Wheel life prediction and operation and maintenance plan decision method and device and storage medium

Abstract

The invention provides a wheel life prediction and operation and maintenance plan decision method and device and a storage medium. The method comprises the following steps: acquiring data related to the remaining life of a wheel; generating a wheel residual life based on the wheel life related data and a prediction model obtained by pre-training; obtaining wheel turning repair related data, and generating a wheel turning repair plan based on the wheel turning repair related data; updating the remaining service life of the wheel based on the wheel turning repair plan; and generating an operation, maintenance and / or purchase plan corresponding to the updated wheel remaining life based on the updated wheel remaining life. According to the technical scheme, the remaining service life of the wheel can be estimated only by using a small amount of data, the data complexity is reduced, the prediction accuracy is improved, the turning wheel operation plan is flexibly generated, the potential influence of the turning wheel on the remaining service life is accurately reflected, the timeline of the maintenance task is automatically generated or optimized, and the maintenance efficiency is improved. The accurate matching of the maintenance activity and the actual demand is ensured, and the non-planned downtime is reduced.

Description

Technical Field

[0001] The present invention relates to the field of rail transportation, and in particular to a method, device and storage medium for wheel life prediction and operation and maintenance plan decision-making. Background Art

[0002] As a key component in the rail transit industry, accurate prediction of the remaining life of wheels is not only a basic requirement for ensuring driving safety, but also has a profound impact on operational efficiency, material procurement strategies, and the scientific and economic nature of maintenance plans. Accurate prediction of the remaining life of wheels can assist operators in optimizing train operation diagrams, planning vehicle maintenance and wheelset replacement time in advance, reasonably arranging shifts, reducing capacity losses caused by maintenance, and improving overall operational efficiency and service reliability. Based on the remaining life prediction data, the procurement department can more accurately estimate the demand for wheelsets and replacement cycles, avoiding excessive reserves that cause capital occupation, or insufficient inventory that causes emergency purchases that increase costs. Accurate predictions not only help the maintenance team to arrange work progress reasonably, but also effectively integrate maintenance resources, such as manpower, equipment, and sites. By planning wheelset replacement operations in advance, the maintenance department can concentrate resources for efficient maintenance, reduce downtime, and improve maintenance quality while ensuring that daily operations are not affected. Summary of the invention

[0003] To achieve the above objectives, the present invention proposes a wheel life prediction and operation and maintenance plan decision-making method, device and storage medium, which can be used to estimate the remaining life of the wheel using only historical wheel diameter and mileage data, reduce data complexity and improve prediction accuracy, flexibly generate wheel turning operation plans, accurately reflect the potential impact of wheel turning on the remaining service life, automatically generate or optimize the timeline of maintenance tasks, ensure that maintenance activities are accurately matched with actual needs, and reduce unplanned downtime.

[0004] A method for wheel life prediction and operation and maintenance plan decision-making proposed in an embodiment of the present invention includes: obtaining wheel life-related data: obtaining data related to the remaining life of the wheel; predicting wheel life: generating the remaining life of the wheel based on the wheel life-related data and a prediction model obtained by pre-training; generating a turning and repair plan: obtaining wheel turning and repair-related data, and generating a wheel turning and repair plan based on the wheel turning and repair-related data; updating wheel life: updating the remaining life of the wheel based on the wheel turning and repair plan; generating an operation and maintenance plan: generating a corresponding operation, maintenance and / or procurement plan based on the updated remaining life of the wheel.

[0005] In one embodiment, the wheel life-related data further includes: wheel diameter and / or mileage. It is possible to estimate the remaining life of the wheel using only historical wheel diameter and mileage data, reduce data complexity and improve prediction accuracy, flexibly generate wheel turning operation plans, accurately reflect the potential impact of wheel turning on the remaining service life, automatically generate or optimize the timeline of maintenance tasks, ensure that maintenance activities are accurately matched with actual needs, and reduce unplanned downtime

