A method and device for optimizing the layout of high-level maintenance resources for EMUs

Abstract

The present invention provides a method and device for optimizing the layout of high-level maintenance resources for EMUs. The method comprises: obtaining the operation parameter information of the EMUs; calculating the health value of the EMUs according to the operation parameter information of the EMUs; predicting the high-level maintenance time of the EMUs according to the health value, and determining the EMUs to be overhauled; determining the components to be overhauled of the EMUs to be overhauled according to the health values ​​of the components of the EMUs to be overhauled; constructing an objective function based on the maintenance time, maintenance cost and health value targets of the high-level maintenance of the EMUs to be overhauled, determining the target maintenance components from the components to be overhauled, and forming a maintenance plan for the EMUs to be overhauled.

Description

Technical Field

[0001] The present invention belongs to the technical field of rail transit, and in particular relates to a method and a device for optimizing the layout of advanced maintenance resources for multiple units. Background Art

[0002] The existing EMU advanced maintenance resource allocation mainly relies on experience judgment and traditional planning methods. For example, CN202011414072.2 only considers the maintenance time issue.

[0003] The resource layout methods in the existing technology often fail to fully consider the complex relationship between maintenance time, cost, health value target and resource utilization, which will lead to problems such as unreasonable resource allocation, low production efficiency and cost overrun. Although some studies have tried to use simulation models for optimization, most of these models are limited to two-dimensional space and it is difficult to intuitively display the entire process of maintenance operations and their relationship with resource layout.

[0004] Therefore, there is still much room for improvement in the existing technology in the allocation of advanced maintenance resources for EMUs. How to take into account the maintenance time, cost, and health value targets at the same time is a technical problem that needs to be solved. Summary of the invention

[0005] The present invention provides a method and device for optimizing the layout of resources for advanced maintenance of multiple units, which can simultaneously ensure that the maintenance time is short, the maintenance cost is low, and the health value of the multiple units is greatly improved during the advanced maintenance process.

[0006] On the one hand, a method for optimizing the layout of high-level maintenance resources of a train set is provided, comprising:

[0007] Obtain the operating parameter information of the EMU;

[0008] The health value of the EMU is calculated based on the operating parameter information of the EMU;

[0009] Predict the advanced maintenance time of EMUs based on health values ​​and determine the EMUs to be repaired;

[0010] Determine the components to be inspected of the EMU to be inspected according to the health values ​​of the components of the EMU to be inspected;

[0011] An objective function is constructed based on the maintenance time, maintenance cost and health value of the EMU to be overhauled. The value of the objective function is used as the optimization target. The target maintenance components are determined from the components to be overhauled to form a maintenance plan for the EMU to be overhauled.

[0012] Optionally, the health value of the EMU is calculated based on the health value of the system, the health value of the subsystem, the health value of the functional group and the health value of the functional component;

[0013] The EMU includes one or more of the above-mentioned systems, each of the above-mentioned systems includes one or more of the above-mentioned subsystems, each of the above-mentioned subsystems includes one or more of the above-mentioned functional groups, and each of the above-mentioned functional groups includes one or more of the above-mentioned functional parts.

[0014] Optionally, predicting the advanced maintenance time of the EMU according to the health value and determining the EMU to be repaired includes:

[0015] Determine the first health threshold When the health value of the EMU is lower than the first health threshold, it is determined that the EMU needs advanced maintenance and the EMU is classified as an EMU to be repaired.

[0016] Optionally, the components to be inspected of the EMU to be inspected are determined according to the health values ​​of the components of the EMU to be inspected:

[0017] The health value of the EMU to be repaired is lower than the second health threshold The functional parts are divided into components to be repaired.

[0018] Optionally, the objective function is as follows:

[0019] , Indicates maintenance time, Indicates the maintenance cost, Indicates the health value of the advanced repaired train. , They are the cost normalization factor and the maintenance time normalization factor respectively.

