CN109696316B - Train remote monitoring system - Google Patents
Train remote monitoring system Download PDFInfo
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- CN109696316B CN109696316B CN201710998634.4A CN201710998634A CN109696316B CN 109696316 B CN109696316 B CN 109696316B CN 201710998634 A CN201710998634 A CN 201710998634A CN 109696316 B CN109696316 B CN 109696316B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/08—Railway vehicles
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
Abstract
The invention discloses a train remote monitoring system, which comprises: the vehicle-mounted equipment and the server are used for encrypting data to ensure the security and confidentiality of the data, so that the data is prevented from being leaked; when data transmission is carried out, a unified data structure standard is established, a data compression function is used, the data volume transmitted by the front end and the back end is reduced, and the delay waiting time of the whole system is greatly reduced. In addition, the system combines and uses the traditional relational database and the non-relational database which is suitable for big data analysis and processing, the data read-write performance is enhanced through the multi-database architecture, and when big data are analyzed, the data can be analyzed through a big data processing tool. Therefore, the train detection method and the train detection system have the advantages that deep optimization is performed in the links of transmission, storage, analysis, processing and the like, and the purpose of train detection under the condition of mass data is achieved.
Description
Technical Field
The invention relates to the field of train monitoring, in particular to a train remote monitoring system.
Background
At present, in the field of train monitoring, a plurality of system architectures exist, and the train monitoring systems are mainly applied to the fields of real-time state monitoring, real-time fault alarming, fault statistical analysis, fault diagnosis, relevant data mining and the like of trains. However, with the increase of data volume, the increase of sensor number, the increase of the number of monitoring trains, the increase of data categories and the increase of data acquisition frequency, remote train monitoring has already stepped into the big data era, which causes that the system in the existing scheme is difficult to meet the current requirements in the aspects of data transmission, storage, data analysis and processing and data visualization.
Therefore, how to implement the train remote monitoring system in the big data era to efficiently and safely process mass data is a problem to be solved by technical personnel in the field.
Disclosure of Invention
The invention aims to provide a train remote monitoring system, which can efficiently and safely process mass data in a big data era.
In order to achieve the above purpose, the embodiment of the present invention provides the following technical solutions:
a train remote monitoring system comprising:
the vehicle-mounted equipment is used for acquiring real-time data of the train, encrypting and compressing the data and then sending the data to the server;
the server is used for receiving the processed data sent by the vehicle-mounted equipment and storing the real-time fault data in the processed data into a relational database so as to realize fault alarm on the vehicle-mounted equipment; and storing the real-time state data in the processed data into a non-relational database, analyzing historical data in the non-relational database through a big data processing tool to obtain a fault diagnosis result, and analyzing the real-time data in the non-relational database to obtain a state monitoring result.
The vehicle-mounted equipment is further used for detecting the current network state and sending the processed data to the server by using the data transmission mode determined by the current network state.
The scheme also comprises a client; the client is used for sending a data screening instruction to the server; receiving target data sent by the server, and displaying the target data through a visualization tool;
the server is further configured to: and receiving the data screening instruction, acquiring target data from a corresponding database according to the data type and the data requirement corresponding to the data screening instruction, and sending the target data to the client.
Wherein the visualization tool is: HighPhart.
Wherein the server is further configured to: and receiving a data access instruction sent by the client, verifying the client by using user identity information carried by the data access instruction, and if the verification is successful, allocating an access right corresponding to the user identity information to the client so that the client accesses data by using the access right.
And the client and the server transmit data by using a Websocket technology.
Wherein the server is specifically configured to: storing hot data in the real-time state data to a first relational database and storing cold data in the real-time state data to a second relational database according to the data type of the real-time state data in the processed data; the hot data includes real-time data and the cold data includes historical data.
Wherein the server is specifically configured to: and receiving the processed data sent by the vehicle-mounted equipment through a queue technology, and storing the processed data in a corresponding database.
Wherein the server is specifically configured to: and storing and managing the data by adopting a distributed storage structure, and inquiring the stored data in a Map data structure mode.
When the vehicle-mounted equipment and the server perform data interaction by using a secure transmission channel, after the identity of the opposite party is successfully verified by a bidirectional identity verification mechanism, data transmission is realized.
According to the above scheme, the train remote monitoring system provided by the embodiment of the invention comprises: the vehicle-mounted equipment is used for acquiring real-time data of the train, encrypting and compressing the data and then sending the data to the server; the server is used for receiving the processed data sent by the vehicle-mounted equipment and storing the real-time fault data in the processed data into a relational database so as to realize fault alarm on the vehicle-mounted equipment; and storing the real-time state data in the processed data into a non-relational database, analyzing historical data in the non-relational database through a big data processing tool to obtain a fault diagnosis result, and analyzing the real-time data in the non-relational database to obtain a state monitoring result.