[0006] A wheel life prediction and operation and maintenance plan decision-making device proposed in an embodiment of the present invention includes: a wheel life related data acquisition module, configured to: acquire data related to the remaining life of the wheel; a wheel life prediction module, configured to: generate the remaining life of the wheel based on the wheel life related data and a pre-trained prediction model; a turning and repair plan generation module, configured to: acquire wheel turning and repair related data, and generate a wheel turning and repair plan based on the wheel turning and repair related data; a wheel life update module, configured to: update the remaining life of the wheel based on the wheel turning and repair plan; an operation and maintenance plan generation module, configured to: generate corresponding operation, maintenance and / or procurement plans based on the updated remaining life of the wheel. It is able to estimate the remaining life of the wheel using only a small amount of data, reduce data complexity and improve prediction accuracy, flexibly generate wheel turning operation plans, accurately reflect the potential impact of wheel turning on the remaining service life, automatically generate or optimize the timeline of maintenance tasks, ensure that maintenance activities are accurately matched with actual needs, and reduce unplanned downtime.

[0007] An electronic device proposed in an embodiment of the present invention includes: at least one processor; and a memory coupled to the at least one processor, wherein the memory is used to store instructions, and when the instructions are executed by the at least one processor, the processor executes the method described above.

[0008] An embodiment of the present invention provides a computer-readable storage medium on which computer instructions are stored. When the computer instructions are executed, the method described in any of the above embodiments is executed.

[0009] A computer program product provided in an embodiment of the present invention includes a computer program. When the computer program is executed by a processor, the method described in any one of the above embodiments is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The following drawings are intended only to illustrate and explain the present invention, and do not limit the scope of the present invention.

[0011] Figure 1 1 is a flow chart of a method 100 for wheel life prediction and operation and maintenance plan decision-making according to an embodiment of the present invention.

[0012] Figure 2 2 is a schematic diagram of the structure of a wheel life prediction and operation and maintenance plan decision-making device 200 according to an embodiment of the present invention.

[0013] Figure 3 is a schematic diagram of an electronic device 300 according to an embodiment of the present invention.

[0014] The following are the descriptions of the reference numerals:

[0015]

[0016] DETAILED DESCRIPTION

[0017] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, specific embodiments of the present invention are now described with reference to the accompanying drawings.

[0018] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0019] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0020] In actual production, the most commonly used method to predict wear in daily operations is to use the average value of the historical wheel diameter wear rate of the vehicle or the entire fleet as an estimate of the future wear rate to predict the remaining life of the wheelset. This method does not take into account the relationship between the actual wear rate and the wheel diameter size, and the prediction accuracy is low. Some people also use numerical simulation methods to predict the remaining life of the wheels based on the physical model of stress changes during the rolling contact of the wheelset, the wheel-rail coupling relationship and the mechanical properties of the wheel and rail materials. This method is carried out in an experimental environment and does not take into account the complexity of the actual operating conditions.

[0021] In terms of wheel wear and tear, although some existing systems can use vibration data analysis to predict wheel out-of-roundness, thereby providing early warning of the need for wheel wear and tear, these systems do not take into account wear predictions in daily operations. This limitation prevents us from directly grasping the specific trend of the overall remaining service life of the wheelset under different wear and tear plans, and also limits the effective integration of these prediction systems with the operation and maintenance plan formulation process, hindering more global and optimized resource planning and decision support.

[0022] Therefore, in the embodiments of the present invention, a more effective wheel life prediction and operation and maintenance plan decision-making method, device and storage medium are proposed.

[0023] Figure 1 FIG. 1 is a flow chart of a wheel life prediction and operation and maintenance plan decision method 100 according to an embodiment of the present invention. Figure 1 As shown, the method 100 may include:

[0024] Step S101, obtaining data related to wheel life: obtaining data related to the remaining life of the wheel.

[0025] In one embodiment, the wheel life related data further includes: wheel diameter and / or running mileage.

[0026] Specifically, the remaining life of the wheel is predicted through a pre-built prediction model, and its input may be the wheel diameter, mileage, etc.

[0027] Step S102, predicting wheel life: generating the remaining wheel life based on the wheel life related data and a prediction model obtained by pre-training.