[0020] Optionally, the value of the objective function is used as the optimization target, a target maintenance component is determined from the components to be maintained, and a maintenance plan for the EMU to be maintained is formed, including:

[0021] Set the number of target overhaul components to the independent variable n;

[0022] Assign values ​​to the independent variable n starting from 1; after each assignment of n, search for the optimal pre-maintenance plan under the current value of n; and monitor the health value and objective function value of the optimal pre-maintenance plan under each value of n;

[0023] When a pre-maintenance plan is found whose health value after maintenance is greater than the third health threshold, n is increased to n+1, and the objective function value of the optimal pre-maintenance plan under n+1 is detected. The objective function value of the optimal pre-maintenance plan under n size differences;

[0024] like Greater than or equal to , then search for the optimal pre-maintenance plan under n+2, and continue to compare the objective function value of the optimal pre-maintenance plan under n+2 The objective function value of the optimal pre-maintenance plan under n+1 until the objective function value no longer increases;

[0025] like Less than or equal to , then the optimal pre-maintenance plan under n is adopted as the maintenance plan.

[0026] Optionally, searching for the optimal pre-maintenance solution under n includes:

[0027] Arrange the components to be repaired in order;

[0028] Randomly select n components to be repaired from the sorted components to form a pre-repair plan;

[0029] Obtain the objective function value of the pre-maintenance plan according to the objective function calculation;

[0030] Repeat the above steps periodically until the objective function values ​​of all pre-maintenance plans are calculated, and the pre-maintenance plan with the largest objective function value is the optimal pre-maintenance plan.

[0031] On the other hand, a high-level maintenance resource layout optimization device for EMU is provided, comprising:

[0032] An acquisition module is used to obtain the operation parameter information of the EMU;

[0033] A health value calculation module, used to calculate the health value of the EMU according to the operating parameter information of the EMU;

[0034] A determination module is used to predict the advanced maintenance time of the EMU according to the health value and determine the EMU to be repaired; according to the health value of each component of the EMU to be repaired, determine the components to be repaired of the EMU to be repaired;

[0035] The maintenance plan determination module is used to construct an objective function based on the maintenance time, maintenance cost and health value targets of the advanced maintenance of the EMU to be maintained, and use the value of the objective function as the optimization target to determine the target maintenance components from the components to be maintained, so as to form a maintenance plan for the EMU to be maintained.

[0036] On the other hand, an electronic device is provided, which includes the device for optimizing the layout of advanced maintenance resources for EMUs as described above.

[0037] On the other hand, a computer-readable storage medium is provided, in which at least one program code is stored, and the program code is executed by a processor to implement a method for optimizing the layout of advanced maintenance resources of an EMU as described in any one of the above items.

[0038] The beneficial effects brought by the technical solution provided by the present invention are:

[0039] The present invention provides a method for optimizing the layout of resources for advanced maintenance of EMUs, which obtains the health value of the EMU in real time, determines the health status of the EMU, and performs advanced maintenance on the EMU when the health status of the EMU does not meet the requirements. In the process of advanced maintenance, under the conditions of ensuring low cost of advanced maintenance of the EMU, high maintenance time period, and high health value of the EMU after maintenance, the components that can be repaired on the EMU are screened, so as to find the optimal combination of components to be repaired, ensuring low maintenance cost, high maintenance efficiency, and a large improvement in the health value of the EMU. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 A flow chart of a method for optimizing the layout of high-level maintenance resources for EMUs provided by the present invention;

[0042] Figure 2 A structural block diagram of a motor vehicle group provided by the present invention;

[0043] Figure 3 A structural schematic diagram of a bogie system provided by the present invention;

[0044] Figure 4 A structural block diagram of a high-level maintenance resource layout optimization device for EMUs provided by the present invention;

[0045] Figure 5 This is a structural block diagram of an electronic device provided by the present invention.

