Processing method and device for motor maintenance, electronic equipment and medium

Abstract

The application discloses a processing method and device for motor maintenance, electronic equipment and medium, and the method comprises the following steps: obtaining operation data and maintenance requirements of a motor; determining technical guidance information corresponding to the maintenance requirements; calculating the sorting index of the technical guidance information according to the operation data, and sorting the technical guidance information based on the sorting index. According to the obtained operation data and maintenance requirements, the technical guidance information corresponding to the maintenance requirements is determined and sorted, which can help the operator to efficiently find the technical guidance information meeting the maintenance requirements when the motor equipment is maintained, so as to obtain the most effective solution and improve the efficiency and accuracy of motor maintenance.

Description

Technical Field

[0001] This invention relates to the electrical field, and more particularly to a method, apparatus, electronic device, and medium for motor maintenance. Background Technology

[0002] Traditional motor maintenance methods mainly include telephone repair requests and scheduled maintenance, with repair personnel performing maintenance and handling the required repairs. In traditional methods, inspection records are typically kept on various paper forms. When a repair request arises, repair personnel must find solutions from these records or maintenance manuals. However, this approach generally suffers from the following problems, reducing the efficiency of motor maintenance: firstly, it is often difficult to find useful data from a large number of past paper repair records; secondly, a significant amount of time is spent searching for corresponding solutions in the maintenance manual. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to overcome the shortcomings of the low efficiency of motor maintenance in the prior art, and to provide a processing method, device, electronic device and medium for motor maintenance.

[0004] The present invention solves the above-mentioned technical problems through the following technical solution:

[0005] Firstly, a method for overhauling an electric motor is provided, the method comprising:

[0006] Obtain motor operating data and maintenance requirements;

[0007] Determine the technical guidance information corresponding to the maintenance requirements;

[0008] The ranking index of the technical guidance information is calculated based on the operational data, and the technical guidance information is ranked based on the ranking index.

[0009] Optionally, the ranking index of the technical guidance information is calculated based on the operational data, including:

[0010] Select all or part of the operational data corresponding to the maintenance requirements as the target operational data;

[0011] By analyzing the correlation between the target operational data and the technical guidance information, a first weight is determined for each of the target operational data.

[0012] The ranking index of the technical guidance information is obtained by weighting each target operation data according to the first weight.

[0013] Optionally, the processing method further includes:

[0014] Obtain the historical selection count corresponding to the technical guidance information;

[0015] The ranking index of the technical guidance information is obtained by weighting each of the target operation data according to the first weight, including:

[0016] The target running data is weighted according to the first weight, and the ranking index of the technical guidance information is obtained according to the weighted calculation result and the historical selection number.

[0017] Optionally, a weighted calculation is performed on each of the target running data according to the first weight, and a ranking index of the technical guidance information is obtained based on the weighted calculation result and the historical selection count, including:

[0018] The coefficient of the historical selection count is determined based on the historical selection count.

[0019] The ranking index is calculated according to the following formula:

[0020] I = (V1P1 + V2P2 + ... + V) n P n (a+KH);

[0021] Among them, V n P represents the running data of the nth target. n The first weight of the nth target running data is represented by I, the ranking index is represented by K, the coefficient is represented by H, the number of historical selections is represented by a, and the preset value is represented by a.

[0022] Optionally, obtain the motor's operating data and maintenance requirements, including:

[0023] The initial operating data of the motor is acquired by sensors arranged on the motor.

[0024] The initial running data is parsed to obtain the running data.

[0025] Optionally, after obtaining the motor's operating data and maintenance requirements, the process includes:

[0026] Obtain the identification information of the motor;

[0027] The operating data and maintenance requirements are stored based on the identification information.

[0028] Optionally, after sorting the technical guidance information based on the sorting index, the process includes:

[0029] The sorted technical guidance information is displayed using an augmented reality device;

[0030] And / or, after obtaining the motor's operating data and maintenance requirements, including:

[0031] The operational data and maintenance requirements are displayed using an augmented reality device.

