CN112396905A - Cross-network and distance-crossing-based railway multiplex distributed simulation method and system - Google Patents
Cross-network and distance-crossing-based railway multiplex distributed simulation method and system Download PDFInfo
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Abstract
The invention discloses a cross-network and distance-spanning based railway multiplex distributed simulation method and a system, which relate to the field of railway simulation training and have the technical scheme key points that: carrying out simulation training on different training stages of different work types of the railway through a training client; completing core calculation tasks of training clients corresponding to various work categories through a simulation server; and counting and managing the dependency relationship of the characteristic core calculation process in each training client through a synchronization manager, triggering and controlling the training clients to perform simulation model calculation according to the dependency relationship in sequence, performing timestamp registration after the corresponding training clients finish data transmission, and performing synchronization point registration and updating after all timestamp registrations are finished in a synchronization period. The invention can realize the data interactive synchronization of the joint drilling process of the training subsystems across networks and distances, ensure that the simulation speed meets the real-time requirement, does not need to add extra hardware equipment and has good application prospect.
Description
Technical Field
The invention relates to the field of railway simulation training, in particular to a railway multiplex distributed simulation method and system based on cross-network and cross-distance.
Background
The large-scale construction and investment operation of railways lead the training requirements of railway workers to be continuously increased, and the railway multiplex combined simulation training system comes up at the same time. The railway multi-work joint simulation training system is often distributed in different areas and has the characteristic of distance span. Meanwhile, all modules of the system in the same area communicate by means of an internal local area network, and all modules in different areas communicate by means of a special railway network connection in a star network structure, so that the system has the characteristic of cross-network.
However, in the joint drilling process of the cross-network and distance-crossing railway multi-type different-place distributed simulation training system, when modules in different regions communicate, data asynchronism exists, so that the simulation result of the system is inaccurate; in addition, the unreasonable arrangement of the position of the simulation server in the railway private network structure reduces the simulation speed to some extent. Therefore, how to research and design a railway multiplex distributed simulation method and system based on cross-network and cross-distance with accurate simulation result and high simulation speed is a problem which is urgently needed to be solved at present.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide a railway multiplex distributed simulation method and system based on cross-network and cross-distance.
The technical purpose of the invention is realized by the following technical scheme:
in a first aspect, a cross-network and cross-distance based railway multiplex distributed simulation method is provided, which comprises the following steps:
s101: carrying out simulation training on different training stages of different work types of the railway through a training client;
s102: completing core calculation tasks of training clients corresponding to various work categories through a simulation server;
s103: and counting and managing the dependency relationship of the characteristic core calculation process in each training client through a synchronization manager, triggering and controlling the training clients to perform simulation model calculation according to the dependency relationship in sequence, performing timestamp registration after the corresponding training clients finish data transmission, and performing synchronization point registration and updating after all timestamp registrations are finished in a synchronization period.
Further, the specific method of the synchronization point registration is as follows:
when the simulation training system is started, a synchronization manager registers a first synchronization point, and according to the dependency relationship, the synchronization manager firstly triggers a training client without a dependency item to perform simulation model calculation;
the synchronous manager detects the state of the corresponding training client in real time in the whole period of simulation model calculation and data transmission of the training client; if the training client finishes data sending, performing timestamp registration and recording the time point when the training client finishes calculation; if the training client does not finish data transmission, continuing to detect;
and after the synchronization manager finishes the timestamp registration of the last training client side of the dependency relationship, a new synchronization point is registered, and the system enters a new synchronization period.
Furthermore, the training client is classified according to a traffic dispatcher, an assistant dispatcher, a station attendant, a vehicle service, a machine service, a work service, an electric service, a vehicle, a driver and an on-board mechanic, and is used for simulation training of scene restoration of various work types of railways, fault scene simulation, operation drilling, assessment scoring and participation in multi-work type combined drilling.
