CN114715234B - Digital twin system, device and method for train operation control system - Google Patents
Digital twin system, device and method for train operation control system Download PDFInfo
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Abstract
The invention provides a digital twin system, a device and a method of a train operation control system. The digital twin system of the train operation control system includes: the data layer is used for collecting various types of operation data of the train operation control system; the model layer is used for receiving various types of operation data; model simulation is carried out based on each operation data, and prediction data corresponding to each operation data is obtained; the application layer is used for receiving the predicted data corresponding to each piece of operation data; at least one operation of fault analysis, life prediction and health evaluation is performed based on the prediction data corresponding to each operation data, so as to obtain feedback data; and the interaction layer is used for receiving and displaying the feedback data. The invention is used for solving the defects that the information is not fed back to the train operation control system and the train operation control system cannot be comprehensively simulated, diagnosed and predicted in the prior art.
Description
Technical Field
The invention relates to the technical field of railways, in particular to a digital twin system, a device and a method of a train operation control system.
Background
The digital twin is constructed in a virtual space, can represent the virtual digital expression of physical entity characteristics, forming process and behaviors, and has the characteristics of multiple physical properties, multiple scales, probability and the like. The method mainly aims at a digital model of an existing or to-be-existing physical entity object, perceives, diagnoses and predicts the state of the physical entity object in real time through actual measurement, simulation and data analysis, regulates and controls the behavior of the physical entity object through optimization and instructions, evolves itself through mutual learning among related digital models, and improves decisions of stakeholders in the life cycle of the physical entity object.
The technology is applied to a certain degree in the manufacturing fields of aviation, automobiles and the like. The technology plays a good auxiliary role in real-time diagnosis and life prediction of physical equipment. But there is no engineering application example in the field of train operation control systems for the railway industry.
Train operation control systems currently in use in the industry typically deploy separate signal maintenance subsystems. The main purpose of the system is to monitor the key state of the system and receive the running state information sent by the train running control system. After certain data are accumulated, the signal maintenance system combines massive historical data and real-time data, and can diagnose or predict faults of specific categories in real time. The system does not substantially feed back information to the train operation control system.
The existing train operation control system is more and more complex, the equipment technology content is higher and higher, and the traditional signal maintenance subsystem is difficult to meet the maintenance requirement of a user on the system.
The main defects of the signal maintenance subsystem of the current train operation control system are as follows:
1) The signal maintenance subsystem basically receives information of the train operation control system in one way, and feeds back information to the train operation control system rarely. Therefore, the function of the system can only be to assist in maintaining the train operation control system, and the system does not basically feed back information to the train operation control system.
2) The fault diagnosis and fault prediction functions of the signal maintenance subsystem are only sporadic for specific types of faults. The signal maintenance subsystem cannot more fully simulate, diagnose and predict the train operation control system.
Disclosure of Invention
The invention provides a digital twin system, a device and a method of a train operation control system, which are used for solving the defects that the information feedback to the train operation control system is avoided and the train operation control system cannot be comprehensively simulated, diagnosed and predicted in the prior art.
The invention provides a digital twin system of a train operation control system, which comprises:
the data layer is used for collecting various types of operation data of the train operation control system;
the model layer is used for receiving the operation data of the multiple types; performing model simulation based on each piece of operation data to obtain prediction data corresponding to each piece of operation data;
the application layer is used for receiving the prediction data corresponding to each operation data; and performing at least one operation of fault analysis, life prediction and health evaluation based on the prediction data corresponding to each operation data to obtain feedback data;
And the interaction layer is used for receiving and displaying the feedback data.
According to the digital twin system of the train operation control system provided by the invention, the model layer is further used for sending decision information to the data layer, and the data layer is further used for sending the received decision information to the train operation control system or the interaction layer; wherein the decision information is obtained by the model layer performing model simulation based on the operation data.
According to the digital twin system of the train operation control system provided by the invention, the interaction layer is also used for sending the operation information of the user to the application layer; the application layer is further configured to send modeling management information or simulation operation information to the model layer based on the received operation information.
According to the digital twin system of the train operation control system provided by the invention, the plurality of types of operation data comprise at least two of train automatic protection data, train automatic monitoring data, interlocking data, zone control data, passenger flow data, axle counting data, track circuit data, transponder data and switch machine data.
