Method and device for evaluating severity of home appliance failure, storage medium and service device

Abstract

The embodiment of the application discloses a kind of evaluation method, device, storage medium and service equipment of household appliance fault severity, related to household appliance field.The total quantity of each user is counted, the number of users of target fault is inquired, the total number of times of target fault is inquired, the average page stay duration of user inquiry target fault is inquired, and the fault severity coefficient and fault grade are calculated according to the statistical parameter values, the severity of household appliance under different fault types is quantitatively counted, the fault verification degree is evaluated by fine way, to provide guidance for subsequent research and development design, to improve the reliability of household appliance product work.

Description

Technical Field

[0001] This application relates to the field of home appliances, and more particularly to a method, apparatus, storage medium, and service equipment for assessing the severity of home appliance malfunctions. Background Technology

[0002] Home appliances may experience various types of malfunctions during use. Consumers will contact repair personnel to fix these appliances. Repair personnel use their experience to troubleshoot the problems, and after-sales staff will fill out electronic or paper repair records, which are then archived. Currently, there is a lack of research on the quantitative evaluation of the severity of home appliance malfunctions. Research often only records the number of malfunctions, lacking an accurate assessment of their severity, and thus failing to provide a basis for future research and development. Summary of the Invention

[0003] This application provides a method, apparatus, storage medium, and terminal device for assessing the severity of home appliance malfunctions, which solves the problem in the prior art that the severity of home appliance malfunctions cannot be quantitatively assessed. The technical solution is as follows:

[0004] In a first aspect, embodiments of this application provide a method for assessing the severity of a malfunction in a household appliance, the method comprising:

[0005] Retrieve fault query records;

[0006] Based on the fault query records, the total number of users, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time for users querying the target fault are counted.

[0007] The severity coefficient of the fault is calculated based on the statistical values ​​of various parameters.

[0008] The severity level of the target fault is determined based on the fault severity coefficient.

[0009] Secondly, embodiments of this application provide an apparatus for assessing the severity of a household appliance malfunction, the apparatus comprising:

[0010] The acquisition unit is used to retrieve fault query records;

[0011] The statistics unit is used to count the total number of users, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time for users querying the target fault, based on the fault query records.

[0012] The calculation unit is used to calculate the fault severity coefficient based on the statistical values ​​of various parameters;

[0013] A determination unit is used to determine the severity level of the target fault based on the fault severity coefficient.

[0014] Thirdly, embodiments of this application provide a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the above-described method steps.

[0015] Fourthly, embodiments of this application provide a service device, which may include: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to execute the above-described method steps.

[0016] The beneficial effects of the technical solutions provided in some embodiments of this application include at least the following:

[0017] By providing users with a fault query function through terminal devices, the fault query records of each user are obtained. Then, the total number of users, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time of users querying the target fault are statistically analyzed. Based on the statistical parameter values, the fault severity coefficient and fault level are calculated. The severity of home appliances under different fault types is statistically analyzed in a quantitative way, and the degree of fault verification is evaluated in a refined way. This provides guidance for subsequent research and development design, thereby improving the reliability of home appliance products. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the network architecture provided in the embodiments of this application;

[0020] Figure 2 This is a flowchart illustrating the method for assessing the severity of household appliance malfunctions provided in this application embodiment;

[0021] Figure 3 This is a schematic diagram of the fault query page provided in an embodiment of this application;

[0022] Figure 4 This is a schematic diagram of the structure of a device for assessing the severity of a malfunction of a household appliance provided in this application;

[0023] Figure 5 This is a structural schematic diagram of a service device provided in this application. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0025] It should be noted that the method for assessing the severity of appliance malfunctions provided in this application is generally performed by the service equipment, and correspondingly, the device for assessing the severity of appliance malfunctions is generally installed in the service equipment.

[0026] Figure 1 An exemplary network architecture is shown that can be applied to the method or apparatus for assessing the severity of malfunctions of home appliances in this application.

[0027] like Figure 1 As shown, the network architecture may include: terminal device 101 and service device 102. Terminal device 101 and service device 102 can communicate with each other via the network, which serves as the medium for providing communication links between the various units. The network may include various types of wired or wireless communication links, such as: wired communication links including optical fiber, twisted pair, or coaxial cable, and wireless communication links including Bluetooth, Wi-Fi, or microwave communication links.