[0046] The reference numerals are as follows:

[0047] 11: Acquisition module; 12: Health value calculation module; 13: Determination module; 14: Maintenance plan determination module;

[0048] 21: processor; 22: memory. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] Figure 1 This is a flow chart of a method for optimizing the layout of high-level maintenance resources for EMUs provided by the present invention. Figure 1 ,include:

[0051] S101. Obtaining operation parameter information of the EMU.

[0052] In this embodiment, the operation parameter information of the EMU includes on-board sensor data.

[0053] S102. Calculate the health value of the EMU according to the operating parameter information of the EMU.

[0054] In this embodiment, in step S102:

[0055] The health value of the EMU is calculated based on the health value of the system, the health value of the subsystem, the health value of the functional group and the health value of the functional component; the EMU includes one or more of the systems, each of the systems includes one or more of the subsystems, each of the subsystems includes one or more of the functional groups, and each of the functional groups includes one or more of the functional components.

[0056] In one example, a first weight coefficient is assigned to each functional component, and the first weight coefficient is used to represent the influence of the functional component under the functional group on the health value of the functional group; a second weight coefficient is assigned to each functional group, and the second weight coefficient is used to represent the influence of the functional group under each subsystem on the health value of the subsystem; a third weight coefficient is assigned to each subsystem, and the third weight coefficient is used to represent the influence of each subsystem on the health value of the system; a fourth weight coefficient is assigned to each system, and the fourth weight coefficient is used to represent the influence of each system on the health value of the EMU.

[0057] In this embodiment, by assigning weights to the systems, subsystems, functional groups and functional parts of the EMU, the health values ​​of the functional parts of the EMU can be determined by on-board sensors, and thus the health values ​​of the functional groups, subsystems, systems, and the EMU can be calculated.

[0058] In this embodiment, the first to fourth weight coefficients are allocated by inviting experts in the field of EMU diagnosis to score in the form of a questionnaire and by obtaining the failure rates of systems, subsystems, functional groups, and functional parts from historical maintenance data.

[0059] Figure 2 This is a structural block diagram of a train set provided in this embodiment. Figure 2 ,exist Figure 2 The EMU includes 15 systems in total, among which the traction power supply system is divided into traction system and power supply system. The in-car system is divided into passenger information system, air conditioning system, water supply and drainage system, exterior door and in-car facility system, and driving facility system.

[0060] Taking the bogie system as an example, Figure 3 The subsystems, functional groups and functional parts of the bogie system are given.

[0061] The bogie system includes a wheel axle component subsystem, and the wheel axle component subsystem includes a wheel axle functional group, a wheel spindle functional group and a brake disc functional group.

[0062] exist Figure 3 In the system, each system, subsystem, function group and function key is also coded to facilitate searching during advanced maintenance.

[0063] by Figure 3 For example, the fourth weight coefficient of the bogie system can be 0.3, the third weight coefficient of the wheel axle subsystem can be 0.25 (in addition to the wheel axle system, the bogie system also includes other subsystems, not shown in the figure). In the functional group, the second weight coefficient of the wheel axle can be 0.36, the first weight coefficient of the wheel can be 0.43, the first weight coefficient of the axle can be 0.31, and the first weight coefficient of the axle box bearing can be 0.26.

[0064] Of course, the above are some examples provided by the present invention, and in actual implementation, the weights can be set as needed.

[0065] The EMU system function classification is divided into four levels: system, subsystem, functional group, and functional parts, using 4-bit coding. It is divided into 9 envelopes, 15 systems, and 80 subsystems. The components of the EMU can be classified under the corresponding subsystem.

[0066] S103. Predict the advanced maintenance time of the EMU according to the health value, and determine the EMU to be repaired.

[0067] In one example, step S103 includes:

[0068] Determine the first health threshold When the health value of the EMU is lower than the first health threshold, it is determined that the EMU needs advanced maintenance and the EMU is classified as an EMU to be repaired.

[0069] In this embodiment, whether the EMU needs maintenance is determined by monitoring the health value of the EMU.

[0070] For example, the first health threshold The value range is 50%~60%. For example, 55%.

