A method, device and equipment for intelligent maintenance of rail transit vehicles

Abstract

The present application relates to an intelligent maintenance method, device and equipment for rail transit vehicles, which belongs to the technical field of maintenance of rail transit vehicles, and includes predicting the predicted time of failure of a component to be repaired based on historical data and current operation data; determining the correlation between the component to be repaired and the associated component based on a pre-established maintenance chain, wherein the associated component refers to a component associated with the component to be repaired; determining the maintenance time of the component to be repaired based on the predicted time, the correlation and the existing maintenance process data, wherein the existing maintenance process data includes the planned maintenance time of the associated component; determining the repair cost of repairing the component to be repaired and the replacement cost of replacing it based on the existing maintenance process data; determining the maintenance method of the component to be repaired based on the repair cost and the replacement cost, wherein the maintenance method includes repair and replacement; formulating a maintenance plan based on the maintenance method and maintenance time. The present application has the effect of reasonably arranging the maintenance plan.

Description

Technical Field

[0001] The present application relates to the technical field of rail transit vehicle maintenance, and in particular to a method, device and equipment for intelligent maintenance of rail transit vehicles. Background Art

[0002] The various components of rail transit vehicles, especially the running parts such as bogies, bearing boxes and bearings, will suffer certain damages as the rail transit vehicles run, which may cause failures. Therefore, during the operation of rail transit vehicles, regular maintenance of rail transit vehicles is an important measure to ensure the safety of personnel.

[0003] The traditional planned maintenance model stipulates a unified maintenance cycle, but does not fully consider the actual use of each component. When a component is about to reach the planned maintenance time or the component has just been repaired, other components also have abnormalities and need to be repaired. This may lead to high-frequency and unnecessary repetitive operations in a short period of time during the maintenance work, reducing the utilization rate of working hours and increasing labor costs. Summary of the invention

[0004] In order to reasonably arrange the maintenance plan, the present application provides a method, device and equipment for intelligent maintenance of rail transit vehicles.

[0005] In the first aspect, the present application provides a rail transit vehicle intelligent maintenance method, which adopts the following technical solution:

[0006] A rail transit vehicle intelligent maintenance method, comprising:

[0007] Predict the time when the repaired parts will fail based on historical data and current operation data;

[0008] Determine the degree of association between the component to be repaired and associated components according to a pre-established repair chain, wherein the associated components refer to components associated with the component to be repaired;

[0009] Determine the inspection time of the component to be repaired according to the predicted time, the correlation degree and the existing repair process data, wherein the existing repair process data includes the planned repair time of the associated component;

[0010] Determining the repair cost of repairing the component to be repaired and the replacement cost of replacing the component with a new one based on the existing repair process data;

[0011] Determine the maintenance method of the component to be repaired according to the repair cost and the replacement cost, wherein the maintenance method includes repair and replacement;

[0012] A maintenance plan is formulated based on the maintenance method and the maintenance time.

[0013] By adopting the above technical scheme, the parts to be repaired may be affected by the related parts, so that the maintenance time of the parts to be repaired is affected by the planned maintenance time of the related parts. Therefore, a more accurate maintenance time is determined by predicting the time, correlation and existing maintenance process data, and by comprehensively considering the predicted time and the planned maintenance time, the maintenance time is reasonably arranged to reduce the high-frequency and unnecessary repetitive operations on the parts to be repaired, thereby improving the utilization rate of working hours; through the level of repair cost and replacement cost, the low cost is determined as the maintenance method of the parts to be repaired to reduce the maintenance cost; a reasonable maintenance plan is formulated according to the maintenance method and maintenance time to facilitate the maintenance work.

[0014] Preferably, the repair chain is established according to the disassembly sequence between the component to be repaired and the associated components.

[0015] Preferably, determining the degree of association between the component to be repaired and the associated components according to the pre-established maintenance chain includes:

[0016] The disassembly interval between the associated component and the component to be repaired is determined, and the degree of the association is determined according to the disassembly interval.