Further, the location selection of the simulation server specifically includes:
establishing a network structure matrix of the simulation training system according to the unit period data transmission quantity of the local area network and the configuration condition of the training client;
establishing a railway private network structure matrix of the simulation training system according to the upper limit value of the railway private network bandwidth and the configuration quantity of the railway private network;
determining a client configuration matrix according to the actual configuration quantity of the training clients, determining a transmission quantity matrix after evaluating the synchronous bandwidth of each type of training clients, and calculating and determining a network structure matrix according to the client configuration matrix and the transmission quantity matrix;
and calculating a bandwidth redundancy matrix of the simulation training system according to the network structure matrix and the railway private network structure matrix, judging and analyzing whether the railway private network meets the requirement of the corresponding simulation training system on external data transmission according to the bandwidth redundancy matrix, and simultaneously determining the position selection range of the simulation server.
Further, the network structure matrix FAThe method specifically comprises the following steps:
FA＝{f1，f2，f3，……，fm}＝AX
wherein f is1、f2、f3、fmThe unit period data transmission quantity of each local area network in the simulation training system is represented, and the value of m is determined by the actual network structure of the system; the matrix A ═ aij)m×nRepresenting the configuration of a training client in a simulated training system, aijIs a positive integer; matrix X ═ Xij)n×1And the data transmission quantity of unit cycle of each training client in the simulation training system is shown.
Further, the railway private network structure matrix FBThe method specifically comprises the following steps:
FB＝{w1，w2，w3，……，wm}
wherein, w1、w2、w3、wmAnd the upper limit value of the bandwidth of each local railway private network in the simulation training system is shown.
Further, the bandwidth redundancy matrix FCThe method specifically comprises the following steps:
the special railway network structure matrix FBAnd network structure matrix FASubtracting to obtain a bandwidth redundancy matrixFCThe method comprises the following steps:
according to thetaiWhether it is greater than zero, i ∈ {1, 2, … …, m }:
if theta is presentiIf the number of the simulation servers is less than zero, the railway private network cannot meet the requirement of the area on external data transmission of the simulation training system, and the simulation servers can only be arranged in the area to serve as central nodes of the railway private network star-shaped network structure;
if all regions thetaiIf the value is larger than zero, the special railway network can meet the requirement of the simulation training system in any area on external data transmission, and the simulation server is not limited to be arranged in a certain place.
Further, the selection of the optimal position of the simulation server specifically comprises:
when all regions theta are satisfiediWhen the bandwidth is larger than zero, calculating a bandwidth redundancy matrix F of the simulation training system with the simulation server arranged at different regionsc' and railway special network structure matrix FBThe mean square error MSE α of' is specifically as follows:
wherein, Fc' denotes a bandwidth redundancy matrix FCVariation of bandwidth redundancy value, theta, to remove the place where the simulation server is locatedi' is a matrix Fc' each element; fB' indicating railway private network structure matrix FBRemoving the upper limit value of the bandwidth of the private network of the railway of the set place of the simulation serveri' is a matrix FB' each element;
and selecting a position scheme when the MSE alpha is the minimum value as the optimal position of the simulation server, wherein the bandwidth redundancy of the railway private network is highest and the data transmission time of the system is fastest.
In a second aspect, a railway multiplex distributed simulation system based on cross-network distance crossing is provided, which includes:
the training clients are used for carrying out simulation training on different training stages of different work types of the railway;
the simulation server is used for completing the core calculation task of the training client corresponding to each work type;
and the synchronization manager is used for counting and managing the dependency relationship of the characteristic core calculation process in each training client, triggering and controlling the training clients to perform simulation model calculation according to the dependency relationship in sequence, performing timestamp registration after the corresponding training clients finish data transmission, and performing synchronization point registration and updating after all timestamp registrations are finished in a synchronization period.