[0071] S104. Determine the components to be inspected of the EMU to be inspected according to the health value of each component of the EMU to be inspected.

[0072] In one example, step S104 includes:

[0073] The health value of the EMU to be repaired is lower than the second health threshold The functional parts are divided into components to be repaired.

[0074] In this embodiment, whether a functional component needs to be replaced is determined by the second health threshold. For example, if the health value of some functional components is high, there is no need to repair or replace them.

[0075] S105. Construct an objective function based on the maintenance time, maintenance cost and health value of the high-level maintenance of the EMU to be overhauled, take the value of the objective function as the optimization target, determine the target maintenance components from the components to be overhauled, and form a maintenance plan for the EMU to be overhauled.

[0076] In one example, step S105 includes:

[0077] Step 1: Set the number of target maintenance components as the independent variable n.

[0078] In step 1, in order to search for the optimal maintenance plan, it is necessary to search for solutions under each value of n to find the functional parts that most need to be replaced.

[0079] For example, when n is equal to 1, a functional component that needs to be replaced most can be found and searched. The functional component that needs to be replaced most is the functional component with the lowest replacement cost, the shortest replacement time and the largest health value of the EMU after replacement.

[0080] For example, when n is equal to 2, a combination of 2 functional components can be searched.

[0081] For another example, when n is equal to 3, a combination of 3 functional components can be searched.

[0082] Since different functional parts have different replacement costs, replacement times, and different improvements to the health of the EMU, the optimal solution can be found by changing the value of n to ensure that when the EMU is repaired with this solution, the replacement cost is the lowest, the replacement time is the shortest, and the improvement to the health of the EMU is the greatest.

[0083] Step 2, assign values ​​to the independent variable n starting from 1; after each assignment of n, search for the optimal pre-maintenance plan under the current value of n; and monitor the health value and objective function value of the optimal pre-maintenance plan under each value of n.

[0084] That is, in step 2, every time the value of n increases by 1, an optimal pre-maintenance plan will be searched.

[0085] In this embodiment, searching for the optimal pre-maintenance solution under n conditions includes:

[0086] The first step is to sort the components to be repaired in order.

[0087] In the second step, n components to be repaired are randomly selected from the sorted components to form a pre-repair plan.

[0088] The third step is to obtain the objective function value of the pre-maintenance plan based on the objective function calculation.

[0089] Among them, the objective function is as follows:

[0090] , Indicates maintenance time, Indicates the maintenance cost, Indicates the health value of the advanced repaired train. , They are the cost normalization factor and the maintenance time normalization factor respectively.

[0091] In this embodiment, the maintenance time is calculated as follows:

[0092] , where m is the index of the functional group, represents the decomposition end time of functional group m, Represents the maintenance completion time of all functional parts under functional group m. Represents the end time of the assembly of the functional group.

[0093] In this embodiment, the calculation formula of the maintenance cost is as follows:

[0094]

[0095] in, is the replacement cost of functional component n under functional group m, represents the transportation cost of functional part n per unit distance, represents the transportation distance between maintenance station i and maintenance station e, Represents the frequency of transportation of functional part n between equipment i and equipment e.

[0096] In this embodiment, the calculation formula of the train health value is as follows:

[0097]

[0098] in, Indicates Weight coefficient, The value range is from 1 to 4. Indicates functional parts.

[0099] The fourth step is to repeat the above steps periodically until the objective function values ​​of all pre-maintenance plans are calculated, and the pre-maintenance plan with the largest objective function value is the optimal pre-maintenance plan.

[0100] Step 3: After finding a pre-maintenance plan with a post-maintenance health value greater than the third health threshold, increase n to n+1 and detect the objective function value of the optimal pre-maintenance plan under n+1. The objective function value of the optimal pre-maintenance plan under n size difference.

[0101] In this embodiment, the optimal pre-maintenance solution has the following characteristics: short maintenance time, low maintenance cost, and maximum improvement in the health value of the EMU.

