Reliability Analysis of Metro Door System Based on Fuzzy Reasoning Petri Net

Liu, Ping; Cheng, Xiaoqing; Qin, Yong; Yuan, Zhang; Xing, Zongyi

doi:10.1007/978-3-642-53751-6_29

Cited by 3 publications

(3 citation statements)

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“…In the last years, many studies have been carried out to analyze the failure occurrence of railway equipment as well as to evaluate the impact of a failure on transportation (see for example [17]). Cheng et al [18] evaluate the reliability of metro door systems using a FMECA procedures. Kim et al [19] investigate the effects of a failure of the brake system for a railroad unit with a FMECA.…”

Section: Literature Reviewmentioning

confidence: 99%

FMECA Assessment for Railway Safety-Critical Systems Investigating a New Risk Threshold Method

et al. 2021

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This paper develops a Failure Mode, Effects and Criticality Analysis (FMECA) for a heating, ventilation and air conditioning (HVAC) system in railway. HVAC is a safety critical system which must ensure emergency ventilation in case of fire and in case of loss of primary ventilation functions. A study of the HVAC's critical areas is mandatory to optimize its reliability and availability and consequently to guarantee a low operation and maintenance cost. The first part of the paper describes the FMECA which is performed and reported to highlight the main criticalities of the HVAC system under analysis. Secondly, the paper deals with the problem of the evaluation of a threshold risk value, which can distinguish negligible and critical failure modes. Literature barely considers the problem of an objective risk threshold estimation. Therefore, a new analytical method based on finite difference is introduced to find a univocal risk threshold value. The method is then tested on two Risk Priority Number datasets related to the same HVAC. The threshold obtained in both cases is a good tradeoff between the risk mitigation and the cost investment for the corrective actions required to mitigate the risk level. Finally, the threshold obtained with the proposed method is compared with the methods available in literature. The comparison shows that the proposed finite difference method is a well-structured technique, with a low computational cost. Furthermore, the proposed approach provides results in line with the literature, but it completely deletes the problem of subjectivity.

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Section: Literature Reviewmentioning

confidence: 99%

FMECA Assessment for Railway Safety-Critical Systems Investigating a New Risk Threshold Method

et al. 2021

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“…In this section, the practicality and flexibility of the proposed q-ROFLRPN model and its reasoning algorithm is demonstrated by an empirical example on the fault diagnosis of metro door system [48]. Door system, as one of the important components of urban railway train system, is complex mechatronic system and its reliability affects the reliability and security of train operation.…”

Section: Case Studymentioning

confidence: 99%

Linguistic Reasoning Petri Nets Using q-Rung Orthopair Fuzzy Linguistic Sets and Weighted Ordered Weighted Averaging Operators

et al. 2019

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Fuzzy Petri nets (FPNs) are an important tool for knowledge representation and reasoning in the rule-based expert system. Recently, various fuzzy sets and linguistic models have been introduced into FPNs to improve its ability in handling imprecise, fuzzy, and linguistic information. However, the existing FPN models still have the following two deficiencies: The first one is the incompatibility of the knowledge representation parameters in modeling the membership degrees of linguistic variables and hesitancy of experts when experts provide linguistic evaluations. Another one is that the reasoning operators in existing reasoning algorithm considering the local weights and ordered weights of propositions fail to guarantee the reasoning result satisfies the monotonicity, boundary, and idempotency. In this paper, we propose the q-rung orthopair fuzzy linguistic reasoning Petri nets (q-ROFLRPNs) by using the q-rung orthopair fuzzy linguistic sets (q-ROFLSs) to enhance the capability of conventional FPNs in dealing with fuzzy and linguistic knowledge. We define new closed operational laws of q-ROFLSs by linguistic scale functions (LSFs), which not only guarantee the validity and reliability of reasoning results but also handle different semantic situations of the linguistic term set. In addition, an enhanced reasoning algorithm based on weighted ordered weighted averaging (WOWA) operator is proposed by considering the weights of propositions themselves and their ordered weights, and the monotonicity, boundary, and idempotency of the results are satisfied. At last, a case study on fault diagnosis for metro door system is provided to demonstrate the effectiveness and advantages of the proposed model. INDEX TERMS Fuzzy Petri net (FPN), knowledge representation, q-rung orthopair fuzzy linguistic set, weighted ordered weighted averaging (WOWA) operator.

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“…But this method is based on historical fault data, and the fault type still needs to be diagnosed manually. Liu et al [14] addressed the shortcomings of the FTA method in the reliability analysis of the subway door. They introduced the Bayesian network (BN) and fuzzy theory to establish the fault probability model of the subway door.…”

Section: Introductionmentioning

confidence: 99%

Fault detection system of subway sliding plug door based on adaptive EMD method

Wang,

Liu,

Lin

et al. 2023

Meas. Sci. Technol.

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With the rapid development of urban rail transit, the safety of subway sliding plug door has become a great concern. To improve the operational reliability of the sliding plug door, we designed a fault detection system based on the adaptive empirical mode decomposition (AEMD). Firstly, to address the impact of noise on signal analysis, the AEMD denoising method is proposed. Intrinsic mode functions (IMFs) are obtained. Then appropriate IMF components are selected for reconstruction according to the adaptive threshold of Hausdorff distance to achieve a better denoising effect. Secondly, this paper uses feature selection methods and machine learning techniques to classify the 12 fault types of the subway sliding plug door. Our proposed method is implemented with a hardware acquisition device and analysis software. The experimental results show that the identification accuracy reaches 98.96% on the practical platform. Practical tests, ablation studies using AEMD, and comparison results prove the effectiveness and robustness of the proposed method.

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Reliability Analysis of Metro Door System Based on Fuzzy Reasoning Petri Net

Cited by 3 publications

References 1 publication

FMECA Assessment for Railway Safety-Critical Systems Investigating a New Risk Threshold Method

FMECA Assessment for Railway Safety-Critical Systems Investigating a New Risk Threshold Method

Linguistic Reasoning Petri Nets Using q-Rung Orthopair Fuzzy Linguistic Sets and Weighted Ordered Weighted Averaging Operators

Fault detection system of subway sliding plug door based on adaptive EMD method

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