[0017] Preferably, determining the maintenance time of the component to be repaired according to the predicted time, the correlation degree and the existing maintenance process data includes:

[0018] The associated components with the highest degree of association are used as linkage components;

[0019] respectively calculating the time difference between the predicted time and the planned repair time of all linkage components;

[0020] Determining whether the time difference is not greater than a preset time;

[0021] If so, the earlier time between the predicted time and the planned repair time whose time difference is not greater than the preset time is used as the repair time of the component to be repaired;

[0022] If not, the correlation degree is reduced by one level, and the associated components with the correlation degree equal to the correlation degree after being reduced by one level are used as linkage components, and the process returns to the step of respectively calculating the time difference between the predicted time and the planned repair time of all linkage components;

[0023] When the correlation degree drops to the lowest level, and the time difference is still greater than the preset time, the predicted time when the component to be repaired fails is used as the maintenance time.

[0024] By adopting the above technical scheme, the higher the correlation, the greater the influence between the associated components and the components to be repaired. For the associated components with the highest correlation, if the time difference between the planned repair time and the predicted time is not greater than the preset time, the previous time will be used as the maintenance time of the components to be repaired. This not only ensures that the components to be repaired are repaired before the expected failure, but also ensures that the components to be repaired and the associated components with a time difference of no more than the preset time are repaired together, thereby reducing the situation of high-frequency and unnecessary repetitive operations on the components to be repaired and improving the utilization rate of working hours.

[0025] Preferably, the determining of the inspection method of the component to be repaired according to the repair cost and the replacement cost further includes:

[0026] When the repair cost is low, determining that the repair method of the component to be repaired is the repair;

[0027] When the replacement cost is low, it is determined that the repair method of the component to be repaired is the replacement.

[0028] Preferably, when the repair cost is low, after determining that the repair method of the component to be repaired is the repair, the method further includes:

[0029] Determine whether the repair site and repair personnel are available during the said maintenance time;

[0030] If so, finally determining that the inspection method of the component to be repaired is the repair;

[0031] If not, then it is finally determined that the repair method of the component to be repaired is the replacement.

[0032] Preferably, when the replacement cost is low, after determining that the repair method of the component to be repaired is the replacement, the method further includes:

[0033] Determine whether the replacement parts have been purchased before the maintenance time, wherein the replacement parts are parts that replace the parts to be repaired;

[0034] If so, finally determining that the repair method of the component to be repaired is the replacement;

[0035] If not, then it is finally determined that the maintenance method of the component to be repaired is the repair.

[0036] In the second aspect, the present application provides an intelligent maintenance device for rail transit vehicles, which adopts the following technical solution:

[0037] An intelligent maintenance device for rail transit vehicles, comprising:

[0038] A prediction module is used to predict the predicted time of failure of the component to be repaired based on historical data and current operation data;

[0039] A first determination module is used to determine the degree of association between the component to be repaired and associated components according to a pre-established maintenance chain, wherein the associated components refer to components associated with the component to be repaired;

[0040] A second determination module is used to determine the maintenance time of the component to be repaired according to the predicted time, the correlation degree and the existing maintenance process data, wherein the existing maintenance process data includes the planned maintenance time of the associated component;

[0041] A third determination module is used to determine the repair cost of repairing the component to be repaired and the replacement cost of replacing the component with a new one based on the existing repair process data;

[0042] A fourth determination module determines a maintenance method of the component to be repaired according to the repair cost and the replacement cost, wherein the maintenance method includes repair and replacement; and

[0043] A formulation module formulates a maintenance plan according to the maintenance method and the maintenance time.

[0044] In the third aspect, the present application provides an intelligent maintenance device for rail transit vehicles, which adopts the following technical solution:

[0045] An intelligent maintenance device for rail transit vehicles comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes the intelligent maintenance method for rail transit vehicles described in any one of the first aspects.

[0046] In summary, the present application includes at least one of the following beneficial technical effects:

[0047] 1. The parts to be repaired may be affected by the associated parts, so that the maintenance time of the parts to be repaired is affected by the planned maintenance time of the associated parts. Therefore, a more accurate maintenance time is determined by predicting the time, correlation and existing maintenance process data. By comprehensively considering the predicted time and the planned maintenance time, the maintenance time is reasonably arranged to reduce the high-frequency and unnecessary repetitive operations on the parts to be repaired, thereby improving the utilization rate of working hours. According to the level of repair cost and replacement cost, the low cost is determined as the maintenance method of the parts to be repaired to reduce the maintenance cost. According to the maintenance method and maintenance time, a reasonable maintenance plan is formulated to facilitate the maintenance work;