[0028] In this system, terminal device 101 logs into service device 102 using an account and password. Service device 102 displays a fault query page on terminal device 101. Users query faults through this page, and service device 102 returns a fault resolution page to terminal device 101. Users obtain solutions to their faults through this page. Service device 102 records fault query records for each user in the background, including user ID, query time, duration of time spent on the fault resolution page, fault keywords, and device type. Based on these records, it calculates the fault severity coefficient and severity level, quantitatively assessing the severity of appliance malfunctions to improve the accuracy of the evaluation. Appliances include, but are not limited to, air conditioners, washing machines, and refrigerators.

[0029] It should be noted that the terminal device 101 and the service device 102 can be either hardware or software. When the terminal device 101 and the service device 102 are hardware, they can be implemented as a distributed service device cluster consisting of multiple service devices, or as a single service device. When the terminal device 101 and the service device 102 are software, they can be implemented as multiple software programs or software modules (e.g., used to provide distributed services), or as a single software program or software module; no specific limitations are made here.

[0030] The terminal device of this application can be equipped with various communication client applications, such as video recording applications, video playback applications, voice interaction applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0031] A terminal device can be either hardware or software. When the terminal device is hardware, it can be various terminal devices with a display screen, including but not limited to smartphones, tablets, laptops, and desktop computers. When the terminal device is software, it can be installed on the terminal devices listed above. It can be implemented as multiple software programs or software modules (e.g., used to provide distributed services) or as a single software program or software module; no specific limitation is made here.

[0032] When the terminal device is hardware, it can also be equipped with a display device and a camera. The display device can be any device capable of displaying information, and the camera is used to capture video streams. For example, the display device can be a cathode ray tube display (CR), a light-emitting diode display (LED), an e-ink screen, a liquid crystal display (LCD), or a plasma display panel (PDP). Users can use the display device on the terminal device to view displayed text, images, videos, and other information.

[0033] It should be understood that Figure 1 The number of terminal devices, network devices, and service devices shown is for illustrative purposes only. Depending on implementation needs, there can be any number of terminal devices, network devices, and service devices.

[0034] The following will be combined with the appendix Figure 2 This application provides a detailed description of the method for assessing the severity of household appliance malfunctions according to embodiments of the present application. The device for assessing the severity of household appliance malfunctions in these embodiments can be... Figure 1 The terminal device shown.

[0035] Please see Figure 2 This document presents a flowchart illustrating a method for assessing the severity of a home appliance malfunction, as provided in this embodiment. Figure 2 As shown, the method described in this application embodiment may include the following steps:

[0036] S201. Obtain fault query records.

[0037] In this embodiment, a user uses a terminal device to query solutions for home appliance malfunctions on a service device. The service device records the user's query process to form a malfunction query record; each query generates one record. Users can be repair personnel, after-sales personnel, or consumers of the home appliances. Users log in to the service device to query malfunctions through malfunction query software installed on their terminal device, or through a browser; this application does not impose any restrictions. When assessing the severity of a home appliance malfunction, the service device retrieves all users' malfunction query records. Furthermore, a company may produce multiple different models of home appliances. To improve the accuracy of malfunction assessment, the service device can retrieve only malfunction query records for a specified model category and / or the target malfunction. Furthermore, to reduce computational load, the service device can retrieve malfunction query records within a specified time period, which can be configured by the user.

[0038] For example, see Figure 3 The diagram illustrates a fault query page. Users download the fault query software to their terminal device, register using the software to obtain an account and password, and then log in to the service device. The service device displays the fault query page on the user's terminal device screen. The fault query page includes: a model category input control and a fault code input control. The input controls are graphical interfaces providing information input. Users input the model category of the appliance using the model category input control and fault keywords using the fault code input control, such as: fan not turning, not cooling, not heating, etc. Furthermore, the model category input control provides a candidate model category set, including all appliance models generated by the company. Users can only select one model category from the candidate model category set for input. The fault code input control provides a candidate fault keyword set, including all possible fault keywords for the corresponding appliance model category. Users can only select one fault keyword from the candidate fault keyword set for input. By restricting the valid information input by users and preventing them from randomly entering invalid information, the efficiency and accuracy of fault query can be improved.