[0028] In one embodiment, the predicting wheel life further includes: generating wheel wear amount and / or wheel wear rate based on the wheel life related data and a pre-trained prediction model, and generating remaining wheel life based on the wheel wear amount and / or wheel wear rate.

[0029] Specifically, the prediction model for predicting wheel wear amount and / or wheel wear rate can adapt to different data collection methods and different sampling frequencies, such as wheel diameter gauge measurement, lathe measurement, trackside monitoring mechanism measurement and other measurement methods and sampling frequencies.

[0030] Step S103, generating a wheel turning plan: acquiring wheel turning-related data, and generating a wheel turning plan based on the wheel turning-related data.

[0031] In one embodiment, generating a turning and repair plan further comprises:

[0032] The wheel turning and repair related indicators include: the demand and operation plan for wheel turning and repair of each system of the train;

[0033] A wheel turning and repair plan is generated based on the demand and the operation plan.

[0034] In one embodiment, the requirements of the various systems of the train for wheel turning and repair further include: vehicle status data, available status of yard resources and / or time requirements for wheel turning and repair of the vehicle online plan.

[0035] Specifically, the prediction conclusions of each system on the demand for wheel turning and repair can be comprehensively analyzed, and a customized turning and repair plan can be generated taking into account the current actual operating conditions.

[0036] Specifically, the decision on whether to perform wheel turning will take into account multiple indicators, such as vehicle mileage, operating hours, wheel size, vibration and impact between wheels and rails, and whether vehicle status data reaches the restriction conditions; yard resources, such as whether the lathe is available; whether the vehicle has an online plan. During the wheel turning period, the vehicle cannot be online for 3-5 days. And these data will come from different systems, such as vehicle mileage from the operation monitoring system, wheel size from the trackside detection system combined with manual measurement by personnel, and vibration and impact from the wheel monitoring system. Combined with the above-mentioned multiple systems to predict the demand for wheel turning, if it is predicted that wheel turning is needed in the next three months, the time period for wheel turning can be selected to generate a specific turning and repair plan in combination with the yard resources and the plan for the vehicle to go online.

[0037] Step S104, updating the wheel life: updating the remaining wheel life based on the wheel turning and repair plan.

[0038] Specifically, turning will shorten the service life of the wheel, so the prediction of the remaining life of the wheel needs to be updated by taking into account the actual turning.

[0039] Step S105, generating an operation and maintenance plan: based on the updated remaining life of the wheel, generating a corresponding operation, maintenance and / or procurement plan.

[0040] Specifically, the operation plan, maintenance plan, and procurement plan can be automatically generated based on the remaining life prediction results, and users can make manual adjustments based on actual conditions.

[0041] In one embodiment, the method further comprises:

[0042] Step S106, wheel life warning: visually display the updated remaining wheel life, and generate warning information based on the updated remaining wheel life and a preset remaining wheel life warning threshold.

[0043] Specifically, the predicted remaining service life of the wheelset can be intuitively presented through a visual interface, and for wheels that are about to reach the replacement threshold, early warning notifications can be automatically triggered to ensure that timely measures are taken.

[0044] Figure 2 FIG. 2 is a schematic diagram of the structure of a wheel life prediction and operation and maintenance plan decision-making device 200 according to an embodiment of the present invention. Figure 2 As shown, the device 200 may include:

[0045] The wheel life related data acquisition module 201 is configured to: acquire data related to the remaining life of the wheel;

[0046] The wheel life prediction module 202 is configured to: generate the remaining life of the wheel based on the wheel life related data and the prediction model obtained by pre-training;

[0047] The wheel turning plan generating module 203 is configured to: obtain wheel turning related data, and generate a wheel turning plan based on the wheel turning related data;

[0048] The wheel life updating module 204 is configured to: update the remaining life of the wheel based on the wheel turning and repair plan;

[0049] The operation and maintenance plan generating module 205 is configured to generate a corresponding operation, maintenance and / or procurement plan based on the updated remaining life of the wheel.