[0032] Secondly, a processing device for motor maintenance is provided, the processing device comprising:

[0033] The first acquisition module is used to acquire the motor's operating data and maintenance requirements;

[0034] The determination module is used to determine the technical guidance information corresponding to the maintenance requirements;

[0035] The sorting module is used to calculate the sorting index of the technical guidance information based on the running data, and sort the technical guidance information based on the sorting index.

[0036] Thirdly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and for running on the processor, wherein the processor executes the computer program to implement the processing method for motor maintenance described in the first aspect.

[0037] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, wherein when the computer program is executed by a processor, it implements the processing method for motor maintenance described in the first aspect.

[0038] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of the present invention.

[0039] The positive and progressive effects of this invention are as follows: based on the acquired operating data and maintenance requirements, the corresponding technical guidance information for maintenance requirements is determined and sorted, which can help operators efficiently find the technical guidance information that meets the maintenance requirements when maintaining motor equipment, so as to obtain the most effective solution and improve the efficiency and accuracy of motor maintenance. Attached Figure Description

[0040] Figure 1 A flowchart illustrating a method for motor maintenance provided as an exemplary embodiment of the present invention;

[0041] Figure 2 This is a flowchart illustrating the acquisition of motor operating data and maintenance requirements in an exemplary embodiment of the present invention.

[0042] Figure 3 This is a flowchart illustrating the calculation of the ranking index of the technical guidance information based on the operational data in an exemplary embodiment of the present invention;

[0043] Figure 4A schematic diagram of a processing device for motor maintenance provided as an exemplary embodiment of the present invention;

[0044] Figure 5 This is a schematic diagram of the structure of an electronic device provided as an exemplary embodiment of the present invention.

[0045] Figure 6 This is a schematic diagram of the processing flow of an XR device according to an exemplary embodiment of the present invention. Detailed Implementation

[0046] The present invention will be further illustrated below by way of an exemplary embodiment, but the invention is not limited to the scope of the embodiments described herein.

[0047] Figure 1 A flowchart of a processing method for motor maintenance, provided as an exemplary embodiment of the present invention, is included in the processing method:

[0048] S11. Obtain motor operating data and maintenance requirements.

[0049] In one embodiment, Figure 2 The flowchart for obtaining motor operating data and maintenance requirements specifically includes:

[0050] S111. Obtain the initial operating data of the motor.

[0051] The initial operating data can be collected by sensors installed on the motor. The data collected by the motor is converted into initial operating data. The format of the initial operating data includes, but is not limited to, JASON (a data format).

[0052] In one implementation, the initial runtime data in JASON format includes a title (MotorDatas), an identifier (flag), a parameter value (value), a timestamp (time), a time (Time), and a device identifier (sn), as detailed below:

[0053] {

[0054] "MotorDatas": [{

[0055] "flag": "HUM",

[0056] value: 65.2000

[0057] }, {

[0058] "flag": "VX",

[0059] value: 8.5000

[0060] },

[0061] …………

[0062] ],

[0063] "timestamp": "1664181792",

[0064] Time: 2022-09-26 08:43:12

[0065] "sn": "2013025698592"

[0066] }

[0067] In one possible implementation, the initial operating data can be transmitted to an XR (Extended Reality) device via IoT (Internet of Things) technology, and the XR device can then parse the initial operating data.

[0068] S112. Parse the initial running data to obtain the running data.

[0069] This involves parsing the initial running data to obtain running data containing specific values.

[0070] Taking the initial running data in JASON format as an example, the following running data is obtained by parsing the initial running data: the motor equipment with device identification code 2013025698592, time: 2022-09-26 08:43:12, timestamp: 1664181792, and two collected running data: "HUM": 65.200 and "VX": 8.5000.

[0071] In one embodiment, after step S11, the processing method further includes:

[0072] Obtain the motor identification information.

[0073] The identification information of the motor can be the device identification code in the above embodiments.

[0074] The operational data and maintenance requirements are stored based on the identification information.

[0075] Among them, the received historical operating data and maintenance requirements can be classified and stored in the database according to the equipment identification code, so that users can call up the historical operating data during the maintenance process.