[0039] Among them, users are Figure 3After the user enters the device type and fault keywords on the fault query page, the terminal device sends a query request to the service device based on the user's submission command. The query request carries the device type and fault keywords entered by the user. In response to the query request, the service device pushes the corresponding fault resolution page to the terminal device. The fault resolution page includes the fault solution corresponding to the fault keywords for that device type. The user views the fault resolution page to obtain the fault solution. The terminal device will count the time the user stays on the fault resolution page. The dwell time indicates the time the terminal device displays or closes the fault resolution page. The terminal device sends the counted dwell time to the service device for storage. The specific process is as follows: The terminal device records the start time of the service device pushing the fault resolution page. When it detects the user's closing instruction for the fault resolution page, it closes the fault resolution page and records the closing time. Then, it calculates the dwell time between the start time and the closing time and sends this dwell time to the service device. The service device generates a fault query record for the user based on the user identifier (uniquely identifying the user and assigned by the service device during user registration), the user's query time (which can be represented by the time the query request was sent), the user's dwell time on the fault resolution page, fault keywords, and device type. The service device generates and stores the fault query records for each user according to the above method.

[0040] Therefore, the fault query page provided in this application provides repair personnel with standard repair solutions, unifies the repair capabilities of various repair personnel, and improves the repair efficiency of home appliances.

[0041] S202. Based on the fault query records, count the total number of users, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time for users querying the target fault.

[0042] In this embodiment, based on the multiple fault query records obtained in S201, the total number of users, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time for users querying the target fault are counted. The target fault is a fault type specified by the user. Fault types are distinguished by fault query terms in the fault query records; fault query terms with the same or similar semantics correspond to the same fault type. The total number of users represents the total number of users registered in the service device. The number of users querying the target fault represents the number of users querying the target fault from the multiple fault query records obtained, for example, the number of users querying the fault keyword "wind turbine fault". The total number of queries for the target fault represents the sum of the number of times each user queries the target fault. It should be noted that if the same user queries the target fault multiple times, the number of queries for the target fault by that user is only counted as 1. The average time a user spends on a target problem page is the average of the time all users spend on the problem resolution page. It should be noted that if the same user queries the target problem multiple times, then the time the user spends on the problem resolution page is the sum of the multiple time periods. This can improve the accuracy of the time spent assessment.

[0043] S203. Calculate the fault severity coefficient based on the statistical values ​​of each parameter.

[0044] In this embodiment, the severity coefficient of the target fault is related to the total number of users counted in S202, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time for users querying the target fault. The above parameter values ​​and the severity coefficient of the target fault are linearly related. Calculating the severity coefficient using these parameter values ​​improves the accuracy of fault assessment. Furthermore, the severity coefficient is positively correlated with the severity of the target fault; that is, the larger the severity coefficient, the higher the severity of the target fault, and vice versa.

[0045] In this embodiment of the application, the calculation of the fault severity coefficient based on the statistical values ​​of various parameters includes:

[0046] The severity coefficient of the target fault is calculated using the following formula:

[0047]

[0048] Where η represents the severity coefficient of the fault, n represents the total number of users, m represents the number of users querying the target fault, p represents the total number of queries for the target fault, q represents the average page dwell time (in minutes) for users querying the target fault, w1 and w2 represent weights, w1+w2=1, further, w1=0.6, w2=0.4.

[0049] For example, suppose we are assessing the severity of a "wind turbine failure," and the total number of users is 5000, the number of users querying "wind turbine failure" is 1000, the total number of queries for "wind turbine failure" is 10000, and the average user spends 60 minutes viewing the fault resolution page for the wind turbine failure. Then, the calculated severity coefficient for the wind turbine failure would be:

[0050] S204. Determine the severity level of the target fault based on the fault severity coefficient.

[0051] In the embodiments of this application, the severity level is used to describe the severity of the target fault in a quantitative way. The total number of severity levels is at least two, and the specific number can be determined according to actual needs. For example, the total number of severity levels is 5, namely: most severe high-frequency fault, severe slightly high-frequency fault, severe medium-frequency fault, ordinary medium-frequency fault, and ordinary low-frequency fault, which can simultaneously characterize the severity of the fault and the frequency of fault occurrence.

[0052] Furthermore, determining the severity level of the target fault based on the fault severity coefficient includes:

[0053] The target coefficient interval is traversed among multiple preset coefficient intervals, and the fault severity coefficient falls into the target coefficient interval.