According to the digital twin system of the train operation control system provided by the invention, the model layer comprises at least two of a train automatic protection model for simulating the train automatic protection data, a train automatic monitoring model for simulating the train automatic monitoring data, an interlocking model for simulating the interlocking data, a zone control model for simulating the zone control data, a passenger flow model for simulating the passenger flow data, an axle counting model for simulating the axle counting data, a track circuit model for simulating the track circuit data, a transponder model for simulating the transponder data and a switcher model for simulating the switcher data.
According to the digital twin system of the train operation control system provided by the invention, the data layer further comprises a data processing module for performing data cleaning and/or data conversion on the multiple types of operation data.
According to the digital twin system of the train operation control system provided by the invention, the data layer further comprises a data storage module for storing the operation data of the multiple types.
The invention also provides a digital twin device of the train operation control system, which comprises:
The data module is used for collecting various types of operation data of the train operation control system;
the model module is used for receiving the operation data of the multiple types; performing model simulation based on each piece of operation data to obtain prediction data corresponding to each piece of operation data;
the application module is used for receiving the prediction data corresponding to each operation data; and performing at least one operation of fault analysis, life prediction and health evaluation based on the prediction data corresponding to each operation data to obtain feedback data;
And the interaction module is used for receiving and displaying the feedback data.
The invention also provides a digital twin method of the train operation control system, which is applied to the digital twin system of the train operation control system and comprises the following steps:
acquiring various types of operation data of a train operation control system through a data layer;
Receiving the plurality of types of operation data through a model layer; performing model simulation based on each piece of operation data to obtain prediction data corresponding to each piece of operation data;
Receiving prediction data corresponding to each operation data through an application layer; and performing at least one operation of fault analysis, life prediction and health evaluation based on the prediction data corresponding to each operation data to obtain feedback data;
and receiving and displaying the feedback data through an interaction layer.
The digital twin method of the train operation control system provided by the invention further comprises the following steps:
Sending decision information to the data layer through the model layer, and sending the received decision information to a train operation control system or an interaction layer through the data layer; wherein the decision information is obtained by the model layer performing model simulation based on the operation data.
According to the digital twin system, the device and the method of the train operation control system, provided by the invention, the operation data of the physical entity of the train operation control system is received, the prediction data corresponding to the simulation based on the operation data line model is subjected to at least one operation of fault analysis, life prediction and health evaluation to obtain feedback data, and the feedback data is subjected to feedback display through an interaction layer, so that the feedback information of the train operation control system is realized; the invention also carries out at least one operation of fault analysis, life prediction and health evaluation on the collected multiple types of operation data of the train operation control system, and does not singly process specific data, thereby more comprehensively simulating, diagnosing and predicting the train operation control system and improving the reliability, maintainability and safety of the train operation control system.
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In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is one of the schematic structural diagrams of a digital twinning system of the train operation control system provided by the present invention;
FIG. 2 is a second schematic diagram of the digital twinning system of the train operation control system provided by the present invention;
FIG. 3 is one of the flow diagrams of the digital twinning method of the train operation control system provided by the present invention;
FIG. 4 is a second flow diagram of the digital twinning system of the train operation control system provided by the present invention;
Fig. 5 is a schematic structural diagram of a digital twin device of the train operation control system provided by the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The main defects of the signal maintenance subsystem of the current train operation control system are as follows:
1) The signal maintenance subsystem basically receives information of the train operation control system in one way, and feeds back information to the train operation control system rarely. Therefore, the function of the system can only be to assist in maintaining the train operation control system, and the system does not basically feed back information to the train operation control system.
2) The fault diagnosis and fault prediction functions of the signal maintenance subsystem are only sporadic for specific types of faults. The signal maintenance subsystem cannot more fully simulate, diagnose and predict the train operation control system.
In view of this, the invention provides a digital twin system, device and method of a train operation control system, which aims to solve the defects that the prior art does not feed back information to the train operation control system and can not simulate, diagnose and predict the train operation control system more comprehensively.
The digital twin system of the train operation control system of the present invention is described below with reference to fig. 1-2.
Referring to fig. 1, a digital twin system of a train operation control system includes: a data layer, a model layer, an application layer, and an interaction layer. The invention establishes a system architecture and a data flow with definite layers of a digital twin system of a train operation control system, wherein the digital twin system of the train operation control system comprises a man-machine layer, an application layer, a model layer and a data layer.
The data layer is used for collecting various types of operation data of the train operation control system. Wherein the train operation control system includes various types of real-time operation data.