Compared with the prior art, the invention has the following beneficial effects:
the method can be applied to a railway multi-engineering remote distributed simulation training system, realizes the interactive synchronization of data in the joint drilling process of the training subsystems across the network and the distance, ensures that the simulation speed meets the real-time requirement, well solves the problem of data synchronization caused by the limitation of the bandwidth of a railway special network in the railway multi-engineering remote distributed simulation training system across the network and the distance, does not need to add extra hardware equipment, and has good application prospect.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a diagram illustrating a synchronization point registration process according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a network architecture of a simulation training system according to an embodiment of the present invention;
FIG. 3 is a flow chart of synchronization point registration in an embodiment of the present invention;
FIG. 4 is a flow chart of simulation server location optimization in an embodiment of the present invention.
Detailed Description
In order that the objects, aspects and advantages of the present invention will become more apparent, the present invention will be further described in detail with reference to the following examples and accompanying fig. 1-4, wherein the exemplary embodiments and descriptions thereof are provided for illustrative purposes only and are not provided as limitations on the present invention
Example 1
A cross-network and cross-distance based railway multiplex distributed simulation method, as shown in fig. 1, includes the following steps:
s101: carrying out simulation training on different training stages of different work types of the railway through a training client;
s102: completing core calculation tasks of training clients corresponding to various work categories through a simulation server;
s103: and counting and managing the dependency relationship of the characteristic core calculation process in each training client through a synchronization manager, triggering and controlling the training clients to perform simulation model calculation according to the dependency relationship in sequence, performing timestamp registration after the corresponding training clients finish data transmission, and performing synchronization point registration and updating after all timestamp registrations are finished in a synchronization period.
As shown in FIG. 1 and FIG. 3, the dependency relationship is X1-＞X3->X2-＞……->XnFor example, the specific method of synchronization point registration is as follows:
the synchronous manager registers a first synchronous point T when the simulation training system is started0The synchronous manager firstly triggers the training client X without the dependent item according to the dependency relationship1And carrying out simulation model calculation.
Training client X1During the whole period T of simulation model calculation and data transmissionaIn the method, a synchronization manager detects a corresponding training client X in real time1The state of (1); if training client X1And after the data transmission is finished, performing timestamp registration and recording the time point a of the training client for finishing the calculation1(ii) a If training client X1And if the data transmission is not finished, the detection is continued.
Sync manager complete X1After registering the timestamp, according to the dependency relationship X1-＞X3->X2-＞……->XnTrigger trainingClient X3Model calculation of (1) at training client X3Whole T for model calculation and data transmissionbPeriodic, synchronous manager real-time detection training client X3X3If training client X is detected3After the data transmission is finished, time stamp registration is carried out, and a training client X is recorded3Is calculated by the calculation completion time b1(ii) a Training client X if detection3If the data transmission is not completed, the detection is continued.
Synchronization manager pair X2-＞……-＞XnClient computing management process and X1-＞X3The calculation management process is the same. Last training client X when the synchronization manager completes the dependency relationshipnAfter the time stamp of (2) is registered, a new synchronization point T is registered1The system enters a new synchronization cycle.
The training client is classified according to a driving dispatcher, an assistant dispatcher, a station attendant, a vehicle service, a machine service, a work service, an electric service, a vehicle, a driver and a vehicle-mounted mechanic, and is used for simulation training of scene restoration, fault scene simulation, operation drilling, assessment scoring and participation of multi-work type combined drilling of various work types of railways.
Example 2
As shown in fig. 2 and 4, the location selection of the simulation server specifically includes:
firstly, establishing a network structure matrix of a simulation training system according to the unit cycle data transmission quantity of a local area network and the configuration condition of a training client; network structure matrix FAThe method specifically comprises the following steps:
wherein f is1、f2、f3、fmThe unit period data transmission quantity of each local area network in the simulation training system is represented, and the value of m is determined by the actual network structure of the system; the matrix A ═ aij)m×nRepresenting the configuration of a training client in a simulated training system, aijTo be just neatCounting; matrix X ═ Xij)n×1And the data transmission quantity of unit cycle of each training client in the simulation training system is shown.
