Train operation scheduling method and device based on train-ground integrated system and train

Abstract

The invention provides a train operation scheduling method based on a train-ground integrated system. The train operation scheduling method can be applied to the technical field of railway vehicle operation and management. The train operation scheduling method comprises the following steps: acquiring state monitoring information of each component configured on a plurality of candidate trains, operation mileage information of each component, maintenance record information of each component, historical operation environment information of the plurality of candidate trains and monitoring information of a plurality of to-be-operated lines; based on the state monitoring information of each component, the running mileage information of each component, the maintenance record information of each component and the historical running environment information of each candidate train, generating health state information of each candidate train; generating state information of each to-be-operated line based on the monitoring information of each to-be-operated line; and based on the health state information of each candidate train and the state information of each to-be-operated line, generating an operation scheduling plan for each candidate train so as to schedule each candidate train to operate on each to-be-operated line.

Description

Technical Field

[0001] The present disclosure relates to the technical field of rail vehicle operation and management, and more specifically, to a train operation scheduling method, device and train based on a vehicle-ground integrated system. Background Art

[0002] Under the traditional electromechanical system integration mode, the information between the rail vehicle system and the ground systems is independent and the control is decentralized, which makes the efficiency of the coordinated operation and scheduling between the rail vehicle system and the ground systems low. For example: the train dispatcher, section dispatcher, and yard dispatcher each have their own responsibilities, the vehicle operation failure requires manual communication and dispatch, the vehicle daily inspection is performed manually, there is no data interaction between the ground system and equipment, and there is no data interaction between vehicle operation and ground maintenance. The feedback of train status information, maintenance information, and running line status information is not timely, forming multiple information islands, affecting the efficiency of train dispatching and operation. Summary of the invention

[0003] In view of this, the present disclosure provides a train operation scheduling method, device and train based on a vehicle-ground integrated system.

[0004] According to one aspect of the present disclosure, a train operation scheduling method based on a vehicle-ground integrated system is provided, including: obtaining status monitoring information of each component configured on multiple candidate trains, running mileage information of each component, maintenance record information of each component, historical operating environment information of multiple candidate trains and monitoring information of multiple lines to be operated; generating health status information of each candidate train based on the status monitoring information of each component, the running mileage information of each component, the maintenance record information of each component and the historical operating environment information of each candidate train; generating status information of each line to be operated based on the monitoring information of each line to be operated; and generating an operation scheduling plan for each candidate train based on the health status information of each candidate train and the status information of each line to be operated, so as to schedule each candidate train to operate on each line to be operated.

[0005] According to an embodiment of the present disclosure, based on the status monitoring information of each component, the running mileage information of each component, the maintenance record information of each component and the historical operating environment information of each candidate train, the health status information of each candidate train is generated, including: extracting the historical operating environment information of each component from the historical operating environment information of each candidate train; generating the remaining life information of each component based on the running mileage information of each component, the historical operating environment information of each component and the maintenance record information of each component; and generating the health status information of each candidate train based on the remaining life information of each component of the same candidate train and the status monitoring information of each component.

[0006] According to an embodiment of the present disclosure, based on the running mileage information of each component, the historical running environment information of each component and the maintenance record information of each component, the remaining life information of each component is generated respectively, including: inputting the running mileage information of each component, the historical running environment information of each component and the maintenance record information of each component into a trained first target model, and outputting the remaining life information of each component respectively; wherein the first target model is obtained by training a first initial model using the historical remaining life of the sample component as a label, and utilizing the historical running mileage, the historical running environment and the historical maintenance record.

[0007] According to an embodiment of the present disclosure, based on the remaining life information of each component of the same candidate train and the status monitoring information of each component, the health status information of each candidate train is generated, including: inputting the remaining life information of each component based on the same candidate train and the status monitoring information of each component into a trained second target model, and outputting the health status information of each candidate train respectively; wherein the second target model is obtained by training the second initial model using the historical failure rate of each sample train as a label and utilizing the historical remaining life and historical monitoring status of the components of each sample train.

[0008] According to an embodiment of the present disclosure, the monitoring information of the lines to be operated includes the monitoring information of the contact network, the track monitoring information and the tunnel monitoring information corresponding to the lines to be operated; based on the monitoring information of each line to be operated, the status information of each line to be operated is generated, including: inputting the monitoring information of each contact network, each track monitoring information and each tunnel monitoring information corresponding to each line to be operated into a trained third target model to generate the status information of each line to be operated; wherein the third target model is obtained by training the third initial model with the status of the sample operating line as a label, using the historical monitoring information of the contact network, the historical monitoring information of the track and the historical monitoring information of the tunnel corresponding to the sample operating line.

[0009] According to an embodiment of the present disclosure, based on the health status information of each candidate train and the status information of each line to be operated, an operation scheduling plan for each candidate train is generated to schedule each candidate train to operate on each line to be operated, including: matching based on the health status information of each candidate train and the status information of each line to be operated to obtain an initial matching result; verifying the initial matching result based on the remaining life information of each component in each candidate train to obtain a verification result; and in response to the verification result being passed, generating an operation scheduling plan based on the initial matching result.

[0010] Another aspect of the present disclosure provides a train operation scheduling device based on a vehicle-ground integrated system, including an acquisition module, a first generation module, a second generation module, and a third generation module. The acquisition module is used to acquire the status monitoring information of each component configured on multiple candidate trains, the running mileage information of each component, the maintenance record information of each component, the historical operating environment information of multiple candidate trains, and the monitoring information of multiple lines to be operated. The first generation module is used to generate the health status information of each candidate train based on the status monitoring information of each component, the running mileage information of each component, the maintenance record information of each component, and the historical operating environment information of each candidate train. The second generation module is used to generate the status information of each line to be operated based on the monitoring information of each line to be operated; and the third generation module is used to generate an operation scheduling plan for each candidate train based on the health status information of each candidate train and the status information of each line to be operated, so as to schedule each candidate train to operate on each line to be operated.