In the scheme, in order to ensure the safety and confidentiality of data, the system carries out encryption processing on the data in a vehicle-ground communication link, so that the data is prevented from being leaked; when data transmission is carried out, a unified data structure standard is established, a data compression function is used, the data volume transmitted by the front end and the back end is reduced, and the delay waiting time of the whole system is greatly reduced. Moreover, the system combines and uses a traditional relational database and a non-relational database which is suitable for big data analysis and processing. The traditional relational database is high in efficiency and high in speed in the aspect of query statistics, the non-relational database is used for data analysis and processing on a big data platform and is not interfered with each other, but the two types of database data association analysis can be realized through a user-defined service assembly when necessary. Therefore, the train detection method and the train detection system have the advantages that deep optimization is performed in the links of transmission, storage, analysis, processing and the like, and the purpose of train detection under the condition of mass data is achieved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a train remote monitoring system disclosed in an embodiment of the present invention;
FIG. 2 is a schematic diagram of another train remote monitoring system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a specific train remote monitoring system disclosed in the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention discloses a train remote monitoring system, which aims to realize that the train remote monitoring system can efficiently and safely process mass data in a big data era.
Referring to fig. 1, a train remote monitoring system provided in an embodiment of the present invention includes:
the vehicle-mounted equipment 100 is used for acquiring real-time data of the train, encrypting and compressing the data and then sending the data to the server 200;
the vehicle-mounted device 100 is further configured to detect a current network state, and send the processed data to the server 200 in a data transmission mode determined by the current network state.
Specifically, the vehicle-mounted device 100 in this embodiment is configured to detect the state data of the train in real time, and send the state data to the server 200. After the vehicle-mounted device 100 detects the status data, in order to prevent the data leakage problem, in the vehicle-ground communication link, the transmitted data needs to be encrypted first to prevent the data leakage.
Further, the in-vehicle apparatus 100 compresses data before transmitting the data, thereby reducing the size of each packet of data. It can be understood that the system optimizes the data transmission structure, establishes a unified data structure standard, uses the data compression function, reduces the data volume transmitted by the front end and the back end, and greatly reduces the delay waiting time of the whole system.
Specifically, the vehicle-mounted device 100 in the present solution is a vehicle-mounted device using a 4G/3G/2G full network communication scheme, supports the latest 4G network system, and is also downward compatible with networks of 3G/2G systems, thereby increasing the transmission bandwidth and enhancing the transmission stability. When the vehicle-mounted device 100 transmits data to the server 200, the data transmission mode may be determined according to the network status, for example: when the network condition is good, the 4G network is used for transmission, and the network bandwidth can completely meet the requirement of high-frequency transmission of all basic data of one train. When the network condition is poor, the network is automatically switched to the 3G network and the 2G network, so that the network instability caused by 4G signal difference packet loss and repeated switching of the 4G/3G network is reduced.
The server 200 is configured to receive the processed data sent by the vehicle-mounted device 100, and store real-time fault data in the processed data in a relational database, so as to implement fault alarm on the vehicle-mounted device 100; and storing the real-time state data in the processed data into a non-relational database, analyzing historical data in the non-relational database through a big data processing tool to obtain a fault diagnosis result, and analyzing the real-time data in the non-relational database to obtain a state monitoring result.
Wherein, the server 200 is specifically configured to: and receiving the processed data sent by the vehicle-mounted device 100 through a queue technology, and storing the processed data in a corresponding database.
Specifically, the server 200 in this embodiment uses a queue technology, and it is ensured that data can still be efficiently analyzed and put in storage under the condition of high concurrency. In addition, in the aspect of data storage, the system combines and uses a traditional relational database and a non-relational database which is suitable for big data analysis processing. The traditional relational database is high in efficiency and speed in the aspect of inquiry statistics and is used for storing historical data such as train positioning data and fault data. The non-relational database is used for data analysis processing of a big data platform, mutual interference is avoided, data association analysis of the two types of databases can be achieved through a user-defined service component if necessary, and data read-write performance is enhanced through the multi-database architecture mode. Therefore, the train detection method and the train detection system have the advantages that deep optimization is performed in the links of transmission, storage, analysis, processing and the like, and the purpose of train detection under the condition of mass data is achieved.
