scholarly journals Research on Real-time and Reliability of Wireless Transmission of High-speed Train Control Data Based on Data Mining Technology

2021 ◽  
Vol 1952 (4) ◽  
pp. 042093
Author(s):  
Mingyu Luo ◽  
Liguo Zhu
Keyword(s):  
Data Mining ◽  
Real Time ◽  
High Speed ◽  
Wireless Transmission ◽  
High Speed Train ◽  
Control Data ◽  
Mining Technology ◽  
Train Control

scholarly journals Parallel anomaly detection algorithm for cybersecurity on the highspeed train control system

2021 ◽  
Vol 19 (1) ◽  
pp. 287-308
Author(s):  
Zhoukai Wang ◽  
◽  
Xinhong Hei ◽  
Weigang Ma ◽  
Yichuan Wang ◽  
...  
Keyword(s):  
Data Transmission ◽  
High Speed ◽  
Detection Algorithm ◽  
Data Detection ◽  
High Speed Train ◽  
Control Data ◽  
Control Center ◽  
Train Control ◽  
Train Control System ◽  
Distributed Platform

<abstract> <p>With the rapid development of the high-speed train industry, the high-speed train control system has now been exposed to a complicated network environment full of dangers. This paper provides a speculative parallel data detection algorithm to rapidly detect the potential threats and ensure data transmission security in the railway network. At first, the structure of the high-speed train control data received by the railway control center was analyzed and divided tentatively into small chunks to eliminate the inside dependencies. Then the traditional threat detection algorithm based on deterministic finite automaton was reformed by the speculative parallel optimization so that the inline relationship's influences that affected the data detection order could be avoided. At last, the speculative parallel detection algorithm would inspect the divided data chunks on a distributed platform. With the help of both the speculative parallel technique and the distributed platform, the detection deficiency for train control data was improved significantly. The results showed that the proposed algorithm exhibited better performance and scalability when compared with the traditional, non-parallel detection method, and massive train control data could be inspected and processed promptly. Now it has been proved by practical use that the proposed algorithm was stable and reliable. Our local train control center was able to quickly detect the anomaly and make a fast response during the train control data transmission by adopting the proposed algorithm.</p> </abstract>

Real-Time Energy-Saving Optimization for Multiple Trains Based on Multiagent Cooperative Control

2017 ◽  
Vol 2607 (1) ◽  
pp. 93-102
Author(s):  
Rui-Fen Zhang ◽  
Wei ShangGuan ◽  
Bai-Gen Cai ◽  
Jian Wang ◽  
Wei Jiang ◽  
...  
Keyword(s):  
Energy Saving ◽  
Real Time ◽  
Cooperative Control ◽  
High Speed ◽  
Optimization Problem ◽  
Operation Strategy ◽  
High Speed Train ◽  
Railway Line ◽  
Train Control ◽  
Train Operation

Nowadays, the energy-saving optimization problem has gradually become a hot spot in the subject of high-speed train control. Traditional static train trajectory planning is designed offline according to a preplanned timetable, but ignored are the uncertainties of parameters because of line conditions and other factors in the process of operation. Thus, the previous operation strategy may not suit the remaining section. The cooperative control strategy for multiple trains was investigated with the aim of conserving energy between successive stations under the constraints of safety and punctuality. First, combined with the train operation strategy under the quasi-moving block system of the Chinese Train Control System, a train cooperative interaction mechanism based on multiagent input is proposed to obtain the real-time running characteristics of trains on the railway via the Radio Block Center (RBC) agent. In the case of unanticipated events of railway line conditions, train operation is often out of accord with the timetable. Therefore, a resilience set related to trip-time deviation and headway variation is introduced to evaluate the robustness of the railway system and achieve balance in the train group. Also, a multigroup parallel differential evolution algorithm is developed to solve the online optimization problem of a high-speed train group according to real-time information. The proposed approach is analyzed by using operational data from the Wuhan–Changsha highspeed railway line in China to assess energy savings and punctuality. Results of the case study show superior performance and effectiveness of the model, and the methodology is illustrated.

Early Warning of Power Plant Equipment Based on Massive Real-Time Data Mining Technology

2014 ◽  
Vol 599-601 ◽  
pp. 1487-1490 ◽  
Author(s):  
Li Kun Zheng ◽  
Kun Feng ◽  
Xiao Qing Xiao ◽  
Wei Qiao Song
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Early Warning ◽  
Time Data ◽  
Mining Technology ◽  
Equipment Safety ◽  
State Evaluation ◽  
Power Plant Equipment ◽  
Real Time Data

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.

Operation-oriented reliability and availability evaluation for onboard high-speed train control system with dynamic Bayesian network

2018 ◽  
Vol 233 (3) ◽  
pp. 455-469 ◽  
Author(s):  
Lei Jiang ◽  
Yiliu Liu ◽  
Xiaomin Wang ◽  
Mary Ann Lundteigen
Keyword(s):  
Control System ◽  
Bayesian Network ◽  
High Speed ◽  
Dynamic Bayesian Network ◽  
Dynamic Bayesian Networks ◽  
High Speed Train ◽  
Train Control ◽  
Train Control System ◽  
Onboard System ◽  
Reliability And Availability

The reliability and availability of the onboard high-speed train control system are important to guarantee operational efficiency and railway safety. Failures occurring in the onboard system may result in serious accidents. In the analysis of the effects of failure, it is significant to consider the operation of an onboard system. This article presents a systemic approach to evaluate the reliability and availability for the onboard system based on dynamic Bayesian network, with taking into account dynamic failure behaviors, imperfect coverage factors, and temporal effects in the operational phase. The case studies are presented and compared for onboard systems with different redundant strategies, that is, the triple modular redundancy, hot spare double dual, and cold spare double dual. Dynamic fault trees of the three kinds of onboard system are constructed and mapped into dynamic Bayesian networks. The forward and backward inferences are conducted not only to evaluate the reliability and availability but also to recognize the vulnerabilities of the onboard systems. A sensitivity analysis is carried out for evaluating the effects of failure rates subject to uncertainties. To improve the reliability and availability, the recovery mechanism should be paid more attention. Finally, the proposed approach is validated with the field data from one railway bureau in China and some industrial impacts are provided.

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