[0011] Another aspect of the present disclosure provides a train, including: an acquisition module, used to acquire an operation scheduling plan obtained by the above method; and a generation module, used to generate an operation instruction based on the operation scheduling plan to control the train to run according to the operation scheduling plan.

[0012] Another aspect of the present disclosure provides an electronic device, including: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the above method.

[0013] Another aspect of the present disclosure provides a computer program product, which includes computer executable instructions, and the instructions are used to implement the above method when executed.

[0014] According to the embodiments of the present disclosure, through the vehicle-ground integrated system, the status monitoring information of each component configured on the train, the running mileage information of each component, the maintenance record information of each component, the historical operating environment information of multiple candidate trains and the monitoring information of multiple lines to be operated can be obtained in time. Based on the above information, the health status information of each candidate train and the status information of each line to be operated are generated accordingly. Through the generated health status information and the status information of the lines to be operated, a reasonable train operation scheduling plan is finally generated efficiently to schedule each candidate train to run on each line to be operated. The above-mentioned operation scheduling plan generation process utilizes the data interaction between the vehicle and the ground daily train inspection system, and more reasonably and efficiently evaluates the health status of the train and the status of the train's operating line, effectively shortening the time for formulating the operation scheduling plan and improving the efficiency of train operation scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0016] Figure 1 An exemplary system architecture to which a train operation scheduling method based on a vehicle-ground integrated system can be applied according to an embodiment of the present disclosure is schematically shown;

[0017] Figure 2 The working principle diagram of the novel daily train inspection system according to the embodiment of the present disclosure is schematically shown;

[0018] Figure 3 A flow chart of a train operation scheduling method based on a vehicle-ground integrated system according to an embodiment of the present disclosure is schematically shown;

[0019] Figure 4 The following schematically shows a process diagram of generating health status information according to an embodiment of the present disclosure;

[0020] Figure 5 A flow chart of a train operation scheduling method based on a vehicle-ground integrated system according to an embodiment of the present disclosure is schematically shown;

[0021] Figure 6 The structure block diagram of the train operation dispatching device based on the vehicle-ground integrated system according to the embodiment of the present disclosure is schematically shown;

[0022] Figure 7 A block diagram of an electronic device suitable for implementing a train operation scheduling method for a vehicle-ground integrated system according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0023] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0024] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0025] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0026] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0027] In the embodiments of the present disclosure, the collection, updating, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the data involved (for example, including but not limited to user personal information) are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information, network security, and national security.

[0028] In the embodiments of the present disclosure, the user's authorization or consent is obtained before obtaining or collecting the user's personal information.

[0029] Overhaul refers to the maintenance process of disassembling, cleaning, inspecting, flaw detection, and repairing important vehicle parts when the vehicle's mileage or running time reaches the specified value, and conducting comprehensive inspection, debugging, and testing of the vehicle to restore the vehicle's comprehensive performance and meet the requirements of the regulations and quality acceptance standards. Daily train inspection refers to a daily technical inspection of the train, which is a comprehensive technical inspection of the entire train before the train is marshaled and ready to depart, or before the train arrives at the station and has not yet been disassembled. Ensure that the train is in good technical condition, discover and deal with potential faults in a timely manner, and ensure the safe operation of the train.

[0030] Under the traditional electromechanical system integration mode, the information between the rail vehicle system and the ground systems is independent and the control is decentralized, which makes the efficiency of the coordinated operation and scheduling between the rail vehicle system and the ground systems low. For example: the train dispatcher, the section dispatcher, and the yard dispatcher each have their own responsibilities, and the driver needs to communicate with the section dispatcher through telephone fax data in case of vehicle operation failure; the daily vehicle inspection is performed manually; there is no trackside detection equipment, and there is no data interaction between daily inspection and overhaul, and there is no interaction between vehicle operation data and maintenance data; the train status information, maintenance information, and running line status information are not fed back in time. Therefore, the process of evaluating the health status of the train, the status of the train running line, and the operation and scheduling of the train based on the above two evaluation results will consume a lot of manpower and material resources and take a long time, and the efficiency of train operation scheduling, fault judgment and maintenance is low.

[0031] In view of this, the embodiments of the present disclosure can timely obtain the status monitoring information of each component configured on the train, the running mileage information of each component, the maintenance record information of each component, the historical operating environment information of multiple candidate trains, and the monitoring information of multiple lines to be operated through the vehicle-ground integrated system. Based on the above information, the health status information of each candidate train and the status information of each line to be operated are generated accordingly. Through the generated health status information and the status information of the lines to be operated, a reasonable train operation scheduling plan is finally efficiently generated to schedule each candidate train to run on each line to be operated. The above-mentioned operation scheduling plan generation process utilizes the data interaction between the vehicle and the ground daily train inspection system, and more reasonably and efficiently evaluates the health status of the train and the status of the train's operating line, effectively shortening the time for formulating the operation scheduling plan and improving the efficiency of train operation scheduling.