For example, in some embodiments, the plurality of types of operational data of the train operation control system include at least two of train automatic protection data, train automatic monitoring data, interlock data, zone control data, passenger flow data, axle counting data, track circuit data, transponder data, switch machine data.
The automatic train protection data comprise an electronic map, area control information, interlocking information, train speed information, various speed curves of an actual automatic train protection subsystem and an automatic train driving subsystem, system parameters, command parameters, fault information and the like. The train automatic protection data are collected and analyzed, so that the behavior of the train automatic protection and automatic driving subsystem can be simulated and predicted. The interlocking refers to the mutual restriction relation established among the annunciator, the turnout and the approach through technical means in order to ensure the safety of driving and shunting operation of the railway station.
The automatic train monitoring data comprises train operation diagram information, interlocking information, area control information, train operation information, train control authority information and the like. The train automatic monitoring data are collected and analyzed, so that the behavior of the train automatic monitoring subsystem can be simulated and predicted.
The interlocking data comprises an interlocking control command, a current actual interlocking equipment state, train parameter information, area control information, external relay information, each IO module state and the like. The train interlocking subsystem behavior can be simulated and predicted by collecting and analyzing the interlocking data. The interlocking device is used for controlling turnout, approach and signal of the station and realizing the interlocking relationship between the turnout, the approach and the signal.
The regional control data comprises interlocking information, a temporary speed limit control command, train information, an external relay, states of each IO module and the like. The regional control data are collected and analyzed, so that the behavior of the column regional control subsystem can be simulated and predicted.
The passenger flow data comprise historical passenger flow statistical curves of stations, real-time passenger flow information of stations, emergency information of stations and the like. The passenger flow data are collected and analyzed, so that the passenger flow change curve of each station along with time can be simulated and predicted.
The axle counting data includes current train position information, train parameter information, and the like. The axle counting data are collected and analyzed, so that the axle counting system is beneficial to simulating and predicting the overall action of an axle counting. The axle is also called microcomputer axle, and is an installation device on the stations at two ends of railway. In other words, a railway signaling device capable of detecting passing through a wheel is provided which can replace many common rail circuits.
The track circuit data includes current train position information and train parameter information. The track circuit data are collected and analyzed, so that the track circuit behavior of a future period of time can be simulated and predicted. The track circuit is composed of a rail line and a rail insulation circuit, and is used for automatically and continuously detecting whether the rail line is occupied by rolling stock or not, and is also used for controlling a signal device or a switching device so as to ensure driving safety.
The transponder data includes current train position information, train parameter information, interlock information, etc. The method is beneficial to simulating and predicting the overall behavior of the transponder by collecting and analyzing the transponder data. A transponder (Balise) refers to a point device for terrestrial nematic information transmission, the main purpose being to provide reliable terrestrial fixed and variable information to a nematic vehicle device.
The switch machine data comprises information such as current interlocking control commands, real-time voltage and current of the switch machine, video of the inside of the switch machine and the like. The data of the switch machine are collected and analyzed, so that the overall behavior of the switch machine can be simulated and predicted.
By collecting various types of operation data of the train operation control system. The method is beneficial to data processing and treatment based on various types of operation data, so that the train operation control system is comprehensively simulated, diagnosed and predicted.
The model layer is used for receiving the operation data of the multiple types; and performing model simulation based on each piece of operation data to obtain prediction data corresponding to each piece of operation data. Specifically, the model layer has a plurality of models corresponding to the operation data for executing simulation based on the operation data-driven models of the plurality of types. The model layer also comprises a modeling management module for modeling management and a model simulation module for model simulation. And the model interface module is used for interacting with other layers.
In some embodiments, the model layer includes at least two of a train automatic monitoring model simulating the train automatic protection data, an interlock model simulating the interlock data, a zone control model simulating the zone control data, a passenger flow model simulating the passenger flow data, a meter axis model simulating the meter axis data, a track circuit model simulating the track circuit data, a transponder model simulating the transponder data, and a switch machine model simulating the switch machine data.
Specifically, the input of the automatic train protection model is an electronic map, area control information, interlocking information, speed information, various speed curves, system parameters, command parameters and fault information of an actual automatic train protection and automatic train driving subsystem; the output is: the actions of the train autoguard, the train autopilot subsystem for a period of time in the future (e.g., tens of seconds or minutes) include speed profiles, train control parameters, command parameters sent by the train to the ground, etc. That is, the train autoguard model may simulate and predict the behavior of the train autoguard, and the train autopilot subsystem.