Secondly, establishing a railway private network structure matrix of the simulation training system according to the upper limit value of the railway private network bandwidth and the configuration quantity of the railway private network; railway special network structure matrix FBThe method specifically comprises the following steps:
FB＝{w1，w2，w3，……，wm}T
wherein, w1、w2、w3、wmAnd the upper limit value of the bandwidth of each local railway private network in the simulation training system is shown.
Thirdly, determining a client configuration matrix according to the actual configuration quantity of the training clients, determining a transmission quantity matrix after evaluating the synchronous bandwidth of each type of training clients, and calculating and determining a network structure matrix according to the client configuration matrix and the transmission quantity matrix, wherein the method specifically comprises the following steps: fA＝{f1，f2，f3，……，fm}T＝AX。
And fourthly, calculating a bandwidth redundancy matrix of the simulation training system according to the network structure matrix and the railway private network structure matrix, judging and analyzing whether the railway private network meets the requirement of the corresponding simulation training system on external data transmission according to the bandwidth redundancy matrix, and simultaneously determining the position selection range of the simulation server.
Bandwidth redundancy matrix FCThe method specifically comprises the following steps:
the special railway network structure matrix FBAnd network structure matrix FASubtracting to obtain a bandwidth redundancy matrix FCThe method comprises the following steps:
according to thetaiWhether it is greater than zero, i ∈ {1, 2, … …, m }: if theta is presentiIf the value is less than zero, the condition that the railway private network cannot meet the external data transmission of the simulation training system in the area is indicatedThe simulation server can be arranged in the area only as a central node of a railway special network star network structure according to the input requirement; if all regions thetaiIf the value is larger than zero, the special railway network can meet the requirement of the simulation training system in any area on external data transmission, and the simulation server is not limited to be arranged in a certain place.
The selection of the optimal position of the simulation server specifically comprises the following steps:
when all regions theta are satisfiediWhen the bandwidth is larger than zero, calculating a bandwidth redundancy matrix F of the simulation training system with the simulation server arranged at different regionsc' and railway special network structure matrix FBThe mean square error MSE α of' is specifically as follows:
wherein, Fc' denotes a bandwidth redundancy matrix FCVariation of bandwidth redundancy value, theta, to remove the place where the simulation server is locatedi' is a matrix Fc' each element; fB' indicating railway private network structure matrix FBRemoving the upper limit value of the bandwidth of the private network of the railway of the set place of the simulation serveri' is a matrix FBEach element of' is described.
It should be understood that when the server is located in a certain region, the communication between the simulation client and the server in the region depends on the internal local area network, and is not limited by the bandwidth of the private railway network. Therefore, assuming that the server is located in a certain area, F needs to be setcAnd FBAnd removing the relevant elements to perform the variant processing.
And selecting a position scheme when the MSE alpha is the minimum value as the optimal position of the simulation server, wherein the bandwidth redundancy of the railway private network is highest and the data transmission time of the system is fastest.
Example 3
The concrete situation of a certain actual distance-spanning railway multiplex different-place distributed simulation training system across the network is explained.
Firstly, constructing a network structure matrix F according to the actual condition of the systemA：
Wherein f is1Representing the data transmission quantity f of the unit cycle of the local area network of the railway multi-work different-place distributed simulation training system A2Expressing the data transmission quantity f of the unit cycle number of the local area network of the railway multi-work different-place distributed simulation training system B3And the data transmission quantity of the local area network unit period of the railway multi-station different-place distributed simulation training system C is represented.
The matrix A ═ aij)3×10Representing the client configuration condition of the railway multi-station remote distributed simulation training system of the whole cross-network span distance, aijThe configuration number of the client sides of the traveling dispatcher, the assistant dispatcher, the station attendant, the vehicle affairs, the locomotive affairs, the engineering affairs, the electric affairs, the vehicle, the driver and the vehicle-mounted mechanic is represented by a positive integer. Wherein the content of the first and second substances,
the overall client configuration situation of the railway multi-station distributed simulation training system A is shown,
the overall client configuration situation of the railway multi-station distributed simulation training system B is shown,
the overall client configuration condition of the railway multi-station distributed simulation training system C is shown.