[0076] In one embodiment, after step S11, the processing method further includes:

[0077] The motor's condition is predicted based on historical operating data, and early warnings are issued based on the prediction results. This prediction allows for timely response to motor faults, ensuring the stability of motor operation.

[0078] The historical operation data is obtained from the operation data stored in the above embodiments, and each historical operation data is stored and retrieved according to the identification information.

[0079] S12. Determine the technical guidance information corresponding to the maintenance requirements.

[0080] The technical guidance information can be knowledge guidance items, but is not limited to this. Each piece of technical guidance information corresponds to one type of maintenance requirement, or multiple different pieces of technical guidance information correspond to the same type of maintenance requirement, or one piece of technical guidance information corresponds to multiple types of maintenance requirements.

[0081] In one embodiment, troubleshooting solutions described in traditional text can be converted into technical guidance information that can be displayed by XR devices, such as model animations, videos, audio, and images. By displaying technical guidance information in the form of 3D animations and videos, less experienced users can learn how to operate the system.

[0082] S13. Calculate the ranking index of the technical guidance information based on the operation data, and rank the technical guidance information based on the ranking index.

[0083] In one embodiment, Figure 3 The flowchart for calculating the ranking index of technical guidance information based on operational data includes:

[0084] S131. Select all operating data or a portion of the operating data corresponding to the maintenance requirements as the target operating data.

[0085] In one possible implementation, in order to reduce the computational load of the ranking index and improve the correlation between the ranking index calculation results and the inspection requirements, this implementation can determine a portion of the operating data corresponding to the maintenance requirements from multiple operating data as the target operating data, and then calculate the ranking index of the technical guidance information based on the target operating data.

[0086] In one possible implementation, in order to improve the accuracy of the sorting index, all running data can be used as the target running data.

[0087] S132. By analyzing the correlation between target operational data and technical guidance information, determine the first weight of each operational data.

[0088] The correlation between target operating data and technical guidance information can be determined through motor fault mechanism analysis and correlation analysis of historical fault occurrences with corresponding historical operating data. The first weight is then determined based on the correlation analysis results. The first weight is positively correlated with the correlation; the stronger the correlation, the larger the first weight, and vice versa.

[0089] S133. The ranking index of the technical guidance information is obtained by weighting each target's operational data according to the first weight. See the following formula for the ranking index:

[0090] I = V1P1 + V2P2 + ... + V n P n ;

[0091] Among them, V n P represents the running data of the nth target. n The first weight represents the data of the nth target, and I represents the ranking index.

[0092] In one possible implementation, in order to generate personalized sorting results based on the user's personal habits and historical selection frequency, and to correct the sorting index, the processing method further includes:

[0093] The number of times you have selected the information to obtain technical guidance.

[0094] The historical selection count refers to the number of times the user selected the corresponding technical guidance information based on the testing requirements during historical motor maintenance processes. The correlation between the maintenance requirements and the guidance information can be obtained based on the historical selection count. Each time the user selects the technical guidance information during the maintenance process, the corresponding historical selection count increases by one.

[0095] Step S133 specifically includes:

[0096] The data for each target operation is weighted according to the first weight, and the ranking index of the technical guidance information is obtained based on the weighted calculation result and the number of historical selections.

[0097] Furthermore, the coefficient for the historical selection frequency can be determined based on the number of historical selections. The initial coefficient can be set to an initial value and adjusted according to the historical selection frequency. If the historical selection frequency increases, the coefficient is increased accordingly; conversely, the coefficient is decreased.

[0098] The ranking index is calculated using the following formula:

[0099] I = (V1P1 + V2P2 + ... + V) n P n (a+KH);

[0100] Among them, Vn P represents the running data of the nth target. n The first weight represents the nth target running data, I represents the ranking index, K represents the coefficient, H represents the number of historical selections, and a represents the preset value. In this embodiment, a is preferably 1, but it can be adjusted according to the actual application scenario and is not limited to the content recorded in this embodiment.

[0101] In one embodiment, the processing method further includes:

[0102] The sorted technical guidance information is displayed using an XR device.

[0103] The ranking index for each piece of technical guidance information is calculated based on the received operational data and maintenance requirements. The items of technical guidance information are then listed in front of the XR device user according to the ranking index.