[0032] The embodiments of the present disclosure relate to the vehicle system and ground inspection and maintenance system in the vehicle-ground integrated system, with vehicle operation and inspection business as the core, using artificial intelligence, industrial Internet, Internet of Things, operations optimization, three-dimensional visualization and other advanced technologies, through real-time perception of vehicle operation and inspection status, combined with vehicle key component inspection process optimization, reorganizing vehicle maintenance production mode, and replanning the yard layout structure. The yard data and vehicle data flow and information flow are connected, and the vehicle data guides the yard inspection and maintenance operation and maintenance, and the inspection and maintenance operation and maintenance data supports the full life cycle management of the vehicle, thereby generating a highly operable and strategically reliable train operation and scheduling method, improving the efficiency of train operation and scheduling, and providing support for the standard specifications of the new digital yard construction.

[0033] Figure 1 The exemplary system architecture of the train operation scheduling method based on the vehicle-ground integrated system according to the embodiment of the present disclosure is schematically shown. It should be noted that: Figure 1What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0034] like Figure 1 As shown, the system architecture 100 according to this embodiment includes a vehicle system 110 , a ground signal system 120 , a ground inspection and maintenance system 130 , and a ground application service platform 140 .

[0035] The vehicle system 110 includes an on-board network subsystem 111 and an on-board signaling device 112 and other related subsystems. During the operation of the train, the data provided by the train includes but is not limited to the following: train operation mode, such as traction mode, braking mode, coasting mode, traction or braking level information, train mileage, train fault diagnosis information, train signaling device PHM (Prognostics and Health Management) data and related diagnostic information, among which the train PHM diagnostic data can be used to guide daily train inspection behavior.

[0036] The above data can be transmitted by the vehicle to the ATS (Automatic Train Supervision) subsystem of the ground signal system 120 through a wireless communication channel, and the acquired vehicle data can be superimposed. The data superimposed by the ground signal system 120 includes but is not limited to the following: train number information, train location information, and train speed information.

[0037] The signal system is then transmitted to the ground inspection and maintenance system 130 . The data provided by the ground inspection and maintenance system 130 to the ground application service platform include but are not limited to the following: daily train inspection and diagnosis information, component replacement information, and repair process and system information. The data is then transmitted to the ground application service platform 140 .

[0038] In addition, the data transmission path can be changed to transmit vehicle data and signal data separately, and then sent to the ground inspection and maintenance system after being gathered in the ground data center. Whether or not to set up a ground data center does not affect the operation of the entire system.

[0039] The ground inspection and maintenance system 130 adds a new daily train inspection system 131 and an intelligent control platform 132. The daily train inspection system refers to a system that performs technical inspections on trains every day. The newly added parts can be configured according to different application project scenarios. For example, the new daily train inspection system adds a 360° trackside car body and a wheelset pantograph intelligent inspection robot, etc., which is not limited by the present disclosure.

[0040] According to the embodiments of the present disclosure, information such as status monitoring and maintenance records of various components can be obtained through the new daily train inspection system. Figure 2 The working principle diagram of the new daily train inspection system according to the embodiment of the present disclosure is schematically shown.

[0041] like Figure 2 As shown, when the vehicle enters the throat area, it can trigger the vehicle's 360° appearance image detection, perform vehicle number recognition, speed measurement, and roof, side, and bottom image collection, identify the body appearance daily train inspection item faults, and the train inspection team can remotely view the images and faults; after the vehicle enters the warehouse, the daily train inspection operation is triggered, and the daily train inspection team issues automated inspection instructions to collect and identify images of the daily train inspection items of the running part under the vehicle, and remotely view images and faults through handheld terminal interaction; after viewing the fault image, the daily train inspection team conducts daily train inspection fault and remaining items for maintenance inspection; after the daily train inspection operation is completed, the maintenance information is fed back to the ground application service platform, and the train completes the train maintenance status record.

[0042] Among the above interactive data, data such as vehicle operation mode, traction level information, brake level information, vehicle position and vehicle speed play an important role. Taking the vehicle status record related to the overhaul as an example, when the equipment undergoes multiple overhauls, it is judged whether it occurs in the same area and / or the same speed level based on the vehicle position and / or vehicle speed, which is convenient for later equipment improvement and fault analysis. Among them, it can be used for fault coupling analysis, that is, the overhaul data and the vehicle operation data, vehicle health data, signal data and daily train inspection data corresponding to the overhaul data are transmitted to the overhaul equipment supplier for data coupling judgment and analysis at the time of the fault.

[0043] Regarding train operation and maintenance failures, the vehicle system can perform self-inspection of the vehicle system according to the fault detection logic of each system. When the fault condition threshold is met, the fault is automatically reported and located to the specific equipment component, and the fault information is fed back to the ground for operation and maintenance. The ground system can monitor the status information of each device of the train based on image recognition. When the fault condition threshold is met, the fault is automatically reported and located to the specific equipment component for operation and maintenance. For example, if the scratch on the high-voltage equipment on the train is more than 5mm, the equipment fault is reported. In addition, since the train fault diagnosis data is not necessarily accurate, the train fault diagnosis data is not caused by the train fault. It may be indirectly caused by the track fault at the location of the train. As long as it does not run on this section of track, there will be no fault. For example, the train reports a "traction converter grounding fault". After inspection, it is found that it is caused by a foreign object hitting. At this time, the line can be checked in combination with the train position guidance at the time of the fault reporting to avoid the problem from happening again without the need for overhaul.

[0044] It should be understood that Figure 1 The number of systems, subsystems, and devices in the figure is only for illustration purposes, and the number of systems, subsystems, and devices may be increased or decreased according to actual application scenario requirements.

[0045] Figure 3 A flow chart of a train operation scheduling method based on a vehicle-ground integrated system according to an embodiment of the present disclosure is schematically shown.