Matrix X ═ Xij)10×1Unit period data transmission quantity, x, of each client of railway multi-station remote distributed simulation training system for representing cross-network and cross-distance1Data transmission quantity per cycle, x, on behalf of a driving dispatcher client2Data volume per cycle, x, on behalf of an assistant dispatcher client3Data transmission quantity per week, x, representing station attendant client4Representative vehicleData volume per cycle, x, of the service client5Data transmission quantity per period, x, on behalf of the client of the locomotive6Representing the data transmission volume per cycle, x, of a business client7Representing the data transmission quantity per cycle, x, of the electricity client8Representing the amount of data transmission per cycle, x, of a vehicle client9Representing the amount of data transmission per cycle, x, of the driving simulator client10Representing the data transmission volume per week of the on-board mechanic client.
Secondly, determining a matrix A according to the actual client configuration conditions of each region:
by evaluating the synchronization bandwidth of various types of clients, a matrix X is determined:
X＝{3，2，4，2，2，2，1，1，5，2}T；
thereby calculating and determining a system network structure matrix FA：
FA＝{12，5，14}T。
Thirdly, determining a structural matrix F of the railway private network of the system according to the actual condition of the systemB：
FB＝{20，20，20}T。
Fourthly, a system railway private network structure matrix F is combinedBAnd system network structure matrix FASubtracting and calculating a bandwidth redundancy matrix FC：
Fifth, the bandwidth redundancy matrix FcEach element of (2) is greater than 0, and a system bandwidth redundancy matrix F is calculated when the simulation server is arranged at different regionsc' and railway special network structure matrix FBMean square error of `:
(1) when the server is arranged on the A place, the system railway private network structure matrix FB′：
FB′＝{20，20}T
System bandwidth redundancy matrix Fc′：
Fc′＝{15，6}T
Calculating Fc' and FBMean square error MSE1 of':
(2) when the server is arranged on the B place, the system railway private network structure matrix FB′：
FB′＝{20，20}T
System bandwidth redundancy matrix Fc′：
Fc′＝{8，6}T
Calculating Fc' and FBMean square error MSE2 of':
(3) when the server is arranged on the C place, the system railway private network structure matrix FB′：
FB′＝{20，20}T
System bandwidth redundancy matrix Fc′：
Fc′＝{8，15}T
Calculating Fc' and FBMean square error MSE3 of':
it can be seen that MSE3 < MSE1 < MSE2, therefore, when the server is located at C, the system bandwidth redundancy is the highest and the data transmission is the fastest.
Example 4
The railway multiplex distributed simulation system based on cross-network and cross-distance comprises a simulation server, a synchronization manager and a plurality of training clients. And the training clients are used for carrying out simulation training on different training stages of different work types of railways. And the simulation server is used for completing the core calculation task of the training client corresponding to each work type. And the synchronization manager is used for counting and managing the dependency relationship of the characteristic core calculation process in each training client, triggering and controlling the training clients to perform simulation model calculation according to the dependency relationship in sequence, performing timestamp registration after the corresponding training clients finish data transmission, and performing synchronization point registration and updating after all timestamp registrations are finished in a synchronization period.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. The railway multiplex distributed simulation method based on cross-network and cross-distance is characterized by comprising the following steps of:
s101: carrying out simulation training on different training stages of different work types of the railway through a training client;
s102: completing core calculation tasks of training clients corresponding to various work categories through a simulation server;
s103: and counting and managing the dependency relationship of the characteristic core calculation process in each training client through a synchronization manager, triggering and controlling the training clients to perform simulation model calculation according to the dependency relationship in sequence, performing timestamp registration after the corresponding training clients finish data transmission, and performing synchronization point registration and updating after all timestamp registrations are finished in a synchronization period.
