Reliability analysis on ATP system of CTCS-3 based on D-S evidence inference and Bayesian network

Yang, Jinfeng; Zhang, Youpeng

doi:10.14257/ijca.2016.9.7.06

Cited by 4 publications

(4 citation statements)

References 8 publications

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“…And this paper uses α factor model to quantitatively analyze the common cause failure problem. With the accumulation of fault data, compared with β factor model analysis in the literature, 15 α factor model analysis results are more realistic.…”

Section: Reliability Analysis Of Ctcs-3 On-board Subsystemmentioning

confidence: 99%

“…However, evidence theory can obtain the upper and lower bounds of probability by multi-value mapping method and has the ability to deal with epistemic uncertainty. 13 Some academics 14,15 applied the evidence theory to the risk assessment and reliability analysis of railway signal systems and solved the uncertainty problem caused by incomplete knowledge and other factors. Although the Bayesian network analysis method can describe the uncertainty problem by taking the limit value, the conclusion obtained is conservative, rough and inaccurate.…”

Section: Introductionmentioning

confidence: 99%

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Research on reliability analysis strategy of high-speed train ATP on-board equipment under uncertain information

Zhang

Wang

2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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In view of the incomplete knowledge and lack of data, the system has epistemic uncertainties. This paper uses Bayesian network fusion evidence theory to analyze the reliability of high-speed railway ATP on-board equipment. According to the requirements of safety-critical system reliability analysis, this paper starts with the analysis of system structure and unit module status, comprehensively considering the influence of uncertain information, common cause failure, recovery mechanism, and degraded operation on system reliability. In this paper, with the advantage of the Bayesian network in the description of events in multiple states, evidence theory is used to reason about the system under incomplete information conditions, obtain the availability interval of on-board subsystems and discuss the impact of the degraded operation on system availability. The [Formula: see text] factor model is used to analyze common cause failures, and then the Bayesian network modeling of common cause failures is realized by adding common cause failure nodes. The results show that the method enhances the Bayesian network’s ability to process uncertain information, and the common cause failure data of the train control on-board subsystem is continuously accumulated. The factor model can be used to obtain a more practical common cause failure rate.

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Section: Reliability Analysis Of Ctcs-3 On-board Subsystemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on reliability analysis strategy of high-speed train ATP on-board equipment under uncertain information

Zhang

Wang

2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…Zhang et al [5] studied the reliability analysis of ATP (automatic train protection) system based on dynamic fault tree. Yang et al [6]combined D-S evidence inference and Bayesian networks for reliability assessment of on-board subsystems. He et al [7] realized the reliability analysis of electronic computer interlocking via the reliability block diagram model, which provided a theoretical basis for the regular maintenance of the system.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive evaluation of signal equipment status based on fuzzy synthetic evaluation

Yuan

Qi²,

Sun³

et al. 2022

Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022)

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The signal system is the key content of rail transits, and its equipment status evaluation helps to find the hazards of the system in time and ensure the function of the system. In this paper, a comprehensive evaluation indicator system and evaluation model of signal equipment state are established, and a signal equipment state evaluation method based on fuzzy synthetic evaluation is proposed. The applicability of the method is verified by combining with the case analysis. It is expected to provide reference for the ideas and methods in the whole life cycle management process of rail transits.

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“…1 Previous studies have shown how important reliability analysis is for the safety and maintainability of railway networks. [2][3][4][5] These studies focus on the hardware reliability analysis. However, CTCS-3, comprising an onboard and trackside subsystem, is a large and complex system with many interactive elements.…”

Section: Introductionmentioning

confidence: 99%

Reliability evaluation of the Chinese Train Control System Level 3 using a fuzzy approach

Jiang

Wang

Liu

2018

Proceedings of the Institution of Mechanical Engineers, Part F:

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Application of Dynamic Bayesian network to reliability and availability evaluation of CTCS-3 onboard system Highlights:1. Using DBN-based approach to evaluate the reliability and availability, taking account of dynamic failure behavior, recovery mechanism, and temporal effect. 2. Combining some actual situation and analyzing the hierarchical architecture and field data of CTCS-3 onboard system. 3. Comparing the reliability and availability of three kinds of onboard system and analyzing the degraded state.Findings:1.The CDD, TMR and HDD onboard system possess high reliability and availability. Besides, the low occurrence probabilities of degraded state are almost the same. 2.The VDX, RLU, C3CPU, C2CPU, and Power should be given more attention in physical level. 3.The effects of failure rate on the onboard systems follow the order: WP > TD > KN > PB> LP, and KN> WP> TD > PB> LP for CDD and HDD system, respectively. However, the order is KN>TD>WP > PB> LP for TMR system. 4.The recovery mechanism should be paid more attention to improve the reliability and availability of CTCS-3 onboard system. 5.The results of availability are validated by the field data from one railway bureau.Application of Dynamic Bayesian network to reliability and availability evaluation of CTCS-3 onboard system Abstract This paper presents a systemic approach to evaluate the reliability and availability of Chinese Train Control System Level 3 (CTCS-3) onboard system based on dynamic Bayesian network (DBN), aiming to solve the problems such as dynamic failure behavior, recovery mechanism, and temporal effect. Taking account of the actual operational situation, the hierarchical architecture and field data of the CTCS-3 onboard system is analyzed. Classified by the redundancy strategy of vital computer (VC), three kinds of train control systems corresponding to the triple modular redundancy VC (TMR), hot standby double dual VC (HDD), and cold standby double dual VC (CDD) are presented. By mapping the dynamic fault tree into DBN, the structure and parameter modeling are conducted in a case study. Adopting the forward inference, the results show that the reliability and availability of CDD onboard system are higher than HDD, while TMR is between them. And, the low occurrence probabilities of degraded state are almost the same. Through the backward analysis, the difference between posterior and prior probability shows the VDX, RLU, C3CPU, C2CPU, and Power should be paid more attention. The results of sensitivity analysis demonstrate that the effects of failure rate on the onboard systems follow the order: WP > TD > KN > PB> LP, and KN> WP> TD > PB> LP for CDD and HDD system, respectively. However, the order is KN>TD>WP > PB> LP for TMR system. The recovery mechanism should be paid more attention to improve the reliability and availability of CTCS-3 onboard system. The validation of the proposed approach is demonstrated by the field data from one railway bureau.

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Reliability analysis on ATP system of CTCS-3 based on D-S evidence inference and Bayesian network

Abstract: Abstract

Cited by 4 publications

References 8 publications

Research on reliability analysis strategy of high-speed train ATP on-board equipment under uncertain information

Research on reliability analysis strategy of high-speed train ATP on-board equipment under uncertain information

Comprehensive evaluation of signal equipment status based on fuzzy synthetic evaluation

Reliability evaluation of the Chinese Train Control System Level 3 using a fuzzy approach

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