[0046] like Figure 3 As shown, the method 300 includes operations S310 to S340.

[0047] In operation S310, status monitoring information of each component configured on multiple candidate trains, running mileage information of each component, maintenance record information of each component, historical running environment information of multiple candidate trains and monitoring information of multiple lines to be run are obtained.

[0048] In operation S320, health status information of each candidate train is generated based on status monitoring information of each component, running mileage information of each component, maintenance record information of each component, and historical running environment information of each candidate train.

[0049] In operation S330, state information of each line to be operated is generated based on the monitoring information of each line to be operated.

[0050] In operation S340, based on the health status information of each candidate train and the status information of each line to be operated, an operation scheduling plan for each candidate train is generated to schedule each candidate train to operate on each line to be operated.

[0051] According to the embodiments of the present disclosure, the status monitoring information of each component configured on the train includes the status monitoring information of the components of each subsystem in the vehicle system, which can be the status monitoring information of the traction system, power supply system, vehicle-to-ground communication equipment and other components, so as to realize the status diagnosis of the components configured on the train. Specifically, it can be the status monitoring information of the train bogie, car body, door, brake, traction, air conditioning, broadcasting, fireworks, auxiliary system, passenger information system, vehicle-to-ground wireless communication equipment, vehicle (Train Control and Management System, train control and management system) network itself and vehicle TCMS and other system network communication equipment and other components. For example, the status monitoring information is "X train bogie has cracks", "X train charger failure", "X train traction equipment is normal", etc. The status monitoring information of each component can be obtained through vehicle self-inspection, and can also be obtained through ground system diagnosis, and the two can exchange information through vehicle-to-ground communication.

[0052] The running mileage information of each component can be extracted from the running mileage information of the train, representing the running mileage of each component, for example, the running mileage of the P traction motor is 75200 kilometers. The running mileage information of each component includes the running mileage when the train is loaded with passengers and when the train is empty.

[0053] The maintenance record information of each component includes the maintenance record information and the maintenance information of each component. Both the maintenance record and the maintenance record can be used as the basis for judging the remaining service life of the component. For example, the maintenance record information is "The bogie of train X was overhauled and replaced on October 25, 2018 due to cracks. The expected service life of the replaced bogie is 10 years."

[0054] The train operation environment information includes the road conditions, train operation mode, train traction, brake level information, etc. For example, if the train historical operation environment information is "the train passes through 10 curves and 5 steep slopes", the traction wheels and bogies may be seriously worn.

[0055] According to an embodiment of the present disclosure, the health status assessment of the train is achieved through multi-parameter fusion calculation using the status monitoring information of each component, the running mileage information, the maintenance record information and the historical operating environment information of each candidate train acquired as described above.

[0056] The health status information of each candidate train can be obtained by assigning corresponding weight coefficients to the status monitoring data, mileage data, maintenance record data, and operating environment data of different components through hierarchical analysis method and expert experience method. Finally, the data is added up to obtain the health status score of each component. The health status score of the component with the smallest score is used as the total score of the train health status to quantify the health status information of each candidate train.

[0057] For example, according to expert experience, the weights of the traction motor's condition monitoring, mileage, maintenance record, and operating environment are 0.8, 0.5, 0.6, and 0.4, respectively. The values ​​of the traction motor's condition monitoring, mileage, maintenance record, and operating environment data after processing are 90, 70, 60, and 85, respectively. Therefore, the health status score of each component can be obtained by adding the above weight coefficients to 177. The weights of the bogie's condition monitoring, mileage, maintenance record, and operating environment are 0.9, 0.6, 0.8, and 0.8, respectively. The values ​​of the bogie's condition monitoring, mileage, maintenance record, and operating environment data after processing are 79, 68, 80, and 90, respectively. Therefore, the health status score of each component can be obtained by adding the above weight coefficients to 248. At this time, the lower 177 is selected as the total health status score of the train.

[0058] The health status information of each candidate train can also be evaluated by evaluating the status monitoring data of different components, mileage data, maintenance record data, and operating environment data, with the minimum level being used as the health status level of the train to evaluate the health status of the train.

[0059] For example: after evaluating the status monitoring data, mileage data, maintenance record data, and operating environment data of the traction motor and bogie, the levels of the traction motor and bogie are obtained as level one and level two. Level one indicates that the component status is poor, and level two indicates that the component status is medium. The smaller level one is selected as the health status evaluation of the train.

[0060] The above evaluation results can also be presented to operation and maintenance personnel through visual charts such as bar charts, line charts, statistical tables, etc.

[0061] The monitoring information of the lines to be operated can be obtained by evaluating the ground line status through the on-board engineering detection system. Based on the monitoring information of each line to be operated, the status information of each line to be operated is generated, which can be used to characterize whether the train line to be operated can operate normally. Among them, the monitoring information of the lines to be operated includes road condition information of the lines to be operated, power usage of the lines to be operated and other information.

[0062] According to the embodiment of the present disclosure, the operation scheduling plan for each candidate train is generated by matching the obtained health status information of each candidate train with the status information of the line to be operated one by one. The health status information of the train and the status information of the line to be operated can be matched according to the generated matching list of the health status of the corresponding train and the status of the operating line, or through a mapping relationship table between the two, or through matching rules formulated by expert experience.

[0063] For example, in the matching list, when the train health status is level a, it can be matched with the running line status of levels a, b, and c. If the health status information of train X is "train health status is good, level a", and the status information of running line Y is "train line status level b", then the health status information of train X can be matched with the status information of running line Y, and train X can be scheduled to run according to running line Y.