[0054] Query the severity level associated with the target coefficient range and verify that the severity level is positively correlated with the fault severity coefficient.

[0055] Furthermore, the preset multiple coefficient intervals are: (-∞, 5), [5, 15), [15, 25), [25, 35), [35, +∞).

[0056] For example, the mapping relationship between coefficient ranges and severity levels is shown in Table 1:

[0057]

[0058] Table 1

[0059] Based on the example of S203, the calculated fault severity coefficient is 6. By traversing Table 1, the coefficient range falling into [5, 15) is obtained, and the associated severity level is determined to be P4.

[0060] In the embodiments of this application, a fault query function is provided to users through a terminal device to obtain the fault query records of each user. Then, the total number of users, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time of users querying the target fault are counted. Based on the statistical parameter values, the fault severity coefficient and fault level are calculated. The severity of home appliances under different fault types is statistically analyzed in a quantitative way, and the degree of fault verification is evaluated in a refined way, providing guidance for subsequent research and development design to improve the reliability of home appliance products.

[0061] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0062] Please see Figure 4 This illustration shows a structural schematic diagram of a device for assessing the severity of a home appliance malfunction, hereinafter referred to as device 4, provided in an exemplary embodiment of this application. Device 4 can be implemented as all or part of a service device through software, hardware, or a combination of both. Device 4 includes: an acquisition unit 401, a statistics unit 402, a calculation unit 403, and a determination unit 404.

[0063] The acquisition unit is used to retrieve fault query records;

[0064] The statistics unit is used to count the total number of users, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time for users querying the target fault, based on the fault query records.

[0065] The calculation unit is used to calculate the fault severity coefficient based on the statistical values ​​of various parameters;

[0066] A determination unit is used to determine the severity level of the target fault based on the fault severity coefficient.

[0067] In one or more possible embodiments, calculating the fault severity coefficient based on statistically analyzed parameter values ​​includes:

[0068] The severity coefficient of the target fault is calculated using the following formula:

[0069]

[0070] Where η represents the severity coefficient of the fault, n represents the total number of users, m represents the number of users querying the target fault, p represents the total number of queries for the target fault, q represents the average page dwell time for users querying the target fault, w1 and w2 represent weights, and w1+w2=1.

[0071] In one or more possible embodiments, w1 = 0.6, w2 = 0.4.

[0072] In one or more possible embodiments, determining the severity level of the target fault based on the fault severity coefficient includes:

[0073] The target coefficient interval is traversed among multiple preset coefficient intervals, and the fault severity coefficient falls into the target coefficient interval.

[0074] Query the severity level associated with the target coefficient range and verify that the severity level is positively correlated with the fault severity coefficient.

[0075] In one or more possible embodiments, the preset multiple coefficient intervals are: (-∞, 5), [5, 15), [15, 25), [25, 35), [35, +∞).

[0076] In one or more possible embodiments, obtaining the fault query record includes:

[0077] Retrieve fault query records for a specified model category.

[0078] In one or more possible embodiments, it also includes:

[0079] A query unit is used to push a fault query page to the terminal device; wherein, the fault query page includes: a model category input control and a fault code input control;

[0080] Receive a query request from the terminal device; wherein the query request includes the device type and fault keywords;

[0081] In response to the query request, a troubleshooting page is pushed to the terminal device;

[0082] When it is detected that the user closes the troubleshooting page, a troubleshooting query record is generated based on the user identifier, the user's query time, the user's stay time on the troubleshooting page, the troubleshooting keywords, and the device type.

[0083] It should be noted that the device 4 provided in the above embodiments, when performing the method for assessing the severity of home appliance malfunctions, is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the above functions. Furthermore, the device for assessing the severity of home appliance malfunctions provided in the above embodiments and the method for assessing the severity of home appliance malfunctions belong to the same concept, and their implementation process is detailed in the method embodiments, which will not be repeated here.

[0084] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0085] This application also provides a computer storage medium that can store multiple instructions, which are adapted to be loaded and executed by a processor as described above. Figure 2 The method steps of the illustrated embodiment can be found in the following documentation for detailed execution. Figure 2 The specific details of the illustrated embodiments will not be elaborated here.

[0086] This application also provides a computer program product that stores at least one instruction, which is loaded and executed by the processor to implement the method for assessing the severity of home appliance malfunctions as described in the above embodiments.