The input of the automatic train monitoring model is train operation diagram information, interlocking information, zone control information (namely, short for regional control information), train operation information, control authority information and the like; the output is: the behavior of the train automatic monitoring subsystem in a future period of time (e.g., tens of seconds or minutes) includes an approach automatic triggering function, a train control command function, train identification number tracking, a train operation diagram adjustment command, etc. I.e., the train automatic monitoring model may simulate and predict the behavior of the train automatic monitoring subsystem.
The input of the interlocking model is an interlocking control command, a current actual interlocking equipment state, train information, zone control information, external relay information, each IO module state and the like; the output is: behavior of the interlock subsystem over a period of time (e.g., tens of seconds or minutes) in the future, including interlock control commands, interlock feedback status to zone control, interlock train feedback status, etc. I.e., the interlock model may simulate and predict the behavior of the interlock subsystem.
The regional control model is input with interlocking information, a temporary speed limit control command, train information, external relay information, the states of each IO module and the like; the output is: the behavior of the zone control subsystem in a period of time (such as tens of seconds or minutes) in the future comprises train movement authorization, feedback state of zone control to the interlocking equipment, feedback state of zone control train automatic monitoring system and the like. I.e., the zone control model may simulate the behavior of the zone control subsystem.
The input of the passenger flow model is a historical passenger flow statistical curve of each station, real-time passenger flow information of each station and emergency information of each station; outputting a time-dependent passenger flow curve of each station for a period of time in the future. The passenger flow model can simulate and forecast the change curve of passenger flow of each station along with time.
The input of the axle counting model is current train position information and train parameter information; the output is a behavior of the meter axle for a period of time in the future, such as occupying equipment, going out of clear equipment, etc. I.e. the axle counting model can simulate and predict the overall behaviour of the axle counting.
The input of the track circuit model is current train position information and train parameter information; the output is a behavior of the track circuit for a period of time in the future, such as an occupied device, a clearing device, etc. I.e. the track circuit model may simulate and predict the overall behavior of the track circuit.
The input of the transponder model is current train position information, train parameter information and interlocking information; the output is a behavior of the transponder for a period of time in the future, such as a train feedback status, a communication connection status with the train, etc. I.e. the transponder model may simulate and predict the overall behaviour of the transponder.
The input of the switch machine model is information such as a current interlocking control command, real-time voltage, current, video and the like; the output is the behavior of the switch machine, such as voltage, current, travel distance, etc., for a period of time in the future. I.e. the transponder model can simulate and predict the overall behavior of the switch machine. I.e. the switch machine model can simulate and predict the overall behavior of the switch machine.
In other embodiments, when the data layer further includes network topology data, the model layer further includes a network topology model that simulates the network topology data. Specifically, the input of the network topology model is real-time monitoring information of each node of the current network topology and monitoring statistical information of each node of the historical contemporaneous network topology; the output is the behavior of the network topology for a period of time in the future, such as the network packet loss rate, the network congestion degree and the network on-off range. The overall behavior of the network topology can be simulated and predicted by the network topology model.
In other embodiments, when the data layer further includes relay data, the model layer further includes a relay model that simulates the relay data. The input of the relay model is information such as the current relay position, driving voltage and current; the output is the behavior of the switch machine for a period of time in the future, such as relay position, fault condition, etc. The overall behavior of the switch machine can be simulated and predicted through the relay model.
The application layer is used for receiving the predicted data corresponding to each operation data; and performing at least one operation of fault analysis, life prediction and health evaluation based on the predicted data corresponding to each operation data to obtain feedback data, wherein in some embodiments, the application layer comprises a fault early warning module for performing fault analysis, a health evaluation module for performing health evaluation, a life prediction module for performing life prediction and a maintenance suggestion module for giving maintenance suggestions based on the operation data. The application layer pushes out various decision and control suggestions (i.e. predictive data) from the model layer, which are further translated and converted into commands and information recognizable by the real train operation control system and machine.
The interaction layer is used for receiving and displaying the feedback data. Specifically, the interaction layer comprises a human-computer interface for displaying information and an access interface module for interacting information with other layers. The interaction layer receives feedback data sent by the application layer and displays the feedback data through passenger flow data of a human-computer interface (such as a touch display screen), so that a technician knows fault early warning information, health evaluation information and service life prediction information of the train operation control system according to the feedback data. Thereby the position of the problem in the train operation control system is maintained, repaired or adjusted in a targeted way.