[0048] 2. The higher the correlation, the greater the impact between the associated components and the components to be repaired. For the associated components with the highest correlation, if the time difference between the planned repair time and the predicted time is not greater than the preset time, the previous time will be used as the maintenance time of the components to be repaired. This not only ensures that the components to be repaired are repaired before the expected failure, but also ensures that the components to be repaired and the associated components with a time difference of no more than the preset time are repaired together, reducing the situation of high-frequency, unnecessary repetitive operations on the components to be repaired and improving the utilization of working hours. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0050] Figure 1 It is a flow chart of the intelligent maintenance method for rail transit vehicles provided in the embodiment of the present application;

[0051] Figure 2 It is a structural block diagram of the intelligent maintenance device for rail transit vehicles provided in an embodiment of the present application;

[0052] Figure 3 It is a structural schematic diagram of the intelligent maintenance equipment for rail transit vehicles provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0054] This embodiment provides a rail transit vehicle intelligent maintenance method, such as Figure 1 As shown, the main process of the method is described as follows (steps S101 to S106):

[0055] Step S101: predicting the predicted time of failure of the component to be repaired based on historical data and current operation data.

[0056] In this embodiment, the historical data includes the historical operation data of the component to be repaired and the time when the failure occurred. The historical data is analyzed. If the component to be repaired is about to fail whenever a certain operation data appears, the operation data is defined as the early warning operation data, and the failure time difference between the time when the early warning operation data appears and the time when the failure occurs is calculated. For example, the time when the early warning operation data appears is January 1, 2000, and the time when the failure occurs is January 9, 2000, then the failure time difference is 8 days.

[0057] Obtain multiple warning operation data, calculate multiple fault time differences accordingly, and select the fault time difference with the highest frequency as the final fault time difference. For example, within ten years, there are 100 times of the same warning operation data, among which there are 20 times of fault time difference of 8 days, 60 times of fault time difference of 9 days, and 20 times of fault time difference of 10 days, then 9 days is taken as the final fault time difference.

[0058] The current operating data of the component to be repaired is obtained by installing various sensors on rail transit vehicles, and the current operating data is compared with the warning operating data. If the current operating data is the same or similar to the warning operating data, the predicted time of failure of the component to be repaired is predicted based on the failure time difference and the current time.

[0059] Among them, the specific method for determining whether the current operating data is similar to the warning operating data is: respectively obtain the average values ​​of the current operating data and the warning operating data in the same time period, calculate the difference between the average values ​​of the two, and if the difference is less than the preset value, determine that the current operating data is similar to the warning operating data.

[0060] An example is given of predicting the failure time of a component to be repaired based on the failure time difference and the current time: the current time is August 1, 2020, and the failure time difference is 9 days, so the predicted time is August 10, 2020.

[0061] Step S102: determining the degree of association between the component to be repaired and associated components according to the pre-established repair chain, wherein the associated components refer to components associated with the component to be repaired.

[0062] In this embodiment, the associated parts refer to parts that have a disassembly relationship with the part to be repaired, and the maintenance chain is established according to the disassembly sequence between the part to be repaired and the associated parts. For example, if the part to be repaired is a bearing, the maintenance chain is X-bogie-bearing box-bearing-motor-Y, where X, bogie, bearing box, motor and Y are all associated parts, and the disassembly sequence refers to disassembling X, bogie, bearing box, bearing, motor and Y in sequence.

[0063] Determine the disassembly interval between the associated parts and the parts to be repaired. The smaller the disassembly interval, the higher the correlation. For example, the disassembly interval between the bearing box and the bearing is 0, the disassembly interval between the motor and the bearing is also 0, the disassembly interval between the bogie and the bearing is 1, the disassembly interval between Y and the bearing is 1, and the disassembly interval between X and the bearing is 2. The highest correlation with the bearing is the bearing box and the motor, the next highest correlation is the bogie and Y, and the next highest correlation is X.

[0064] Step S103: determining the inspection time of the component to be repaired according to the predicted time, the correlation degree and the existing repair process data, wherein the existing repair process data includes the planned repair time of the associated components.

[0065] In this embodiment, the planned maintenance time refers to the maintenance time formulated according to the daily maintenance plan.