[0064] According to the embodiments of the present disclosure, through the vehicle-ground integrated system, the status monitoring information of each component configured on the train, the running mileage information of each component, the maintenance record information of each component, the historical operating environment information of multiple candidate trains and the monitoring information of multiple lines to be operated can be obtained in time. Based on the above information, the health status information of each candidate train and the status information of each line to be operated are generated accordingly. Through the generated health status information and the status information of the lines to be operated, a reasonable train operation scheduling plan is finally generated efficiently to schedule each candidate train to run on each line to be operated. The above-mentioned operation scheduling plan generation process utilizes the data interaction between the vehicle and the ground daily train inspection system, and more reasonably and efficiently evaluates the health status of the train and the status of the train's operating line, effectively shortening the time for formulating the operation scheduling plan and improving the efficiency of train operation scheduling.

[0065] According to an embodiment of the present disclosure, based on the status monitoring information of each component, the running mileage information of each component, the maintenance record information of each component and the historical operating environment information of each candidate train, the health status information of each candidate train is generated, including: extracting the historical operating environment information of each component from the historical operating environment information of each candidate train; generating the remaining life information of each component based on the running mileage information of each component, the historical operating environment information of each component and the maintenance record information of each component; and generating the health status information of each candidate train based on the remaining life information of each component of the same candidate train and the status monitoring information of each component.

[0066] Figure 4 The figure schematically shows a process of generating health status information according to an embodiment of the present disclosure.

[0067] like Figure 4 As shown, based on the historical operating environment information 421 of the train, the historical operating environment information 422 of the component can be extracted, and the historical operating environment information 422 of the component includes the frequency and duration of the traction braking of the component, the degree of strong impact or wear of the component, the moisture condition of the component, etc. The historical operating environment information of the component and the running mileage information of the component can both reflect the service life of the component to a certain extent. The number of times the component has been repaired and the maintenance conditions also have an impact on the evaluation of the remaining service life of the component. Therefore, the remaining life information 425 of the component can be determined based on the historical operating environment information 422 of the component, the running mileage information 423 of the component, and the maintenance record information 424 of the component.

[0068] For example, the corresponding life conversion coefficient can be determined based on the historical operating environment information of the component, the operating mileage information of the component, and the maintenance record information of the component, and then the loss life value is generated. The factory expected service life is used as the initial value, and the loss life value obtained above is subtracted to finally obtain the remaining life value of the component.

[0069] The component status monitoring information 426 can be converted into numerical values ​​through data standardization processing, and the component status monitoring information can be quantified to obtain the component status monitoring value.

[0070] According to the remaining life information 425 of the component and the status monitoring information 426 of the component, the health status information 427 of the train can be obtained. Specifically, the health status value of each component can be calculated according to the product of the remaining life value of the component and the status monitoring value of the component, and the minimum value of the health status of each component of the train is used as the health status value of the train.

[0071] According to the embodiments of the present disclosure, the historical operating environment information of the components is extracted from the historical operating environment information of the train, and the remaining life information of each component is obtained based on the running mileage information, historical operating environment information and maintenance record information of the components, and the health status information of the train is generated based on the remaining life information and status monitoring information. The health status of the train is evaluated by the remaining life of the components, which enables a more comprehensive and accurate evaluation and diagnosis of the train through the use of the components, prevents the occurrence of unexpected failures of the components, generates corresponding train operation scheduling strategies, and improves the safety of vehicle operation scheduling.

[0072] According to an embodiment of the present disclosure, based on the running mileage information of each component, the historical running environment information of each component and the maintenance record information of each component, the remaining life information of each component is generated respectively, including: inputting the running mileage information of each component, the historical running environment information of each component and the maintenance record information of each component into a trained first target model, and outputting the remaining life information of each component respectively. The first target model is obtained by training the first initial model using the historical remaining life of the sample component as a label and using the historical running mileage, historical running environment and historical maintenance record.

[0073] The historical remaining life of the sample parts is the historical remaining life of each historically scrapped part at different historical moments. The size of the historical remaining life is related to the historical operating mileage, historical operating environment and historical maintenance records.

[0074] The first target model can be obtained by training through machine learning algorithms such as neural networks, random forests, support vector machines, etc. The algorithm used can be adjusted according to the specific situation, and the present disclosure does not limit this.

[0075] Exemplarily, a neural network algorithm is used to train the first initial model by inputting the historical mileage, historical operating environment and historical maintenance records of each sample component, and taking the historical remaining life of the sample component as the output label. When the error between the output remaining life value and the true value is greater than a predetermined threshold, the model parameters are adjusted so that the model can fit the relationship between the input data and the output value as accurately as possible, until the error between the predicted remaining life value output by the model and the true label value meets the predetermined threshold, and the model parameter adjustment is terminated. After training and verification with a large number of historical data of sample components, the first target model is obtained.

[0076] In addition, before using data for model training and calculation, in order to improve the accuracy of model calculation, the original data can be cleaned and standardized. For example, abnormal data and duplicate data can be deleted, the data can be normalized, and the data can be converted into values ​​between [0, 1].

[0077] According to the embodiments of the present disclosure, by inputting the running mileage information, historical running environment information and maintenance record information of each component into the trained first target model, the remaining life information of each component can be accurately and quickly calculated, thereby reducing the error caused by manually setting parameters, improving the accuracy of the remaining life calculation, effectively evaluating the health status of the train, and then generating the corresponding train operation scheduling strategy, thereby improving the efficiency of train operation scheduling.