[0050] The present invention also provides an electronic device 300 . Figure 3 FIG. 3 is a schematic diagram of an electronic device 300 according to an embodiment of the present invention. Figure 3 As shown, the electronic device 300 includes a processor 310 and a memory 320 , wherein the memory 320 stores instructions, wherein when the instructions are executed by the processor 310 , the method 100 described above is implemented.

[0051] The present invention further provides a computer-readable storage medium on which computer instructions are stored. When the computer instructions are executed, the method described above is executed.

[0052] The present invention also provides a computer program product, comprising a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0053] Some aspects of the methods and apparatus of the present invention may be performed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". The processor may be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLCs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors or combinations thereof. In addition, various aspects of the present invention may be expressed as computer products located in one or more computer-readable media, which include computer-readable program codes. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, tapes, etc.), optical disks (e.g., compact disks (CDs), digital versatile disks (DVDs) ...), smart cards, and flash memory devices (e.g., cards, sticks, key drives ...).

[0054] Flowchart is used here to illustrate the operations performed according to the method of the embodiment of the present application. It should be understood that the above operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously. At the same time, other operations may be added to these processes, or a certain step or several steps of operations may be removed from these processes.

[0055] It should be understood that although this specification is described according to various embodiments, not every embodiment contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

[0056] The above description is only an illustrative embodiment of the present invention and is not intended to limit the scope of the present invention. Any equivalent changes, modifications and combinations made by any person skilled in the art without departing from the concept and principle of the present invention shall fall within the scope of protection of the present invention.

Claims

1. A wheel life prediction and operation and maintenance plan decision-making method (100), characterized in that: The method comprises: Obtaining wheel life-related data (S101): obtaining data related to the remaining life of the wheel; Predicting wheel life (S102): generating the remaining life of the wheel based on the wheel life related data and a prediction model obtained by pre-training; Generating a wheel turning plan (S103): acquiring wheel turning-related data, and generating a wheel turning plan based on the wheel turning-related data; Updating wheel life (S104): updating the remaining life of the wheel based on the wheel turning and repair plan; Generate an operation and maintenance plan (S105): Based on the updated remaining life of the wheel, generate a corresponding operation, maintenance and / or procurement plan.

2. The method according to claim 1, characterized in that The wheel life related data further includes: wheel diameter and / or running mileage.

3. The method according to claim 1, characterized in that The predicting wheel life (S102) further comprises: The wheel wear amount and / or wheel wear rate are generated based on the wheel life related data and a pre-trained prediction model, and the wheel remaining life is generated based on the wheel wear amount and / or wheel wear rate.

4. The method according to claim 1, characterized in that: The generating of the turning and repair plan (S103) further comprises: The wheel turning and repair related indicators include: the demand and operation plan for wheel turning and repair of each system of the train; A wheel turning and repair plan is generated based on the demand and the operation plan.

5. The method according to claim 4, characterized in that The requirements of various train systems for wheel turning and repair further include: vehicle status data, available status of yard resources and / or time requirements for wheel turning and repair based on vehicle online plan.

6. The method according to claim 1, characterized in that The method further comprises: Wheel life warning (S106): Visually display the updated remaining wheel life, and generate warning information based on the updated remaining wheel life and a preset remaining wheel life warning threshold.

7. A wheel life prediction and operation and maintenance plan decision-making device (200), characterized in that: The device comprises: The wheel life related data acquisition module (201) is configured to: acquire data related to the remaining life of the wheel; A wheel life prediction module (202) is configured to: generate a wheel remaining life based on the wheel life related data and a pre-trained prediction model; A wheel turning plan generating module (203) is configured to: obtain wheel turning related data, and generate a wheel turning plan based on the wheel turning related data; A wheel life updating module (204) is configured to: update the remaining life of the wheel based on the wheel turning and repair plan; The operation and maintenance plan generating module (205) is configured to generate a corresponding operation, maintenance and / or procurement plan based on the updated remaining life of the wheel.

8. An electronic device (300), comprising: at least one processor (310); as well as A memory (320) coupled to the at least one processor (310), the memory (320) being used to store instructions, which, when executed by the at least one processor (310), causes the processor (310) to perform the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions, when executed, execute the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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