[0102] As n increases, the number of components to be repaired in the maintenance plan increases. The increase in the number of components to be repaired usually leads to an increase in maintenance time, maintenance cost, and health value. Indicates maintenance time , maintenance cost and the health of the advanced repaired train The transformation relationship, , They are the cost normalization factor and the maintenance time normalization factor respectively. The size of the objective function represents "short maintenance time, low maintenance cost, and high health value". The larger the objective function, the closer it is to the optimal maintenance plan.

[0103] Among them, the third health threshold is the minimum health value that the advanced repaired EMU needs to have, and the third health threshold is greater than the first health threshold.

[0104] Step 4: If Greater than or equal to , then search for the optimal pre-maintenance plan under n+2, and continue to compare the objective function value of the optimal pre-maintenance plan under n+2 The objective function value of the optimal pre-maintenance plan under n+1 until the objective function value no longer increases.

[0105] As the value of n increases, according to The calculated objective function value will increase first, and then decrease after reaching a peak value. In step 4, the peak value of the objective function value is found to determine the optimal maintenance plan from the multiple optimal pre-maintenance plans found.

[0106] Step 5: If Less than or equal to , then the optimal pre-maintenance plan under n is adopted as the maintenance plan.

[0107] The present invention provides a method for optimizing the layout of resources for advanced maintenance of EMUs, which obtains the health value of the EMU in real time, determines the health status of the EMU, and performs advanced maintenance on the EMU when the health status of the EMU does not meet the requirements. In the process of advanced maintenance, under the conditions of ensuring low cost of advanced maintenance of the EMU, high maintenance time period, and high health value of the EMU after maintenance, the components that can be repaired on the EMU are screened, so as to find the optimal combination of components to be repaired, ensuring low maintenance cost, high maintenance efficiency, and a large improvement in the health value of the EMU.

[0108] Figure 4 This is a structural block diagram of a high-level maintenance resource layout optimization device for EMUs provided by the present invention. Figure 4 ,include:

[0109] The acquisition module 11 is used to obtain the operation parameter information of the EMU;

[0110] A health value calculation module 12 is used to calculate the health value of the EMU according to the operation parameter information of the EMU;

[0111] The determination module 13 is used to predict the advanced maintenance time of the EMU according to the health value and determine the EMU to be repaired; according to the health value of each component of the EMU to be repaired, determine the components to be repaired of the EMU to be repaired;

[0112] The maintenance plan determination module 14 is used to construct an objective function based on the maintenance time, maintenance cost and health value targets of the advanced maintenance of the EMU to be maintained, and use the value of the objective function as the optimization target to determine the target maintenance components from the components to be maintained, so as to form a maintenance plan for the EMU to be maintained.

[0113] Figure 5 This is a structural block diagram of an electronic device provided by the present invention. Figure 5 , electronic devices may include Figure 4 The above-mentioned EMU high-level maintenance resource layout optimization device. Generally, the electronic device includes: a processor 21 and a memory 22.