[0078] According to an embodiment of the present disclosure, based on the remaining life information of each component of the same candidate train and the status monitoring information of each component, the health status information of each candidate train is generated, including: inputting the remaining life information of each component based on the same candidate train and the status monitoring information of each component into a trained second target model, and outputting the health status information of each candidate train respectively; wherein the second target model is obtained by training the second initial model using the historical failure rate of each sample train as a label and utilizing the historical remaining life and historical monitoring status of the components of each sample train.

[0079] According to an embodiment of the present disclosure, the historical failure rate of a sample train is the ratio of the number of failures of each historically scrapped component at different historical moments to the total number of times used. For example, the failure rate of a traction motor from time t to the time of scrapping t n The failure rate is 1% at all times.

[0080] Similar to the first target model, the second target model can also be obtained by training with machine learning algorithms such as neural networks, random forests, support vector machines, etc. The algorithm used can be adjusted according to the specific situation, and the present disclosure does not limit this. The specific training process and data preprocessing process are similar to the first target model, and can be adjusted according to the actual situation, and will not be repeated here.

[0081] According to an embodiment of the present disclosure, a target model of train health status information is constructed, and the remaining life information of each component of the same candidate train and the status monitoring information of each component are input into a trained second target model to quickly and accurately determine the health status information of each candidate train, reduce the error of health status assessment caused by empirical error, improve the accuracy of train health status assessment, and then generate a corresponding train operation scheduling strategy to improve the efficiency of train operation scheduling.

[0082] According to an embodiment of the present disclosure, the monitoring information of the lines to be operated includes the monitoring information of the contact network, the track monitoring information and the tunnel monitoring information corresponding to the lines to be operated; based on the monitoring information of each line to be operated, the status information of each line to be operated is generated, including: inputting the monitoring information of each contact network, each track monitoring information and each tunnel monitoring information corresponding to each line to be operated into a trained third target model to generate the status information of each line to be operated; wherein the third target model is obtained by training the third initial model with the status of the sample operating line as a label, using the historical monitoring information of the contact network, the historical monitoring information of the track and the historical monitoring information of the tunnel corresponding to the sample operating line.

[0083] According to the embodiments of the present disclosure, the monitoring information of each contact network includes the network voltage and network current information of each contact network. The track monitoring information includes the wear degree of the track, the geometric state of the track, the track spacing and other information. The tunnel monitoring information includes the tunnel environment information, the tunnel length, the wind speed and airflow pressure in the tunnel and other information.

[0084] The status of the sample running line includes the status information of the historical running line under the same running route and running speed. The monitoring information of each overhead line, each track monitoring information and each tunnel monitoring information corresponding to each line to be run is input into the trained third target model to generate the status information of each line to be run.

[0085] Similar to the first target model and the second target model, the third target model can also be obtained by training with machine learning algorithms such as neural networks, random forests, support vector machines, etc. The algorithm used can be adjusted according to specific circumstances, and the present disclosure does not limit this. The specific training process and data preprocessing process are similar to the above-mentioned target models, and can be adjusted according to actual conditions, and will not be repeated here.

[0086] According to the embodiments of the present disclosure, a third target model is trained using the historical monitoring information of the contact network, the historical monitoring information of the track and the historical monitoring information of the tunnel corresponding to the sample operating line, and then the status information of the operating line is calculated and analyzed through the third target model, which can reduce errors caused by manual evaluation and judgment, improve the accuracy of the train operating line status evaluation, and then generate corresponding train operation scheduling strategies to improve the efficiency of train operation scheduling.

[0087] Figure 5 A flow chart of a train operation scheduling method based on a vehicle-ground integrated system according to an embodiment of the present disclosure is schematically shown.

[0088] like Figure 5 As shown, the method 500 includes operations S541 to S545.

[0089] In operation S541, matching is performed based on the health status information of each candidate train and the status information of each line to be operated to obtain an initial matching result.

[0090] In operation S542, the initial matching result is verified based on the remaining life information of each component in each candidate train to obtain a verification result.

[0091] In operation S543, it is determined whether the verification result is passed. If the determination result is yes, operation S544 is performed; if the determination result is no, operation S545 is performed.

[0092] In operation S544, an operation schedule is generated based on the initial matching result.

[0093] In operation S545 , the initial matching result is adjusted to generate an operation schedule.

[0094] The health status information of each candidate train and the status information of each line to be operated are sorted and matched. Specifically, the matching can be carried out through the corresponding mapping relationship between the health status information and the status information of the operating line. For example, the mapping relationship is "if the health status information is greater than 80 points, it is matched with the line in good operating condition; if the health status information is less than 75 points, the train will not be dispatched." If the generated health status information a is 85 points and the operating line status information b is good, then a and b can be matched.

[0095] The following problems may exist in the initial matching results: when the health status determined by the various states of the components just meets the threshold, but the matching running line status is below average, the components at this time cannot meet the requirements of the current running line status. For example, component x has a long service life and is severely worn, but due to the good historical operating environment, low maintenance frequency and high maintenance times of component x, the health status score is high, but the remaining life of the component is not enough to meet the running line with more curves and brakes. Therefore, it is necessary to verify the initial matching results through the remaining life information of the components to reduce the risk of the operation scheduling plan and improve the safety of train operation scheduling.

[0096] During the verification, the verification can be performed according to the verification rules. For example, the verification rule can be that when the operating line is in medium condition, the remaining service life of the component is not less than 1 year. When the verification result passes, the operation scheduling plan can be generated based on the initial matching result. When the verification result fails, the matching result needs to be adjusted to meet the verification rules. After passing the verification, the corresponding operation scheduling plan is generated based on the adjusted matching result.