[0066] The associated component with the highest correlation is used as the linkage component, and the time difference between the predicted time and the planned repair time of all the linkage components is calculated respectively; then it is determined whether the time difference is not greater than the preset time; if so, the previous time between the predicted time and the planned repair time whose time difference is not greater than the preset time is used as the maintenance time of the component to be repaired; if not, the correlation is reduced by one level, and the associated component with the correlation equal to the correlation after the reduction by one level is used as the linkage component, and the step of calculating the time difference between the predicted time and the planned repair time of all the linkage components is returned. And so on, until there is a time difference that is not greater than the preset time, the previous time is used as the maintenance time of the component to be repaired, or when the correlation is reduced to the lowest level, the time difference is still greater than the preset time, and the predicted time when the component to be repaired fails is used as the maintenance time.

[0067] For example, the preset time is 20 days; the correlation between the bearing box and the bearing, and the motor and the bearing is the highest, and the time difference T between the predicted time of the bearing and the planned repair time of the bearing box is calculated. 1 , the time difference between the predicted time of the bearing and the planned repair time of the motor T 2 If the time difference T 1 and time difference T 2 If both the forecast time and the time difference T are not more than 20 days, 1 and time difference T 2 The previous time in is taken as the maintenance time of the component to be repaired; if only the time difference T 1 If the forecast time and time difference T are not more than 20 days, 1 The previous time in is taken as the maintenance time of the component to be repaired; if only the time difference T 2 If the forecast time and time difference T are not more than 20 days, 2 The previous time in is taken as the maintenance time of the component to be repaired; if the time difference T 1 and time difference T 2 If both are greater than 20 days, the bogie and Y are regarded as linkage components, and then the time difference between the predicted time and the planned repair time of the linkage components is calculated.

[0068] Furthermore, the planned repair time of the linkage components can also be changed. Specifically, the previous time is used as the planned repair time of the linkage components whose time difference is not greater than the preset time, so that the components to be repaired and the linkage components are repaired together. For example, the planned repair time of the bearing box is November 1, 2020, the predicted time of the bearing is November 10, 2020, and the planned repair time of the motor is November 20, 2020. It can be seen that the time difference T 1 and time difference T2 Both are no more than 20 days. Therefore, November 1, 2020 will be the inspection time for the bearings, and November 1, 2020 will also be the planned maintenance time for the bearing box and motor.

[0069] Another method can be used to determine the maintenance time of the parts to be repaired: every time the rail transit vehicle runs to a predetermined mileage, the entire rail transit vehicle will be overhauled, that is, the entire rail transit vehicle will be overhauled, and the repair time of the rail transit vehicle for the whole vehicle overhaul will be determined. If the repair time is before the predicted time, and the time difference between the repair time and the predicted time is not greater than the preset time, the repair time will be used as the maintenance time of the parts to be repaired. Similarly, if the repair time is before the planned repair time of a related component, and the time difference between the repair time and the planned repair time is not greater than the preset time, the repair time will be used again as the planned repair time of the related component.

[0070] Step S104: Determine the repair cost of the component to be repaired and the replacement cost of the component to be replaced based on the existing repair process data.

[0071] In this embodiment, the existing maintenance process data includes a pre-planned maintenance method and a corresponding maintenance cost of the component to be repaired. The maintenance method includes repair and replacement, and the maintenance cost includes repair cost and replacement cost.

[0072] Existing maintenance process data also includes specific information about repair and replacement. For the repair method, the specific information includes the repair personnel information, the repair site information and the expected repair time; for the replacement method, the specific information includes the replacement personnel information and the replacement parts information, among which the replacement parts are new parts that replace the parts to be repaired, and the replacement parts information includes the model of the replacement parts, the manufacturer and whether the replacement parts have been purchased.

[0073] The repair cost is the sum of the labor costs of the repair personnel and the loss costs caused by the inability of the rail transit vehicle to operate within the expected repair time. The existing repair data includes the single-day loss costs caused by the inability of the rail transit vehicle to operate in one day. The single-day loss costs can be used to calculate the loss costs caused by the inability of the rail transit vehicle to operate within the expected repair time; the replacement cost is the sum of the labor costs of the replacement personnel and the cost of purchasing replacement parts.

[0074] Step S105: Determine the maintenance method of the component to be repaired according to the repair cost and the replacement cost, wherein the maintenance method includes repair and replacement.