[0104] When an operator selects the corresponding technical guidance information, the historical selection count of that technical guidance information will be accumulated so that when the maintenance requirement occurs again, the ranking index of that technical guidance information will be improved.

[0105] In one embodiment, the processing method further includes:

[0106] The XR device displays the operating data and maintenance requirements.

[0107] The operating data and maintenance requirements can be displayed together with the technical guidance information, so that users can select the appropriate technical guidance information based on the corresponding operating data and maintenance requirements.

[0108] In one embodiment, the processing method further includes:

[0109] The camera identifies the device's identification code, generating a virtual scene of the corresponding motor device for display on the XR device.

[0110] In this embodiment, when a user is using an XR device to repair motor equipment, the XR device can automatically push relevant technical guidance information to the user's XR device for display based on the collected and analyzed operating data, so as to help the operator efficiently locate the repair needs and push the most effective solution.

[0111] The following specific implementation method will further illustrate this embodiment:

[0112] The system connects to sensors installed on the motor or to the motor-related control system, and acquires initial operating data in JSON format. This format includes a title (MotorDatas), an identifier (flag), a parameter value (value), a timestamp (time), a time, and a device identification code (sn). In this embodiment, the operating data includes temperature, humidity, and vibration sensor data along the X, Y, and Z axes. The JSON format is as follows:

[0113] {

[0114] "MotorDatas": [{

[0115] "flag": "HUM",

[0116] value: 65.2000

[0117] }, {

[0118] "flag": "TEM",

[0119] value: 24.3000

[0120] }, {

[0121] "flag": "VX",

[0122] value: 8.5000

[0123] }, {

[0124] "flag": "VY",

[0125] "value": "21.8000"

[0126] }, {

[0127] "flag": "VZ",

[0128] value: 7.6000

[0129] }],

[0130] "timestamp": "1664181792",

[0131] Time: 2022-09-26 08:43:12

[0132] "sn": "2013025698592"

[0133] }

[0134] The initial operating data is transmitted to the XR device via IoT technology. The initial operating data is then parsed to obtain operating data including specific real-time parameters. The operating data parsed from the above JSON data includes: temperature: 24.3; humidity: 65.2; vibration velocity in the X-axis direction: 8.5; vibration velocity in the Y-axis direction: 21.8; vibration velocity in the Z-axis direction: 7.6; timestamp: 1664181792; time: 2022-09-26 08:43:12; device identification code: 2013025698592.

[0135] After receiving the operating data, the system processes the data based on the device identification code 2013025698592, and performs noise reduction, automatic interpolation, and other processing on the data.

[0136] Traditional text-based troubleshooting solutions can be transformed into technical guidance information that can be displayed by XR devices, such as model animations, videos, audio, and images.

[0137] Each technical guidance message corresponds to one type of maintenance requirement, or multiple different knowledge items correspond to the same type of maintenance requirement, or one knowledge item corresponds to multiple types of maintenance requirements. Each technical guidance message contains a ranking index, which can be automatically adjusted based on received operating data and historical selection records to make subsequent pushes more accurate.

[0138] The formula for calculating the ranking index is as follows:

[0139] I = (V1P1 + V2P2 + ... + V) n P n (a+KH);

[0140] Among them, V n P represents the running data of the nth target. n The first weight represents the nth target running data, I represents the ranking index, K represents the coefficient, H represents the number of historical selections, and a represents the preset value. In this embodiment, a is preferably 1, but it can be adjusted according to the actual application scenario and is not limited to the content recorded in this embodiment.

[0141] In addition, XR devices use cameras to identify equipment identification codes and generate corresponding virtual scenes of the motor equipment for display. XR devices can also display maintenance needs, operating data, and sorted technical guidance information. These XR devices include, but are not limited to, AR (Augmented Reality) devices, VR (Virtual Reality) devices, and MR (Mixed Reality) devices.

[0142] Figure 4 A structural diagram of a processing device for motor maintenance is provided as an exemplary embodiment of the present invention. The processing device includes:

[0143] The first acquisition module 41 is used to acquire the motor's operating data and maintenance requirements;

[0144] Module 42 is used to determine the technical guidance information corresponding to the maintenance requirements;

[0145] The sorting module 43 is used to calculate the sorting index of the technical guidance information based on the running data, and to sort the technical guidance information based on the sorting index.