[0114] The processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. The memory 22 may include one or more computer-readable storage media, which may be non-transitory. The memory 22 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 22 is used to store at least one instruction, which is used to be executed by the processor 21 to implement a method for optimizing the layout of advanced maintenance resources of a train set performed by an electronic device provided in the method embodiment of the present application.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the layout of high-level maintenance resources for EMUs, characterized in that: include: Obtain the operating parameter information of the EMU; The health value of the EMU is calculated based on the operating parameter information of the EMU; Predict the advanced maintenance time of EMUs based on health values ​​and determine the EMUs to be repaired; Determine the components to be inspected of the EMU to be inspected according to the health values ​​of the components of the EMU to be inspected; An objective function is constructed based on the maintenance time, maintenance cost and health value of the EMU to be overhauled. The value of the objective function is used as the optimization target. The target maintenance components are determined from the components to be overhauled to form a maintenance plan for the EMU to be overhauled. The objective function is as follows: , Indicates maintenance time, Indicates the maintenance cost, Indicates the health value of the train after advanced repairs. , are the cost normalization factor and the maintenance time normalization factor respectively; Taking the value of the objective function as the optimization target, the target maintenance components are determined from the components to be maintained, and a maintenance plan for the EMU to be maintained is formed, including: Set the number of target overhaul components to the independent variable n; Assign values ​​to the independent variable n starting from 1; after each assignment of n, search for the optimal pre-maintenance plan under the current value of n; and monitor the health value and objective function value of the optimal pre-maintenance plan under each value of n; When a pre-maintenance plan is found whose health value after maintenance is greater than the third health threshold, n is increased to n+1, and the objective function value of the optimal pre-maintenance plan under n+1 is detected. The objective function value of the optimal pre-maintenance plan under n size differences; like Greater than or equal to , then search for the optimal pre-maintenance plan under n+2, and continue to compare the objective function value of the optimal pre-maintenance plan under n+2 The objective function value of the optimal pre-maintenance plan under n+1 until the objective function value no longer increases; like Less than , then the optimal pre-maintenance plan under n is adopted as the maintenance plan.

2. The method for optimizing the layout of high-level maintenance resources of EMUs according to claim 1 is characterized in that: The health value of the EMU is calculated based on the health value of the system, the health value of the subsystem, the health value of the functional group and the health value of the functional parts; The EMU includes one or more of the above-mentioned systems, each of the above-mentioned systems includes one or more of the above-mentioned subsystems, each of the above-mentioned subsystems includes one or more of the above-mentioned functional groups, and each of the above-mentioned functional groups includes one or more of the above-mentioned functional parts.

3. The method for optimizing the layout of high-level maintenance resources of EMUs according to claim 1, characterized in that: Predict the advanced maintenance time of EMUs based on health values ​​and determine the EMUs to be repaired, including: Determine the first health threshold When the health value of the EMU is lower than the first health threshold, it is determined that the EMU needs advanced maintenance and the EMU is classified as an EMU to be repaired.

4. The method for optimizing the layout of high-level maintenance resources of EMUs according to claim 1, characterized in that: According to the health value of each component of the EMU to be repaired, determine the components to be repaired of the EMU to be repaired: The health value of the EMU to be repaired is lower than the second health threshold The functional parts are divided into components to be repaired.

5. The method for optimizing the layout of high-level maintenance resources of EMUs according to claim 1 is characterized in that: Search for the best pre-maintenance solution under n conditions, including: Arrange the components to be repaired in order; Randomly select n components to be repaired from the sorted components to form a pre-repair plan; Obtain the objective function value of the pre-maintenance plan according to the objective function calculation; Repeat the above steps periodically until the objective function values ​​of all pre-maintenance plans are calculated, and the pre-maintenance plan with the largest objective function value is the optimal pre-maintenance plan.

6. A high-level maintenance resource layout optimization device for EMUs, characterized in that: The EMU high-level maintenance resource layout optimization device is used to execute the method according to any one of claims 1 to 5, comprising: An acquisition module is used to obtain the operation parameter information of the EMU; A health value calculation module, used to calculate the health value of the EMU according to the operating parameter information of the EMU; A determination module is used to predict the advanced maintenance time of the EMU according to the health value and determine the EMU to be repaired; according to the health value of each component of the EMU to be repaired, determine the components to be repaired of the EMU to be repaired; The maintenance plan determination module is used to construct an objective function based on the maintenance time, maintenance cost and health value targets of the advanced maintenance of the EMU to be maintained, and use the value of the objective function as the optimization target to determine the target maintenance components from the components to be maintained, so as to form a maintenance plan for the EMU to be maintained.

7. An electronic device, characterized in that: The electronic equipment includes an EMU high-level maintenance resource layout optimization device as described in claim 6.

8. A computer-readable storage medium, characterized in that: At least one program code is stored in the computer-readable storage medium, and the program code is executed by a processor to implement a method for optimizing the layout of advanced maintenance resources for EMUs as described in any one of claims 1 to 5.

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