[0075] The repair cost and the replacement cost are judged. When the repair cost is low, the repair method of the component to be repaired is determined to be repair; when the replacement cost is low, the repair method of the component to be repaired is determined to be replacement.

[0076] Furthermore, after determining that the repair cost is low, determine whether the repair site and repair personnel are both free during the maintenance time. That is to say, on the day of the maintenance time, determine whether there is free space at the repair site for the rail transit vehicle to stay for maintenance, and also determine whether the repair personnel can go to the repair site to repair the rail transit vehicle; if so, then ultimately determine that the maintenance method for the parts to be repaired is repair; if not, then ultimately determine that the maintenance method for the parts to be repaired is replacement.

[0077] Furthermore, after determining that the replacement cost is low, determine whether the replacement parts are purchased before the maintenance time (including the day of the maintenance time), that is, determine whether there are replacement parts that can replace the parts to be repaired; if so, then ultimately determine that the maintenance method for the parts to be repaired is replacement; if not, then ultimately determine that the maintenance method for the parts to be repaired is repair.

[0078] Furthermore, if at least one of the repair site and the repair personnel is not idle on the day of the overhaul, and the replacement parts cannot be purchased on the day of the overhaul, the idle time when both the repair site and the repair personnel are idle is determined, and the idle time closest to the current time is determined as the repairable time. For example, if the repair site and the repair personnel are both idle between November 5, 2020 and November 15, 2020, November 5, 2020 is used as the repairable time. Recalculate the repair cost from the current time to the repairable time.

[0079] It also determines the estimated replacement time when the replacement parts can be purchased, and recalculates the replacement cost from the current time to the estimated replacement time.

[0080] When the recalculated repair cost is low, the repair method of the component to be repaired is determined to be repair; when the recalculated replacement cost is low, the replacement method of the component to be repaired is determined to be replacement.

[0081] Step S106: Formulate a maintenance plan according to the maintenance method and maintenance time.

[0082] In this embodiment, the maintenance plan can be presented in the form of a table, and the maintenance method and maintenance time are filled in the table according to a preset format for staff to view.

[0083] Optionally, you can also fill in the form with detailed information about the repair or replacement.

[0084] In order to better implement the above method, an embodiment of the present application also provides a rail transit vehicle intelligent maintenance device, which can be specifically integrated into rail transit vehicle intelligent maintenance equipment, such as a terminal or server. The terminal can include but is not limited to mobile phones, tablet computers or desktop computers.

[0085] Figure 2A structural block diagram of an intelligent maintenance device for rail transit vehicles provided in an embodiment of the present application, such as Figure 2 As shown, the device mainly includes:

[0086] Prediction module 201, used to predict the predicted time of failure of the component to be repaired based on historical data and current operation data;

[0087] A first determination module 202 is used to determine the degree of association between the component to be repaired and the associated components according to a pre-established maintenance chain, wherein the associated components refer to components associated with the component to be repaired;

[0088] The second determination module 203 is used to determine the maintenance time of the component to be repaired according to the predicted time, the correlation degree and the existing maintenance process data, wherein the existing maintenance process data includes the planned maintenance time of the associated component;

[0089] The third determination module 204 is used to determine the repair cost of repairing the component to be repaired and the replacement cost of replacing it with a new one based on the existing repair process data;

[0090] The fourth determination module 205 determines the maintenance method of the component to be repaired according to the repair cost and the replacement cost, wherein the maintenance method includes repair and replacement; and

[0091] The formulation module 206 formulates a maintenance plan according to the maintenance method and maintenance time.

[0092] The various variations and specific examples in the methods provided in the above embodiments are also applicable to the intelligent maintenance device for rail transit vehicles in this embodiment. Through the above detailed description of the intelligent maintenance method for rail transit vehicles, those skilled in the art can clearly know the implementation method of the intelligent maintenance device for rail transit vehicles in this embodiment. For the sake of brevity of the specification, it will not be described in detail here.

[0093] In order to better execute the procedure of the above method, the embodiment of the present application also provides a rail transit vehicle intelligent maintenance equipment, such as Figure 3 As shown, the rail transit vehicle intelligent maintenance equipment 300 includes a memory 301 and a processor 302 .

[0094] The rail transit vehicle intelligent maintenance device 300 can be implemented in various forms, including mobile phones, tablet computers, PDAs, laptop computers, desktop computers and other devices.