The following is a specific example. The fault early warning and behavior prediction of the switch machine are taken as examples for explanation.
The data layer of the digital twin system of the train operation control system collects action current, voltage and internal video information when the switch machine rotates in the opposite direction during positioning and reverse rotation. The data layer cleans, converts and stores the voltage, current and internal video information to form time sequence data with standard format, clear meaning and convenient inquiry, and then pushes the time sequence data to the model layer.
After the switch machine model of the model layer inquires and acquires the switch machine voltage, current and internal video information in the last period of time, the switch machine model is evaluated through a model algorithm to obtain a conclusion: the voltage and current curves in the last period are abnormal, and the probability is that the lead screw of the switch machine is seriously worn, and the lead screw is in the degree of needing to be replaced as soon as possible. The switch machine model of the model layer then pushes the message to the application layer that the lead screw of the switch machine needs to be replaced.
After the application layer receives the message, by calling the switch machine spare part database, the conclusion is drawn that the lead screw spare part of the switch machine is consumed, and the user needs to be prompted to purchase and replace the part as soon as possible. The application layer then pushes the lead screw message to the digital twinning machine layer that the switch machine needs to be replaced.
The man-machine layer receives a message prompt: the user needs to purchase and replace the lead screw of a certain switch machine as soon as possible, the information of the lead screw of the certain switch machine as soon as possible is displayed through a human-computer interface, and the user carries out purchasing and replacing work after seeing the information.
The above process is a typical digital twin application process.
The method comprises the steps of receiving operation data of physical entities of a train operation control system, simulating corresponding prediction data based on an operation data line model, performing at least one operation of fault analysis, life prediction and health evaluation to obtain feedback data, and performing feedback display on the feedback data through an interaction layer to realize feedback information of the train operation control system; the invention also carries out at least one operation of fault analysis, life prediction and health evaluation on the collected multiple types of operation data of the train operation control system, and does not singly process specific data, thereby more comprehensively simulating, diagnosing and predicting the train operation control system and improving the reliability, maintainability and safety of the train operation control system.
Referring to fig. 2, the digital twin system of the present invention will be described by taking an interlocking subsystem in a train operation control system as an example. When the train operation control system is an interlocking subsystem, the interaction layer is used for displaying the state interface of the interlocking equipment, the topology interface of the interlocking equipment and feedback data sent to the interaction layer by the application layer. The application layer comprises an interlocking interface health assessment module, an interlocking host fault early warning module, an electronic relay health degree module and an interlocking host maintenance module. The model layer comprises an electronic relay model, an interlocking host model, an interlocking interface model and an interlocking control display model.
The information flow between the various layers of the digital twin system of the interlock subsystem is described below:
Model layer-data layer: the data layer pushes the interlocking subsystem and the real operation data required by the model calculation to the model layer, and the model layer drives the model to execute simulation activities based on the real operation data.
Application layer-model layer: the model layer generates the prediction data of the virtual system necessary for the application layer to develop each application analysis through the simulation operation of various models in the interlocking subsystem; the application layer pushes modeling management information, simulation operation information and the like to the model layer according to user operation information from the man-machine layer; and the application layer performs fault early warning and health evaluation based on the prediction data to obtain feedback data.
Man-machine layer-application layer: the application layer pushes the state information of the interlocking equipment, the topology information of the interlocking equipment and the feedback data required by the human-computer interface display to the human-computer layer.
In other embodiments, the model layer is further configured to send decision information to the data layer, and the data layer is further configured to send the received decision information to a train operation control system or the interaction layer; wherein the decision information is obtained by the model layer performing model simulation based on the operation data.
The decision information obtained through the model layer is directly sent to the train operation control system, or is displayed through a human-computer interface of the interaction layer, so that interaction and feedback between a digital twin system of the train operation control system and a physical entity of the train operation control system are more directly realized, and overall perception, diagnosis, fault early warning and behavior prediction of the train operation control system are realized. Thereby improving the usability, reliability, maintainability and safety of the train operation control system.
For example, the automatic train monitoring model in the model layer considers that a train may be blocked in a certain section through calculation. A command is then sent to the data layer to let the train get stuck in the platform in advance. The data layer then sends this command to the physical entity's interlock subsystem or interaction layer. The interlocking subsystem buckles the train at the platform in advance; or the interaction layer displays a command for enabling the train to be buckled at the platform in advance through a human-computer interface, so that a technician is informed to conduct the operation of buckling the train at the platform in advance.