[0146] In one embodiment, the sorting module 43 includes:

[0147] The selection unit is used to select all or part of the operating data corresponding to the maintenance requirements as the target operating data.

[0148] The determining unit is configured to determine a first weight for each of the target operating data by analyzing the correlation between the target operating data and the technical guidance information;

[0149] The calculation unit is used to perform a weighted calculation on each of the target running data according to the first weight to obtain the ranking index of the technical guidance information.

[0150] In one embodiment, the processing apparatus further includes:

[0151] The second acquisition module is used to acquire the historical selection count corresponding to the technical guidance information;

[0152] The calculation unit is further configured to perform weighted calculation on each of the target running data according to the first weight, and obtain the ranking index of the technical guidance information based on the weighted calculation result and the number of historical selections.

[0153] In one embodiment, the calculation unit is further configured to determine a coefficient for the number of historical selections based on the number of historical selections;

[0154] The ranking index is calculated according to the following formula:

[0155] I = (V1P1 + V2P2 + ... + V) n P n (a+KH);

[0156] Among them, V n P represents the running data of the nth target. n The first weight of the nth target running data is represented by I, the ranking index is represented by K, the coefficient is represented by H, the number of historical selections is represented by a, and the preset value is represented by a.

[0157] In one embodiment, the first acquisition module 41 includes:

[0158] An acquisition unit is used to acquire the initial operating data of the motor, which is collected by sensors arranged on the motor.

[0159] The parsing unit is used to parse the initial running data to obtain the running data.

[0160] In one embodiment, the processing apparatus further includes:

[0161] The third acquisition module is used to acquire the identification information of the motor;

[0162] The storage module is used to store the operating data and maintenance requirements based on the identification information.

[0163] In one embodiment, the processing apparatus further includes:

[0164] The display module is used to display the sorted technical guidance information via an extended reality device;

[0165] In one embodiment, the display module is further configured to display the operating data and maintenance requirements via an extended reality device.

[0166] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the present invention according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0167] Figure 5 This is a structural diagram of an electronic device provided in an example embodiment of the present invention. Figure 5The electronic device 50 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0168] like Figure 5 As shown, the electronic device 50 can be manifested in the form of a general-purpose computing device, such as a server device. The components of the electronic device 50 may include, but are not limited to: at least one processor 51, at least one memory 52, and a bus 53 connecting different system components (including memory 52 and processor 51).

[0169] Bus 53 includes a data bus, an address bus, and a control bus.

[0170] The memory 52 may include volatile memory, such as random access memory (RAM) 521 and / or cache memory 522, and may further include read-only memory (ROM) 523.

[0171] The memory 52 may also include a program tool 525 (or utility) having a set (at least one) program module 524, such program module 524 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0172] The processor 51 performs various functional applications and data processing, such as the methods provided in any of the above embodiments, by running computer programs stored in the memory 52.

[0173] Electronic device 50 can also communicate with one or more external devices 54. This communication can be performed via input / output (I / O) interface 55. Furthermore, the model-generated electronic device 50 can also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapter 56. As shown, network adapter 56 communicates with other modules of the model-generated electronic device 50 via bus 53. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the model-generated electronic device 50, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0174] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0175] In one embodiment, the electronic device may include an XR device, such as HoloLens 2 glasses, etc. Figure 6 This is a schematic diagram of the processing flow of an XR device provided in an exemplary embodiment of the present invention. The XR device can run a motor maintenance processing method provided in this embodiment of the present invention. The XR device includes the following modules, each used to perform different functions:

[0176] The data access module is used to acquire motor operating data, data uploaded from the gateway, and stored historical operating data, and transmit the collected data to the data analysis module.

[0177] The data processing module is used to decode and encode the data transmitted by the data access module, and then perform data processing, including but not limited to storage, forwarding, noise reduction, and automatic interpolation and filling.