Based on the foregoing embodiment, in this embodiment, the server 200 is specifically configured to: storing hot data in the real-time state data to a first relational database and storing cold data in the real-time state data to a second relational database according to the data type of the real-time state data in the processed data; the hot data includes real-time data and the cold data includes historical data.
The server 200 is specifically configured to: and storing and managing the data by adopting a distributed storage structure, and inquiring the stored data in a Map data structure mode.
It should be noted that, in this embodiment, the hot data and the cold data are stored separately, so that the problem of data access performance caused by different application service scenarios and different data usage frequencies can be solved. Hot data is real-time status data that the latest user may need to use many times, and cold data is data that the user who is a long time away does not need to use frequently compared to hot data. Moreover, the server 200 adopts a distributed storage structure to store and manage real-time mass data, and the real-time state data can realize dynamic real-time update management.
In addition, in the aspect of data analysis and processing, Hadoop and a series of big data processing tools are used for processing big data. In addition, according to the scheme, a memory data cache architecture based on configurable parameters is designed, so that the database query IO of basic protocol data configuration is reduced, and meanwhile, the performance is greatly improved based on the query mode of a memory Map data structure.
Referring to fig. 2, based on any of the above embodiments, the train remote monitoring system in this embodiment further includes a client 300;
the client 300 is configured to send a data filtering instruction to the server 200; receiving target data sent by the server 200 and displaying the target data through a visualization tool; wherein, the visualization tool is: HighCart;
the server 200 is further configured to: and receiving the data screening instruction, and acquiring target data from a corresponding database according to the data type and the data requirement corresponding to the data screening instruction.
Specifically, as the number of trains is increased, the types and the number of data are increased, and how to display data concerned by a user in a limited display screen becomes a difficult problem. Therefore, in the scheme, single-point tracking and multipoint tracking can be selected in the aspects of a system real-time monitoring part and train positioning and tracking. And when the data is displayed, a large number of colors and animation effects can be used, so that a user can see the running conditions, fault states and the like of all trains on the electronic map. For the fault modules in the system, the system provides various flexible screening conditions, and a user can screen out the faults to be displayed according to a series of conditions such as time, position, grade and the like. In the aspect of statistical analysis, various clear charts with clear colors are used in a large quantity, and even if the data size is larger, a user can find out concerned data from mass data immediately.
Therefore, in the present scheme, when the user screens and displays data through the client 300, the server 200 first finds corresponding data from the database according to the data type and data requirement of the data screening instruction sent by the user, returns the data to the client 300, and displays the data through the client 300; when the data is displayed, the data can be displayed according to preset display rules, and the readability of the data is greatly improved by combining data visualization tools such as HighHart and the like.
Based on the foregoing embodiment, the server 200 in this embodiment is further configured to: receiving a data access instruction sent by a client 300, verifying the client 300 by using user identity information carried in the data access instruction, and if the verification is successful, allocating an access right corresponding to the user identity information to the client 300 so that the client 300 accesses data by using the access right.
It can be understood that in the link from the web server to the user PC in the present solution, the server in the present solution adopts white list verification, which prohibits access of illegal IP. After the user is successfully verified, the access right corresponding to the user grade is allocated, and the user only has the access right corresponding to the own grade; furthermore, the scheme separates the read-write permission of the database, and prevents the database from being tampered and deleted. In addition, according to the scheme, SQL injection verification prevention and CSRF attack prevention processing are performed on the web program code layer, and the risk of data leakage is reduced. Therefore, the whole web system provided by the scheme adopts strict identity authentication and authority management, different users can only access authorized content, and the problem of override access is prevented.
It should be noted that in the present solution, a websocket technology is also applied between the server 200 and the client 300 of the entire web system, and data transmission is performed only when data is updated, so that the system can withstand the test of multiple concurrent and large number of periodic polling access requests.
Based on any of the above embodiments, in this embodiment, when the vehicle-mounted device 100 and the server 200 perform data interaction by using a secure transmission channel, after the identity of the other party is successfully verified by a bidirectional identity verification mechanism, data transmission is achieved.