In other embodiments, the interaction layer is further configured to send operation information of a user to the application layer; the application layer is further configured to send modeling management information or simulation operation information to the model layer based on the received operation information. Specifically, the interaction layer can also receive operation information of a user through a human-computer interaction interface (such as a touch display screen). The operation information includes modeling management instructions or simulation operation instructions for the model layer. The application layer receives the operation information of the user, and pushes modeling management information or simulation operation information to the model layer, so that modeling management or model simulation, such as simulation of a switch machine model, is performed.
In other embodiments, the data layer further comprises a data processing module for data cleansing and/or data conversion of the plurality of types of operational data.
Specifically, data cleansing may cleanse some missing data, erroneous data, and duplicate data. For example, the data missing a specific value in the switch machine data is refilled, for example, when the switch machine voltage data is empty, the switch machine voltage data is refilled; error data in the switch machine data is corrected, and for example, when the date data of the switch machine is displayed in error, 00/0000 is displayed. At this time, the date data of the switch machine is corrected and replaced by the correct date; and filtering repeated data in the switch machine data, for example, when the current data of the switch machine is 0.1A0.1A repeated, filtering redundant 0.1A to obtain the current data of the switch machine as 0.1A.
Data conversion refers to merging, cleaning and integrating data. Through conversion, consistency of different source data in terms of semantics can be achieved. For example, the conversion of small data points into integer data facilitates the calculation of the model.
Through data cleaning and/or data conversion operation of the data processing module, the efficiency of model simulation of the model layer is improved, and the accuracy of model simulation results of the model layer is improved.
The data layer also includes a data storage module for storing the plurality of types of operational data. Therefore, the train operation control system collected by the data layer can store various types of operation data in the data storage module, and the various types of operation data collected by the data layer are prevented from being lost.
The digital twin method of the train operation control system of the present invention is described below with reference to fig. 3 and 4. Referring to fig. 3, the digital twin method of the train operation control system is applied to the digital twin system of the train operation control system, and the method includes:
And 100, collecting various types of operation data of the train operation control system through a data layer.
Wherein, the various types of operation data can refer to corresponding descriptions in the digital twin system of the train operation control system.
Step 200, receiving the operation data of the multiple types through a model layer; and performing model simulation based on each piece of operation data to obtain prediction data corresponding to each piece of operation data.
Wherein the plurality of models of the model layer may be referenced to corresponding descriptions in the digital twin system of the train operation control system described above.
Step 300, receiving prediction data corresponding to each operation data through an application layer; and performing at least one operation of fault analysis, life prediction and health evaluation based on the prediction data corresponding to each operation data to obtain feedback data.
Step 400, receiving and displaying the feedback data through an interaction layer.
The method comprises the steps of receiving operation data of physical entities of a train operation control system, simulating corresponding prediction data based on an operation data line model, performing at least one operation of fault analysis, life prediction and health evaluation to obtain feedback data, and performing feedback display on the feedback data through an interaction layer to realize feedback information of the train operation control system; the invention also carries out at least one operation of fault analysis, life prediction and health evaluation on the collected multiple types of operation data of the train operation control system, and does not singly process specific data, thereby more comprehensively simulating, diagnosing and predicting the train operation control system and improving the reliability, maintainability and safety of the train operation control system.
In other embodiments, referring to fig. 4, the digital twin method of the train operation control system further includes:
Step 500, sending decision information to the data layer through the model layer;
Step 600, the received decision information is sent to a train operation control system or an interaction layer through the data layer; wherein the decision information is obtained by the model layer performing model simulation based on the operation data.
The decision information obtained through the model layer is directly sent to the train operation control system, or is displayed through a human-computer interface of the interaction layer, so that the digital twin of the train operation control system and the interaction and feedback between physical entities of the train operation control system are more directly realized, and the overall perception, diagnosis, fault early warning and behavior prediction of the train operation control system are realized. Thereby improving the usability, reliability, maintainability and safety of the train operation control system.
The digital twin device of the train operation control system provided by the invention is described below, and the digital twin device of the train operation control system described below and the digital twin method of the train operation control system described above can be correspondingly referred to each other.