2. The method for multiplex distributed simulation of railways based on cross-network and cross-distance according to claim 1, wherein the specific method for registering the synchronization points is as follows:
when the simulation training system is started, a synchronization manager registers a first synchronization point, and according to the dependency relationship, the synchronization manager firstly triggers a training client without a dependency item to perform simulation model calculation;
the synchronous manager detects the state of the corresponding training client in real time in the whole period of simulation model calculation and data transmission of the training client; if the training client finishes data sending, performing timestamp registration and recording the time point when the training client finishes calculation; if the training client does not finish data transmission, continuing to detect;
and after the synchronization manager finishes the timestamp registration of the last training client side of the dependency relationship, a new synchronization point is registered, and the system enters a new synchronization period.
3. The method as claimed in claim 1, wherein the training clients are classified according to driving dispatchers, assistant dispatchers, station operators, car services, machine services, engineering services, electric services, vehicles, drivers and vehicle-mounted machinists, and are used for simulation training of site scene restoration, fault scene simulation, operation drilling, assessment scoring and participation in multi-engineering combined drilling of the railway.
4. The cross-network and distance-span based railway multiplex distributed simulation method according to claim 1, wherein the selection of the location of the simulation server is specifically as follows:
establishing a network structure matrix of the simulation training system according to the unit period data transmission quantity of the local area network and the configuration condition of the training client;
establishing a railway private network structure matrix of the simulation training system according to the upper limit value of the railway private network bandwidth and the configuration quantity of the railway private network;
determining a client configuration matrix according to the actual configuration quantity of the training clients, determining a transmission quantity matrix after evaluating the synchronous bandwidth of each type of training clients, and calculating and determining a network structure matrix according to the client configuration matrix and the transmission quantity matrix;
and calculating a bandwidth redundancy matrix of the simulation training system according to the network structure matrix and the railway private network structure matrix, judging and analyzing whether the railway private network meets the requirement of the corresponding simulation training system on external data transmission according to the bandwidth redundancy matrix, and simultaneously determining the position selection range of the simulation server.
5. The method for multi-tasking distributed simulation of railways according to claim 4, wherein the network structure matrix F is a matrix of network structuresAThe method specifically comprises the following steps:
FA＝{f1，f2，f3，......，fm}T＝AX
wherein f is1、f2、f3、fmThe unit period data transmission quantity of each local area network in the simulation training system is represented, and the value of m is determined by the actual network structure of the system; the matrix A ═ aij)m×nRepresenting the configuration of a training client in a simulated training system, aijIs a positive integer; matrix X ═ Xij)n×1And the data transmission quantity of unit cycle of each training client in the simulation training system is shown.
6. The method for multi-network and distance-span based railway multi-distributed simulation as claimed in claim 5, wherein the railway special network structure matrix FBThe method specifically comprises the following steps:
FB＝{w1，w2，w3，......，wm}T
wherein, w1、w2、w3、wmAnd the upper limit value of the bandwidth of each local railway private network in the simulation training system is shown.
7. The method for railway multiplex distributed simulation based on cross-network and cross-distance according to claim 6, wherein the bandwidth redundancy matrix FCThe method specifically comprises the following steps:
the special railway network structure matrix FBAnd network structure matrix FASubtracting to obtain a bandwidth redundancy matrix FCThe method comprises the following steps:
according to thetaiWhether it is greater than zero, i ∈ {1, 2, … …, m }:
if theta is presentiIf the number of the simulation servers is less than zero, the railway private network cannot meet the requirement of the area on external data transmission of the simulation training system, and the simulation servers can only be arranged in the area to serve as central nodes of the railway private network star-shaped network structure;
if all regions thetaiIf the value is larger than zero, the special railway network can meet the requirement of the simulation training system in any area on external data transmission, and the simulation server is not limited to be arranged in a certain place.