[0087] Please see Figure 5 This is a schematic diagram of the structure of a service device provided in an embodiment of this application. Figure 5 As shown, the service device 500 may include: at least one processor 501, at least one network interface 504, memory 503, and at least one communication bus 502.

[0088] The communication bus 502 is used to enable communication between these components.

[0089] The network interface 504 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0090] The processor 501 may include one or more processing cores.

[0091] Optionally, the service equipment may also include a user interface, which is an interface for human-computer interaction for users. The user interface may include a display screen, a camera, etc.

[0092] Processor 501 connects to various parts within the service device 500 via various interfaces and lines. It executes various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 503, and by calling data stored in memory 503. Optionally, processor 501 can be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). Processor 501 can integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem can also be implemented as a separate chip without being integrated into processor 501.

[0093] The memory 503 may include random access memory (RAM) or read-only memory. Optionally, the memory 503 may include a non-transitory computer-readable storage medium. The memory 503 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 503 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 503 may also be at least one storage device located remotely from the aforementioned processor 501. Figure 5 As shown, the memory 503, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and application programs.

[0094] exist Figure 5 In the service device 500 shown, the processor 501 can be used to call the application program stored in the memory 503 and specifically execute, such as Figure 2 The method shown can be referred to for details. Figure 2As shown, it will not be elaborated further here.

[0095] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory, or random access memory, etc.

[0096] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A method for assessing the severity of a malfunction in a household appliance, characterized in that, include: Retrieve fault query records, including: retrieve fault query records for a specified model category; Based on the fault query records, the total number of users, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time for users querying the target fault are counted. The severity coefficient of the fault is calculated based on the statistical values ​​of various parameters, including: The severity coefficient of the target fault is calculated using the following formula: ； in, Let represent the severity coefficient of the fault, n represent the total number of users, m represent the number of users querying the target fault, p represent the total number of queries for the target fault, and q represent the average page dwell time for users querying the target fault. and Indicates weight, + =1; The severity level of the target fault is determined based on the fault severity coefficient; Also includes: A fault query page is pushed to the terminal device; wherein, the fault query page includes: a model type input control and a fault code input control; Receive a query request from the terminal device; wherein the query request includes the device type and fault keywords; In response to the query request, a troubleshooting page is pushed to the terminal device; When it is detected that the user closes the troubleshooting page, a troubleshooting query record is generated based on the user identifier, the user's query time, the user's stay time on the troubleshooting page, the troubleshooting keywords, and the device type.

2. The method according to claim 1, characterized in that, =0.6， =0.4。 3. The method according to claim 1 or 2, characterized in that, Determining the severity level of the target fault based on the fault severity coefficient includes: The target coefficient interval is traversed among multiple preset coefficient intervals, and the fault severity coefficient falls into the target coefficient interval. Query the severity level associated with the target coefficient range and verify that the severity level is positively correlated with the fault severity coefficient.

4. The method according to claim 3, characterized in that, The preset multiple coefficient ranges are: , , , , .

5. A device for assessing the severity of a household appliance malfunction, characterized in that, The method for assessing the severity of a home appliance malfunction as described in claim 1 includes: The acquisition unit is used to retrieve fault query records; The statistics unit is used to count the total number of users, the number of users querying the target fault, the total number of queries for the target fault, and the average page dwell time for users querying the target fault, based on the fault query records. The calculation unit is used to calculate the fault severity coefficient based on the statistical values ​​of various parameters; The determining unit is used to determine the severity level of the target fault based on the fault severity coefficient, and push a fault query page to the terminal device; wherein, the fault query page includes: a model category input control and a fault code input control; Receive a query request from the terminal device; wherein the query request includes the device type and fault keywords; In response to the query request, a troubleshooting page is pushed to the terminal device; When it is detected that the user closes the troubleshooting page, a troubleshooting query record is generated based on the user identifier, the user's query time, the user's stay time on the troubleshooting page, the troubleshooting keywords, and the device type.

6. A computer storage medium, characterized in that, The computer storage medium stores a plurality of instructions, which are adapted to be loaded by a processor and executed as method steps as claimed in any one of claims 1 to 4.

7. A service device, characterized in that, include: A processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and executed the method steps as claimed in any one of claims 1 to 4.

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