[0178] The display module categorizes and displays technical guidance information and maintenance requirements on the XR device according to user needs, as shown in the figure.

[0179] For details on the specific functions of each module in the XR device provided in this embodiment, please refer to the motor repair method provided in this embodiment.

[0180] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method provided in any of the above embodiments.

[0181] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0182] In a possible implementation, the present invention can also be implemented as a program product, which includes program code that, when the program product is run on a terminal device, causes the terminal device to execute the method implementing any of the above embodiments.

[0183] The program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0184] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A method for overhauling an electric motor, characterized in that, The processing method includes: Obtain motor operating data and maintenance requirements; Determine the technical guidance information corresponding to the maintenance requirements; The ranking index of the technical guidance information is calculated based on the operational data, and the technical guidance information is ranked based on the ranking index. The ranking index of the technical guidance information is calculated based on the operational data, including: Select all or part of the operational data corresponding to the maintenance requirements as the target operational data; By analyzing the correlation between the target operational data and the technical guidance information, a first weight is determined for each of the target operational data. The ranking index of the technical guidance information is obtained by weighting each target operational data according to the first weight; the first weight is positively correlated with the correlation. The processing method further includes: Obtain the historical selection count corresponding to the technical guidance information; The ranking index of the technical guidance information is obtained by weighting each of the target operation data according to the first weight, including: The target operational data is weighted according to the first weight, and a ranking index for the technical guidance information is obtained based on the weighted calculation result and the historical selection count, specifically including: The coefficient of the historical selection count is determined based on the historical selection count. The ranking index is calculated according to the following formula: I=(V1P1+V2P2+……V n P n )(a+KH); Among them, V n P represents the running data of the nth target. n The first weight of the nth target running data is represented by I, the ranking index is represented by K, the coefficient is represented by H, the number of historical selections is represented by a, and the preset value is represented by a.

2. The processing method as described in claim 1, characterized in that, Obtain motor operating data and maintenance requirements, including: The initial operating data of the motor is acquired by sensors arranged on the motor. The initial running data is parsed to obtain the running data.

3. The processing method as described in claim 1, characterized in that, After obtaining the motor's operating data and maintenance requirements, the following steps are taken: Obtain the identification information of the motor; The operating data and maintenance requirements are stored based on the identification information.

4. The processing method as described in claim 1, characterized in that, After sorting the technical guidance information based on the ranking index, the process includes: The sorted technical guidance information is displayed using an augmented reality device; And / or, after obtaining the motor's operating data and maintenance requirements, including: The operational data and maintenance requirements are displayed using an augmented reality device.

5. A processing device for motor maintenance, characterized in that, The processing device includes: The first acquisition module is used to acquire the motor's operating data and maintenance requirements; The determination module is used to determine the technical guidance information corresponding to the maintenance requirements; The sorting module is used to calculate the sorting index of the technical guidance information based on the running data, and sort the technical guidance information based on the sorting index. The sorting module specifically includes: a selection unit, used to select all or part of the operating data corresponding to the maintenance requirements as target operating data; a determination unit, used to determine a first weight for each target operating data by analyzing the correlation between the target operating data and the technical guidance information; and a calculation unit, used to perform a weighted calculation on each target operating data according to the first weight to obtain a sorting index for the technical guidance information, wherein the first weight is positively correlated with the correlation. The processing device further includes: a second acquisition module, used to acquire the historical selection count corresponding to the technical guidance information; The calculation unit is further configured to perform weighted calculation on each of the target running data according to the first weight, and obtain the ranking index of the technical guidance information according to the weighted calculation result and the number of historical selections; The calculation unit is also used to determine the coefficient of the historical selection number based on the historical selection number; The ranking index is calculated according to the following formula: I=(V1P1+V2P2+……V n P n )(a+KH); Among them, V n P represents the running data of the nth target. n The first weight of the nth target running data is represented by I, the ranking index is represented by K, the coefficient is represented by H, the number of historical selections is represented by a, and the preset value is represented by a.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and for running on the processor, characterized in that, When the processor executes the computer program, it implements the processing method for motor maintenance as described in any one of claims 1-4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the processing method for motor maintenance as described in any one of claims 1-4.

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