Referring to fig. 5, the present invention further provides a digital twin device of a train operation control system, including:
A data module 201, configured to collect multiple types of operation data of the train operation control system;
A model module 202 for receiving the plurality of types of operation data; performing model simulation based on each piece of operation data to obtain prediction data corresponding to each piece of operation data;
an application module 203, configured to receive prediction data corresponding to each of the operation data; and performing at least one operation of fault analysis, life prediction and health evaluation based on the prediction data corresponding to each operation data to obtain feedback data;
And the interaction module 204 is used for receiving and displaying the feedback data.
The digital twin device of the train operation control system receives the operation data of the physical entity of the train operation control system, carries out at least one operation of fault analysis, life prediction and health evaluation on the prediction data corresponding to the operation data line model simulation to obtain feedback data, and carries out feedback display on the feedback data through an interaction layer to realize feedback information of the train operation control system; the invention also carries out at least one operation of fault analysis, life prediction and health evaluation on the collected multiple types of operation data of the train operation control system, and does not singly process specific data, thereby more comprehensively simulating, diagnosing and predicting the train operation control system and improving the reliability, maintainability and safety of the train operation control system.
On the basis of the above embodiments, as an optional embodiment, the model module is further configured to send decision information to the data module, where the data module is further configured to send the received decision information to a train operation control system or the interaction module; wherein the decision information is obtained by the model module performing model simulation based on the operational data.
On the basis of the above embodiments, as an optional embodiment, the interaction module is further configured to send operation information of a user to the application module; the application module is further used for sending modeling management information or simulation operation information to the model module based on the received operation information.
On the basis of the above embodiments, as an alternative embodiment, the multiple types of operation data include at least two of train automatic protection data, train automatic monitoring data, interlocking data, zone control data, passenger flow data, axle counting data, track circuit data, transponder data, and switch machine data.
On the basis of the above embodiments, as an optional embodiment, the model layer includes at least two of a train automatic protection model simulating the train automatic protection data, a train automatic monitoring model simulating the train automatic monitoring data, an interlocking model simulating the interlocking data, a zone control model simulating the zone control data, a passenger flow model simulating the passenger flow data, an axle counting model simulating the axle counting data, a track circuit model simulating the track circuit data, a transponder model simulating the transponder data, and a switch machine model simulating the switch machine data.
On the basis of the above embodiments, as an optional embodiment, the data module further includes a data processing module for performing data cleaning and/or data conversion on the multiple types of operation data.
On the basis of the above embodiments, as an optional embodiment, the data module further includes a data storage module for storing the multiple types of operation data.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A digital twin system for a train operation control system, comprising:
The data layer is used for collecting various types of operation data of the train operation control system, wherein the operation data comprise train automatic protection data, train automatic monitoring data, interlocking data, zone control data, passenger flow data, axle counting data, track circuit data, transponder data and switch machine data;
the model layer is used for receiving the operation data of the multiple types; performing model simulation based on each piece of operation data to obtain prediction data corresponding to each piece of operation data; the model layer comprises a train automatic protection model for simulating the train automatic protection data, a train automatic monitoring model for simulating the train automatic monitoring data, an interlocking model for simulating the interlocking data, a zone control model for simulating the zone control data, a passenger flow model for simulating the passenger flow data, an axle counting model for simulating the axle counting data, a track circuit model for simulating the track circuit data, a transponder model for simulating the transponder data and a switcher model for simulating the switcher data;
the application layer is used for receiving the prediction data corresponding to each operation data; and performing at least one operation of fault analysis, life prediction and health evaluation based on the prediction data corresponding to each operation data to obtain feedback data;
And the interaction layer is used for receiving and displaying the feedback data.
2. The digital twin system of a train operation control system according to claim 1, wherein the model layer is further configured to send decision information to the data layer, and the data layer is further configured to send the received decision information to a train operation control system or the interaction layer; wherein the decision information is obtained by the model layer performing model simulation based on the operation data.
3. The digital twin system of a train operation control system according to claim 1, wherein the interaction layer is further configured to send operation information of a user to the application layer; the application layer is further configured to send modeling management information or simulation operation information to the model layer based on the received operation information.
4. The digital twin system of a train operation control system according to claim 1, wherein the plurality of types of operation data includes at least two of train automatic protection data, train automatic monitoring data, interlock data, zone control data, passenger flow data, axle counting data, track circuit data, transponder data, switch machine data.