[0095] The memory 301 may be used to store instructions, programs, codes, code sets or instruction sets. The memory 301 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 predicting the predicted time of failure of a component to be repaired based on historical data and current operating data, etc.), and instructions for implementing the intelligent maintenance method for rail transit vehicles provided in the above embodiment, etc.; the data storage area may store data involved in the intelligent maintenance method for rail transit vehicles provided in the above embodiment, etc.

[0096] The processor 302 may include one or more processing cores. The processor 302 calls the data stored in the memory 301 by running or executing the instructions, programs, code sets or instruction sets stored in the memory 301, and performs various functions and processes data of the present application. The processor 302 may be at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller and a microprocessor. It is understandable that for different devices, the electronic device used to implement the above-mentioned processor 302 function can also be other, and the embodiment of the present application is not specifically limited.

[0097] The embodiment of the present application provides a computer-readable storage medium, for example, including: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes. The computer-readable storage medium stores a computer program that can be loaded by a processor and execute the intelligent maintenance method for rail transit vehicles of the above embodiment.

[0098] The specific embodiments of the present application are merely explanations of the present application and are not limitations of the present application. After reading this specification, those skilled in the art may make modifications to the embodiments without any creative contribution as needed. However, as long as they are within the scope of the claims of the present application, they are protected by the patent law.

Claims

1. A rail transit vehicle intelligent maintenance method, It is characterized in that include: Predict the time when the repaired parts will fail based on historical data and current operation data; According to a pre-established maintenance chain, determining the degree of association between the component to be repaired and the associated components, wherein the associated components refer to components associated with the component to be repaired; the maintenance chain is established according to the disassembly sequence between the component to be repaired and the associated components; Determine the inspection time of the component to be repaired according to the predicted time, the correlation degree and the existing repair process data, wherein the existing repair process data includes the planned repair time of the associated component; Determining the repair cost of repairing the component to be repaired and the replacement cost of replacing the component with a new one based on the existing repair process data; Determine the maintenance method of the component to be repaired according to the repair cost and the replacement cost, wherein the maintenance method includes repair and replacement; Formulate a maintenance plan based on the maintenance method and maintenance time; Determining the degree of association between the component to be repaired and the associated component based on the pre-established repair chain includes: determining a disassembly interval between the associated component and the component to be repaired, and determining the degree of association based on the disassembly interval; The method of determining the inspection time of the component to be repaired according to the predicted time, the correlation degree and the existing maintenance process data includes: taking the associated component with the highest correlation degree as a linkage component; respectively calculating the time difference between the predicted time and the planned repair time of all the linkage components; judging whether the time difference is not greater than a preset time; if so, taking the previous time between the predicted time and the planned repair time whose time difference is not greater than the preset time as the inspection time of the component to be repaired; if not, reducing the correlation degree by one level, and taking the associated component with the correlation degree equal to the correlation degree after reducing by one level as a linkage component, and returning to the step of respectively calculating the time difference between the predicted time and the planned repair time of all the linkage components; when the correlation degree is reduced to the lowest level, and the time difference is still greater than the preset time, the predicted time when the component to be repaired fails is taken as the inspection time.

2. The method according to claim 1, It is characterized in that The method of determining the maintenance method of the component to be repaired according to the repair cost and the replacement cost also includes: When the repair cost is low, determining that the repair method of the component to be repaired is the repair; When the replacement cost is low, it is determined that the repair method of the component to be repaired is the replacement.

3. The method according to claim 2, It is characterized in that After determining that the repair method of the component to be repaired is the repair when the repair cost is low, the method further includes: Determine whether the repair site and repair personnel are available during the said maintenance time; If so, finally determining that the inspection method of the component to be repaired is the repair; If not, then it is finally determined that the repair method of the component to be repaired is the replacement.

4. The method according to claim 2, It is characterized in that After determining that the repair method of the component to be repaired is the replacement when the replacement cost is low, the method further includes: Determine whether the replacement parts have been purchased before the maintenance time, wherein the replacement parts are parts that replace the parts to be repaired; If so, finally determining that the repair method of the component to be repaired is the replacement; If not, then it is finally determined that the maintenance method of the component to be repaired is the repair.

5. An intelligent maintenance device for rail transit vehicles, It is characterized in that The method comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and executes the method according to any one of claims 1 to 4.

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