[0097] According to the embodiments of the present disclosure, matching results can be quickly obtained by matching the health status information of the train with the status information of the line to be operated. In addition, the initial matching results are verified by the remaining life information of the components, and the potential safety hazards that may exist during the initial matching are comprehensively considered, thereby generating a more reasonable and safe operation scheduling plan.

[0098] Based on the above train operation scheduling method based on the vehicle-ground integrated system, the present disclosure also provides a train operation scheduling device based on the vehicle-ground integrated system. Figure 6 The device is described in detail.

[0099] Figure 6 The structural block diagram of a train operation dispatching device based on a vehicle-ground integrated system according to an embodiment of the present disclosure is schematically shown.

[0100] like Figure 6 As shown, the train operation dispatching device 600 based on the vehicle-ground integrated system of this embodiment includes an acquisition module 610 , a first generation module 620 , a second generation module 630 and a third generation module 640 .

[0101] The acquisition module 610 is used to acquire status monitoring information of each component configured on multiple candidate trains, running mileage information of each component, maintenance record information of each component, historical running environment information of multiple candidate trains, and monitoring information of multiple lines to be run. In one embodiment, the acquisition module 610 can be used to perform the operation S310 described above, which will not be repeated here.

[0102] The first generation module 620 is used to generate health status information of each candidate train based on the status monitoring information of each component, the running mileage information of each component, the maintenance record information of each component and the historical running environment information of each candidate train. In one embodiment, the first generation module 620 can be used to perform the operation S320 described above, which will not be repeated here.

[0103] The second generating module 630 is used to generate the status information of each line to be operated based on the monitoring information of each line to be operated. In one embodiment, the second generating module 630 can be used to perform the operation S330 described above, which will not be described in detail here.

[0104] The third generation module 640 is used to generate an operation scheduling plan for each candidate train based on the health status information of each candidate train and the status information of each line to be operated, so as to schedule each candidate train to operate on each line to be operated. In one embodiment, the third generation module 640 can be used to perform the operation S340 described above, which will not be repeated here.

[0105] According to an embodiment of the present disclosure, the first generation module includes an extraction submodule, a remaining life information generation submodule and a health status information generation submodule. The extraction submodule is used to extract the historical operating environment information of each component from the historical operating environment information of each candidate train. The remaining life information generation submodule is used to generate the remaining life information of each component based on the operating mileage information of each component, the historical operating environment information of each component and the maintenance record information of each component. The health status information generation submodule generates the health status information of each candidate train based on the remaining life information of each component of the same candidate train and the status monitoring information of each component.

[0106] According to an embodiment of the present disclosure, the remaining life information generation submodule includes a first target model application unit, which is used to input the operating mileage information of each component, the historical operating environment information of each component and the maintenance record information of each component into a trained first target model, and output the remaining life information of each component respectively; wherein the first target model is obtained by training the first initial model using the historical remaining life of the sample component as a label, and using the historical operating mileage, historical operating environment and historical maintenance records.

[0107] According to an embodiment of the present disclosure, the health status information generation submodule includes a second target model application unit, which is used to input the remaining life information of each component based on the same candidate train and the status monitoring information of each component into a trained second target model, and output the health status information of each candidate train respectively; wherein the second target model is obtained by training the second initial model using the historical failure rate of each sample train as a label and using the historical remaining life and historical monitoring status of the components of each sample train.

[0108] According to an embodiment of the present disclosure, the monitoring information of the lines to be operated includes the monitoring information of the contact network, the track monitoring information and the tunnel monitoring information corresponding to the lines to be operated. The second generation module includes a third target model application submodule, which is used to input the monitoring information of each contact network, each track monitoring information and each tunnel monitoring information corresponding to each line to be operated into the trained third target model to generate the status information of each line to be operated; wherein the third target model is obtained by training the third initial model using the status of the sample operating line as a label and the historical monitoring information of the contact network, the historical monitoring information of the track and the historical monitoring information of the tunnel corresponding to the sample operating line.

[0109] According to an embodiment of the present disclosure, the third generation module includes a matching submodule, a verification submodule and a response submodule. The matching submodule is used to match the health status information of each candidate train and the status information of each line to be operated to obtain an initial matching result. The verification submodule is used to verify the initial matching result based on the remaining life information of each component in each candidate train to obtain a verification result. The response submodule is used to generate an operation scheduling plan based on the initial matching result in response to the verification result being passed.

[0110] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging circuits, or can be implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0111] For example, any multiple of the acquisition module 610, the first generation module 620, the second generation module 630, and the third generation module 640 can be combined in one module / unit / sub-unit for implementation, or any one of the modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functions of one or more of these modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units and implemented in one module / unit / sub-unit. According to an embodiment of the present disclosure, at least one of the acquisition module 610, the first generation module 620, the second generation module 630, and the third generation module 640 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or by any one of the three implementation methods of software, hardware, and firmware, or by a suitable combination of any of them. Alternatively, at least one of the acquisition module 610 , the first generation module 620 , the second generation module 630 , and the third generation module 640 may be at least partially implemented as a computer program module, and when the computer program module is executed, a corresponding function may be performed.

[0112] The embodiment of the present disclosure also includes a train, which includes an acquisition module and a generation module. The acquisition module is used to acquire the operation scheduling plan obtained by the above method. The generation module is used to generate an operation instruction based on the operation scheduling plan to control the train to run according to the operation scheduling plan.