In this scheme, in order to increase the security of data transmission, the server 200 and the vehicle-mounted device 100 perform bidirectional authentication and establish a secure transmission channel during data transmission, so as to prevent counterfeit data and data hijacking. Referring to fig. 3, for the specific schematic structural diagram of the train remote monitoring system provided in this embodiment, it can be seen that the scheme is deeply optimized for transmission, storage, analysis and processing, data visualization and the like of mass train data, a high-efficiency reasonable frame is built, the data security is verified, and the purpose of train monitoring under the condition of mass data is achieved.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. A train remote monitoring system, comprising:
the vehicle-mounted equipment is used for acquiring real-time data of the train, encrypting and compressing the data and then sending the data to the server; the vehicle-mounted equipment is also used for detecting the current network state and sending the processed data to the server by using a data transmission mode determined by the current network state; when the network condition is poor, the network is automatically switched to a 3G network and a 2G network;
the server is used for receiving the processed data sent by the vehicle-mounted equipment and storing the real-time fault data in the processed data into a relational database so as to realize fault alarm on the vehicle-mounted equipment; and storing the real-time state data in the processed data into a non-relational database, analyzing historical data in the non-relational database through a big data processing tool to obtain a fault diagnosis result, and analyzing the real-time data in the non-relational database to obtain a state monitoring result.
2. The train remote monitoring system according to claim 1, further comprising a client; the client is used for sending a data screening instruction to the server; receiving target data sent by the server, and displaying the target data through a visualization tool;
the server is further configured to: and receiving the data screening instruction, acquiring target data from a corresponding database according to the data type and the data requirement corresponding to the data screening instruction, and sending the target data to the client.
3. The train remote monitoring system according to claim 2, wherein the visualization tool is: HighPhart.
4. The train remote monitoring system of claim 2, wherein the server is further configured to: and receiving a data access instruction sent by the client, verifying the client by using user identity information carried by the data access instruction, and if the verification is successful, allocating an access right corresponding to the user identity information to the client so that the client accesses data by using the access right.
5. The train remote monitoring system according to claim 2, wherein the client and the server transmit data by using Websocket technology.
6. The train remote monitoring system of claim 1,
the server is specifically configured to: storing hot data in the real-time state data to a first relational database and storing cold data in the real-time state data to a second relational database according to the data type of the real-time state data in the processed data; the hot data includes real-time data and the cold data includes historical data.
7. The train remote monitoring system according to claim 6, wherein the server is specifically configured to: and receiving the processed data sent by the vehicle-mounted equipment through a queue technology, and storing the processed data in a corresponding database.
8. The train remote monitoring system according to claim 7, wherein the server is specifically configured to: and storing and managing the data by adopting a distributed storage structure, and inquiring the stored data in a Map data structure mode.
9. The train remote monitoring system according to any one of claims 1 to 8, wherein when the on-board device and the server perform data interaction by using a secure transmission channel, after the identity of the other party is successfully verified by a bidirectional identity verification mechanism, data transmission is realized.
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| CN112098117A (en) * | 2020-08-19 | 2020-12-18 | 中车长春轨道客车股份有限公司 | Data acquisition and quality analysis system for debugging process of motor train unit |
| CN112258690B (en) * | 2020-10-23 | 2022-09-06 | 中车青岛四方机车车辆股份有限公司 | Data access method and device and data storage method and device |
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| US20140059296A1 (en) * | 2012-08-27 | 2014-02-27 | Synchronoss Technologies, Inc. | Storage technology agnostic system for persisting software instantiated objects |
| CN104219310A (en) * | 2014-09-04 | 2014-12-17 | 吉林大学 | Automobile long-distance information system |
| CN104965850B (en) * | 2015-04-29 | 2018-01-30 | 云南电网有限责任公司 | A kind of database high availability implementation method based on open source technology |
| CN104944240A (en) * | 2015-05-19 | 2015-09-30 | 重庆大学 | Elevator equipment state monitoring system based on large data technology |
| CN106027283A (en) * | 2016-04-29 | 2016-10-12 | 福建星海通信科技有限公司 | Method for parsing, storing and real-time displaying of high-concurrency vehicle acquisition data |
| CN106021613A (en) * | 2016-06-30 | 2016-10-12 | 武汉理工大学 | Bridge health monitoring system based on Hadoop |
| CN106685703A (en) * | 2016-12-13 | 2017-05-17 | 浙江工业大学 | Intelligent data collection and visual monitoring system |
| CN106406296B (en) * | 2016-12-14 | 2019-04-23 | 东北大学 | It is a kind of based on vehicle-mounted and cloud train fault diagnostic system and method |
| CN106709035B (en) * | 2016-12-29 | 2019-11-26 | 贵州电网有限责任公司电力科学研究院 | A kind of pretreatment system of electric power multidimensional panoramic view data |
| CN106899691B (en) * | 2017-03-16 | 2020-11-13 | 广州大学 | Intelligent Internet of things monitoring system and method based on cloud platform |
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