided to the user to guide the user to repair it manually. Otherwise, a possible cause analysis sheet is generated for the user to guide the user to report the repair, which can save maintenance costs, improve maintenance efficiency, and optimize user experience.

[0097] Embodiment 4

[0098] In order to solve the above technical problems existing in the prior art, an embodiment of the present invention provides a fault repair guiding device.

[0099] The fault repair guidance device of this embodiment includes:

[0100] The judgment module is used to monitor the operating parameters of the target electrical appliance in real time and judge whether the operating parameters are within a preset operating parameter threshold range:

[0101] A classification module, for inputting the operating parameter into a fault category judgment model to determine the fault category of the target electrical appliance when the operating parameter is not within a preset operating parameter threshold range;

[0102] Provides a module for providing different maintenance guidance information according to different fault categories.

[0103] A module is provided, which is also used to determine whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault category of the target electrical appliance;

[0104] When the fault of the target electrical appliance is a self-repairable fault, a maintenance operation guide corresponding to the fault is provided; and when the fault of the target electrical appliance is a non-self-repairable fault, maintenance personnel information corresponding to the fault is provided.

[0105] Among them, the judgment module is also used to compare different types of working parameters with their respective corresponding preset working parameter threshold ranges, to determine whether each working parameter is within the corresponding preset working parameter threshold range, so as to obtain working parameters that are not within the preset working parameter threshold range.

[0106] The fault repair guidance device of this embodiment further includes:

[0107] The model training module is used to perform classification training using known working parameters and the corresponding fault categories to obtain a fault category judgment model.

[0108] The fault repair guidance device of this embodiment further includes:

[0109] The statistical module is used to count the frequency of each fault of the target electrical appliance after determining the fault category of the target electrical appliance, and send the category of the fault whose frequency exceeds the preset frequency to the electrical appliances of the same model as the target electrical appliance to remind them to check the fault regularly.

[0110] The fault repair guidance device of this embodiment further includes:

[0111] The marking module is used to mark each fault category of the target electrical appliance with a label of self-repairable or non-self-repairable before determining whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault category of the target electrical appliance.

[0112] The fault repair guidance device of this embodiment further includes:

[0113] The fault cause providing module, after providing the maintenance personnel information corresponding to the fault, determines all possible causes of the fault according to the fault category based on the correspondence between the preset fault category and the cause of the fault, and provides them to the maintenance personnel.

[0114] Embodiment 5

[0115] In order to solve the above technical problems existing in the prior art, an embodiment of the present invention further provides a storage medium.

[0116] The storage medium of this embodiment stores a computer program, which implements the steps of the method in the above embodiment when executed by a processor.

[0117] Embodiment 6

[0118] In order to solve the above technical problems existing in the prior art, an embodiment of the present invention further provides a fault repair guidance system.

[0119] The fault repair guidance system of this embodiment includes:

[0120] A collection device, used to collect operating parameters of the target electrical appliance;

[0121] A server connected to the acquisition device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the steps of the above method are implemented according to the working parameters acquired by the acquisition device;

[0122] The client is connected to the server and is used to display the maintenance operation guide or maintenance personnel information provided by the server.

[0123] In the fault repair guidance system provided in this embodiment, the sensor collects working parameter data, and when the target appliance fails, the working parameters are uploaded to the server; the server is used to store repair guides and repair materials, and provide a fault category judgment model; the client is the corresponding APP or applet in the user's smartphone, which has various functions of matching the target appliance, decoding the information sent by the server, and displaying or playing the corresponding information.

[0124] The fault repair guidance system of this embodiment detects the operating status of the electrical appliance in real time and obtains the working parameters of the electrical appliance. When abnormal operation of the electrical appliance is detected, the working parameters are input into the fault category judgment model. The model judges the fault category of the electrical appliance based on the equipment fault data analysis. If the fault is a user-repairable fault, an operation guide is provided to the user to guide the user to repair it manually; otherwise, a possible cause analysis sheet of the fault is generated for the user to guide the user to report the repair, which can save maintenance costs, improve maintenance efficiency, and optimize user experience.