[0113] Figure 7 A block diagram of an electronic device suitable for implementing a train operation scheduling method for a vehicle-ground integrated system according to an embodiment of the present disclosure is schematically shown. Figure 7 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0114] like Figure 7As shown, the electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage part 708 to a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include an onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0115] In RAM 703, various programs and data required for the operation of electronic device 700 are stored. Processor 701, ROM 702 and RAM 703 are connected to each other via bus 704. Processor 701 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 702 and / or RAM 703. It should be noted that the program can also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in one or more memories.

[0116] According to an embodiment of the present disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to the bus 704. The system 700 may further include one or more of the following components connected to the input / output (I / O) interface 705: an input portion 706 including a keyboard, a mouse, etc.; an output portion 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 708 including a hard disk, etc.; and a communication portion 709 including a network interface card such as a LAN card, a modem, etc. The communication portion 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the input / output (I / O) interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed, so that a computer program read therefrom is installed into the storage portion 708 as needed.

[0117] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0118] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0119] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0120] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 702 and / or the RAM 703 described above and / or one or more memories other than the ROM 702 and the RAM 703 .

[0121] The embodiments of the present disclosure also include a computer program product, which includes a computer program, and the computer program contains program code for executing the method provided by the embodiments of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the method provided by the embodiments of the present disclosure.

[0122] When the computer program is executed by the processor 701, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0123] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 709, and / or installed from the removable medium 711. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0124] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0125] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments and / or claims of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0126] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A train operation dispatching method based on a vehicle-ground integrated system, comprising: Acquire status monitoring information of various components configured on multiple candidate trains, running mileage information of various components, maintenance record information of various components, historical running environment information of multiple candidate trains and monitoring information of multiple lines to be run; Generate health status information of each candidate train based on the status monitoring information of each component, the running mileage information of each component, the maintenance record information of each component and the historical running environment information of each candidate train; Based on the monitoring information of each of the lines to be operated, generating status information of each of the lines to be operated; as well as Based on the health status information of each candidate train and the status information of each line to be operated, an operation scheduling plan for each candidate train is generated to schedule each candidate train to operate on each line to be operated.

2. The method according to claim 1, wherein: The generating of health status information of each candidate train based on the status monitoring information of each component, the running mileage information of each component, the maintenance record information of each component and the historical running environment information of each candidate train comprises: Extracting historical operating environment information of each component from the historical operating environment information of each candidate train; Based on the running mileage information of each component, the historical running environment information of each component and the maintenance record information of each component, respectively generate remaining life information of each component; and Based on the remaining life information of each component of the same candidate train and the status monitoring information of each component, health status information of each candidate train is generated.

3. The method according to claim 2, wherein: The generating of the remaining life information of each component based on the running mileage information of each component, the historical running environment information of each component and the maintenance record information of each component includes: Inputting the running mileage information of each component, the historical running environment information of each component and the maintenance record information of each component into the trained first target model, and outputting the remaining life information of each component respectively; The first target model is obtained by training the first initial model using the historical remaining life of the sample component as a label and utilizing the historical operating mileage, historical operating environment and historical maintenance records.

4. The method according to claim 2, wherein: The generating the health status information of each candidate train based on the remaining life information of each component of the same candidate train and the status monitoring information of each component includes: Inputting the remaining life information of each component based on the same candidate train and the status monitoring information of each component into the trained second target model, and outputting the health status information of each candidate train respectively; The second target model is obtained by training the second initial model using the historical failure rate of each sample train as a label and utilizing the historical remaining life and historical monitoring status of the components of each sample train.

5. The method according to claim 1, wherein: The monitoring information of the line to be operated includes monitoring information of the overhead line, track monitoring information and tunnel monitoring information corresponding to the line to be operated; The generating, based on the monitoring information of each of the lines to be operated, the state information of each of the lines to be operated comprises: Inputting the monitoring information of each overhead line, each track monitoring information and each tunnel monitoring information corresponding to each of the lines to be operated into the trained third target model to generate the status information of each of the lines to be operated; Among them, the third target model is obtained by training the third initial model using the state of the sample running line as a label and using the historical monitoring information of the contact network, the historical monitoring information of the track and the historical monitoring information of the tunnel corresponding to the sample running line.

6. The method according to claim 1, wherein: The generating of an operation scheduling plan for each candidate train based on the health status information of each candidate train and the status information of each line to be operated, so as to schedule each candidate train to operate on each line to be operated, comprises: Matching is performed based on the health status information of each candidate train and the status information of each line to be operated to obtain an initial matching result; Verifying the initial matching result based on the remaining life information of each component in each of the candidate trains to obtain a verification result; and In response to the verification result being passed, the operation scheduling plan is generated based on the initial matching result.

7. A train operation dispatching device based on a vehicle-ground integrated system, comprising: An acquisition module is used to acquire status monitoring information of various components configured on multiple candidate trains, running mileage information of various components, maintenance record information of various components, historical running environment information of multiple candidate trains and monitoring information of multiple lines to be operated; A first generating module, configured to generate health status information of each candidate train based on the status monitoring information of each component, the running mileage information of each component, the maintenance record information of each component and the historical running environment information of each candidate train; A second generating module, configured to generate status information of each of the lines to be operated based on the monitoring information of each of the lines to be operated; as well as The third generating module is used to generate an operation scheduling plan for each candidate train based on the health status information of each candidate train and the status information of each line to be operated, so as to schedule each candidate train to operate on each line to be operated.

8. A train comprising: An acquisition module, used to acquire the operation scheduling plan according to any one of claims 1 to 6; A generating module is used to generate an operation instruction based on the operation scheduling plan to control the train to run according to the operation scheduling plan.

9. An electronic device, comprising: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

10. A computer program product, wherein: The computer program product comprises computer executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed.

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