8. The cross-network and distance-span based railway multiplex distributed simulation method according to claim 4, wherein the optimal position of the simulation server is selected specifically as follows:
when all regions theta are satisfiediWhen the bandwidth is larger than zero, calculating a bandwidth redundancy matrix F of the simulation training system with the simulation server arranged at different regionsc' and railway special network structure matrix FBThe mean square error MSE α of' is specifically as follows:
wherein, Fc' denotes a bandwidth redundancy matrix FCVariation of bandwidth redundancy value, theta, to remove the place where the simulation server is locatedi' is a matrix Fc' each element; fB' indicating railway private network structure matrix FBRemoving the upper limit value of the bandwidth of the private network of the railway of the set place of the simulation serveri' is a matrix FB' each element;
and selecting a position scheme when the MSE alpha is the minimum value as the optimal position of the simulation server, wherein the bandwidth redundancy of the railway private network is highest and the data transmission time of the system is fastest.
9. The railway multiplex distributed simulation system based on cross-network and cross-distance is characterized by comprising the following components:
the training clients are used for carrying out simulation training on different training stages of different work types of the railway;
the simulation server is used for completing the core calculation task of the training client corresponding to each work type;
and the synchronization manager is used for counting and managing the dependency relationship of the characteristic core calculation process in each training client, triggering and controlling the training clients to perform simulation model calculation according to the dependency relationship in sequence, performing timestamp registration after the corresponding training clients finish data transmission, and performing synchronization point registration and updating after all timestamp registrations are finished in a synchronization period.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100811453B1 (en) * | 2007-01-17 | 2008-03-10 | 한국철도시설공단 | System for supporting railroad construction and operating method therefor |
| CN201918047U (en) * | 2010-12-30 | 2011-08-03 | 成都运达轨道交通设备有限公司 | Multi-work-type combination practice simulation training system for rail transportation |
| CN105138409A (en) * | 2015-08-25 | 2015-12-09 | 西南交通大学 | Railway train working diagram compiling system and method based on multiple processes |
| US20160253446A1 (en) * | 2015-02-26 | 2016-09-01 | Texas Instruments Incorporated | System and method for high-speed serial link design |
| CN107621788A (en) * | 2017-09-11 | 2018-01-23 | 北京电子工程总体研究所 | A kind of collaborative simulation system and server |
| CN110942695A (en) * | 2019-12-11 | 2020-03-31 | 西南交通大学 | Switching method between railway multiplex teaching and training organization and training modes |
| CN111026089A (en) * | 2019-12-25 | 2020-04-17 | 卡斯柯信号(北京)有限公司 | Automatic deployment method and device for train control center test environment |
-
2020
- 2020-11-12 CN CN202011259700.4A patent/CN112396905B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100811453B1 (en) * | 2007-01-17 | 2008-03-10 | 한국철도시설공단 | System for supporting railroad construction and operating method therefor |
| CN201918047U (en) * | 2010-12-30 | 2011-08-03 | 成都运达轨道交通设备有限公司 | Multi-work-type combination practice simulation training system for rail transportation |
| US20160253446A1 (en) * | 2015-02-26 | 2016-09-01 | Texas Instruments Incorporated | System and method for high-speed serial link design |
| CN105138409A (en) * | 2015-08-25 | 2015-12-09 | 西南交通大学 | Railway train working diagram compiling system and method based on multiple processes |
| CN107621788A (en) * | 2017-09-11 | 2018-01-23 | 北京电子工程总体研究所 | A kind of collaborative simulation system and server |
| CN110942695A (en) * | 2019-12-11 | 2020-03-31 | 西南交通大学 | Switching method between railway multiplex teaching and training organization and training modes |
| CN111026089A (en) * | 2019-12-25 | 2020-04-17 | 卡斯柯信号(北京)有限公司 | Automatic deployment method and device for train control center test environment |
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