[0125] Although the embodiments disclosed in the present invention are as above, the contents described are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A fault repair guidance method, characterized in that: The following steps are involved: Monitor the operating parameters of the target electrical appliance in real time and determine whether the operating parameters are within a preset operating parameter threshold range: When the operating parameter is not within a preset operating parameter threshold range, the operating parameter is input into a fault category judgment model to determine the fault category of the target electrical appliance; Provide different maintenance guidance information according to different fault types; Provide different maintenance guidance information according to different fault types, including the following steps: Determine, according to the fault type of the target electrical appliance, whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault; When the fault of the target appliance is a self-repairable fault, a maintenance operation guide corresponding to the fault is provided to the user; When the fault of the target electrical appliance is a fault that cannot be repaired by itself, provide maintenance personnel information corresponding to the fault; After determining the fault type of the target electrical appliance, the method further comprises the following steps: Counting the frequency of occurrence of each type of fault of the target electrical appliance, and sending the type of the fault whose frequency exceeds a preset frequency to electrical appliances of the same model as the target electrical appliance, so as to remind the user to regularly check the fault; Before determining whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault type of the target electrical appliance, providing different maintenance guidance information according to different fault types, the steps further include: Label each fault type of the target electrical appliance as self-repairable or non-self-repairable; Determining whether the operating parameter is within a preset operating parameter threshold range comprises the following steps: Compare different types of working parameters with their corresponding preset working parameter threshold ranges, and determine whether each working parameter is within the corresponding preset working parameter threshold range, so as to obtain working parameters that are not within the preset working parameter threshold range; The method further comprises the following steps: Using known working parameters and their corresponding fault categories to perform classification training, a fault category judgment model is obtained; After providing maintenance personnel information corresponding to the fault, providing different maintenance guidance information according to different fault categories, the following steps are also included: Based on the correspondence between the preset fault category and the cause of the fault, all possible causes of the fault are determined according to the fault category and provided to maintenance personnel; The training process of the fault category judgment model includes: Provide a representative indicator set X for the model, X={x1,x2,x3.....,xn}; Provide a set of conclusions for all possible outcomes of the model; Provide a set of methods that can perform pattern recognition and map indicator sets to conclusion sets; If the processing results of two or more types of modes in the method set are intersecting, the algorithm is used to balance and adjust to get the final decision; Then, the training is carried out according to the following process, which includes: the model indicator set contains several groups of indicators and several items, which are divided into general indicators and special indicators, where the general indicators and special indicators are obtained by manual annotation based on expert experience; for general indicators, randomly take pairs of values ​​from indicators and conclusions for observation, and use mathematical methods to obtain the regression equation of the conclusion about the indicator and the corresponding weight coefficient; for special indicators, a search algorithm is constructed, each special indicator is mapped into a node, and when the node is searched, the conclusion of its mapping is recorded and all the conclusions of this search are connected after the search is completed; finally, the final conclusion is given based on the algorithm synthesis.

2. A fault repair guidance device, characterized in that: include: The judgment module is used to monitor the operating parameters of the target electrical appliance in real time and judge whether the operating parameters are within a preset operating parameter threshold range: A classification module, for inputting the operating parameter into a fault category judgment model to determine the fault category of the target electrical appliance when the operating parameter is not within a preset operating parameter threshold range; Providing a module for providing different maintenance guidance information according to different fault categories; determining whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault category of the target electrical appliance; When the fault of the target appliance is a self-repairable fault, a maintenance operation guide corresponding to the fault is provided to the user; When the fault of the target electrical appliance is a fault that cannot be repaired by itself, provide maintenance personnel information corresponding to the fault; It is also used to determine whether the fault of the target electrical appliance is a self-repairable fault or a non-self-repairable fault according to the fault category of the target electrical appliance; The fault repair guiding device further comprises: A statistical module is used to count the frequency of each fault of the target electrical appliance after determining the fault category of the target electrical appliance, and send the category of the fault whose frequency exceeds the preset frequency to the electrical appliance of the same model as the target electrical appliance to remind the user to regularly check the fault; The judgment module is further used to compare different types of working parameters with their corresponding preset working parameter threshold ranges, to judge whether each working parameter is within the corresponding preset working parameter threshold range, so as to obtain working parameters that are not within the preset working parameter threshold range; The fault repair guidance device also includes: A model training module is used to perform classification training using known working parameters and corresponding fault categories to obtain a fault category judgment model; The fault repair guidance device also includes: A fault cause providing module, after providing maintenance personnel information corresponding to the fault, determines all possible causes of the fault according to the fault category based on the correspondence between the preset fault category and the cause of the fault, and provides the causes to the maintenance personnel; The training process of the fault category judgment model includes: Provide a representative indicator set X for the model, X={x1,x2,x3.....,xn}; Provide a set of conclusions for all possible outcomes of the model; Provide a set of methods that can perform pattern recognition and map indicator sets to conclusion sets; If the processing results of two or more types of modes in the method set are intersecting, the algorithm is used to balance and adjust to get the final decision; Then, the training is carried out according to the following process, which includes: the model indicator set contains several groups of indicators and several items, which are divided into general indicators and special indicators, where the general indicators and special indicators are obtained by manual annotation based on expert experience; for general indicators, randomly take pairs of values ​​from indicators and conclusions for observation, and use mathematical methods to obtain the regression equation of the conclusion about the indicator and the corresponding weight coefficient; for special indicators, a search algorithm is constructed, each special indicator is mapped into a node, and when the node is searched, the conclusion of its mapping is recorded and all the conclusions of this search are connected after the search is completed; finally, the final conclusion is given based on the algorithm synthesis.

3. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method as claimed in claim 1 are implemented.

4. A fault repair guidance system, characterized in that: include: A collection device, used to collect operating parameters of the target electrical appliance; The server is connected to the acquisition device and includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the steps of the method as claimed in claim 1 are implemented according to the working parameters collected by the acquisition device.

5. The fault repair guidance system according to claim 4, characterized in that: Also includes: The client is connected to the server and is used to display the maintenance operation guide or maintenance personnel information provided by the server.

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