5. The digital twin system of a train operation control system according to claim 4, wherein the model layer comprises at least two of a train automatic protection model simulating the train automatic protection data, a train automatic monitoring model simulating the train automatic monitoring data, an interlock model simulating the interlock data, a zone control model simulating the zone control data, a passenger flow model simulating the passenger flow data, an axle counting model simulating the axle counting data, a track circuit model simulating the track circuit data, a transponder model simulating the transponder data, and a switch machine model simulating the switch machine data.
6. The digital twinning system of a train operation control system of claim 1, wherein the data layer further comprises a data processing module for data cleansing and/or data conversion of the plurality of types of operational data.
7. The digital twinning system of a train operation control system of claim 1, wherein the data tier further comprises a data storage module for storing the plurality of types of operation data.
8. A digital twin device of a train operation control system, comprising:
The data module is used for collecting various types of operation data of the train operation control system, wherein the operation data comprise train automatic protection data, train automatic monitoring data, interlocking data, zone control data, passenger flow data, axle counting data, track circuit data, transponder data and switch machine data;
The model module is used for receiving the operation data of the multiple types; performing model simulation based on each piece of operation data to obtain prediction data corresponding to each piece of operation data; the model module comprises a train automatic protection model for simulating the train automatic protection data, a train automatic monitoring model for simulating the train automatic monitoring data, an interlocking model for simulating the interlocking data, a zone control model for simulating the zone control data, a passenger flow model for simulating the passenger flow data, an axle counting model for simulating the axle counting data, a track circuit model for simulating the track circuit data, a transponder model for simulating the transponder data and a switcher model for simulating the switcher data;
the application module is used for receiving the prediction data corresponding to each operation data; and performing at least one operation of fault analysis, life prediction and health evaluation based on the prediction data corresponding to each operation data to obtain feedback data;
And the interaction module is used for receiving and displaying the feedback data.
9. A digital twin method for a train operation control system, applied to the train operation control system according to any one of claims 1 to 7, comprising:
The method comprises the steps of collecting various types of operation data of a train operation control system through a data layer, wherein the operation data comprise train automatic protection data, train automatic monitoring data, interlocking data, zone control data, passenger flow data, axle counting data, track circuit data, transponder data and switch machine data;
Receiving the plurality of types of operation data through a model layer; performing model simulation based on each piece of operation data to obtain prediction data corresponding to each piece of operation data; the model layer comprises a train automatic protection model for simulating the train automatic protection data, a train automatic monitoring model for simulating the train automatic monitoring data, an interlocking model for simulating the interlocking data, a zone control model for simulating the zone control data, a passenger flow model for simulating the passenger flow data, an axle counting model for simulating the axle counting data, a track circuit model for simulating the track circuit data, a transponder model for simulating the transponder data and a switcher model for simulating the switcher data;
Receiving prediction data corresponding to each operation data through an application layer; and performing at least one operation of fault analysis, life prediction and health evaluation based on the prediction data corresponding to each operation data to obtain feedback data;
and receiving and displaying the feedback data through an interaction layer.
10. The digital twinning method of a train operation control system of claim 9, further comprising:
Sending decision information to the data layer through the model layer, and sending the received decision information to a train operation control system or an interaction layer through the data layer; wherein the decision information is obtained by the model layer performing model simulation based on the operation data.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111301490A (en) * | 2020-05-15 | 2020-06-19 | 北京全路通信信号研究设计院集团有限公司 | Train operation control method and system |
| CN112801338A (en) * | 2020-12-07 | 2021-05-14 | 通控研究院(安徽)有限公司 | Auxiliary decision-making method and system for urban rail transit network operation emergency |
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| CN102279597B (en) * | 2011-05-16 | 2013-07-24 | 北京和利时***工程有限公司 | Simulation test system of train control system |
| CN109413614B (en) * | 2018-09-27 | 2020-11-06 | 北京全路通信信号研究设计院集团有限公司 | Integrated vehicle-ground comprehensive analysis platform |
| CN110766298B (en) * | 2019-10-10 | 2022-11-22 | 北京全路通信信号研究设计院集团有限公司 | Multi-standard multi-service rail transit simulation method and system |
| CN112164272B (en) * | 2020-11-06 | 2022-09-27 | 卡斯柯信号(成都)有限公司 | Signal simulation system and simulation method of tramcar signal system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112801338A (en) * | 2020-12-07 | 2021-05-14 | 通控研究院(安徽)有限公司 | Auxiliary decision-making method and system for urban rail transit network operation emergency |
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