Diagnosis strategy for complex systems based on reliability analysis and MADM under epistemic uncertainty

Duan, Rongxing; Zhou, Huilin; Jiang, Fan

doi:10.17531/ein.2015.3.4

Cited by 11 publications

(9 citation statements)

References 18 publications

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“…However, it is usually difficult to determine the corresponding membership function of each language value, and this diagnosis algorithm was also a single attribute decision making problem. To overcome these limitations, multiple attributes decision-making was used in [7,20]. However, these methods usually used the attributes with defined values and could not make decisions under uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Dynamic diagnostic strategy based on reliability analysis and distance-based VIKOR with heterogeneous information

Li¹,

Duan²

2018

Eksploatacja i Niezawodność – Maintenance and Reliability

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This paper presents a dynamic diagnostic strategy based on reliability analysis and distance-based VIKOR with heterogeneous information. Specifically, the proposed method uses a dynamic fault tree (DFT) to describe the dynamic fault characteristics and evaluates the failure rate of components using interval numbers to deal with the epistemic uncertainty. Furthermore, DFT is mapped into a dynamic evidential network (DEN) to calculate some reliability parameters and these parameters together with test cost constitute a decision matrix. In addition, a dynamic diagnostic strategy is developed based on an improved VIKOR algorithm and the previous diagnosis result. This diagnosis algorithm determines the weights of attributes based on the Entropy concept to avoid experts' subjectivity and obtains the optimal ranking directly on the original heterogeneous information without a transformation process, which can improve diagnosis efficiency and reduce information loss. Finally, the performance of the proposed method is evaluated by applying it to a train-ground wireless communication system. The results of simulation analysis show the feasibility and effectiveness of this methodology.

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Section: Introductionmentioning

confidence: 99%

Dynamic diagnostic strategy based on reliability analysis and distance-based VIKOR with heterogeneous information

Li¹,

Duan²

2018

Eksploatacja i Niezawodność – Maintenance and Reliability

Self Cite

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“…Besides, all the diagnosis algorithms are, in essence, single attribute decision-making. Although multiple attribute decision-making was used in [21,22], both methods failed to incorporate sensors data and update the reliability results to optimize the diagnosis process using the previous diagnosis results.…”

Section: Journal Of Sensorsmentioning

confidence: 99%

Dynamic Diagnosis Strategy for Redundant Systems Based on Reliability Analysis and Sensors under Epistemic Uncertainty

Duan

Jiang

2015

Journal of Sensors

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Fault tolerant technology is often used to improve systems reliability. However, high reliability makes it difficult to get sufficient fault samples, resulting in epistemic uncertainty, which increases significantly challenges in these systems diagnosis. A novel dynamic diagnosis strategy for complex systems is proposed to improve the diagnostic efficiency in the paper, which makes full use of dynamic fault tree, Bayesian networks (BN), fuzzy sets theory, and TOPSIS. Specifically, it uses a dynamic fault tree to model dynamic fault modes and evaluates the failure rates of the basic events using fuzzy sets to deal with epistemic uncertainty. Furthermore, it generates qualitative structure information based on zero-suppressed binary decision diagrams and calculates quantitative parameters provided by reliability analysis using a hybrid approach. Additionally, sensors data are incorporated to update the qualitative information and quantitative parameters. Qualitative information, quantitative parameters, and previous diagnosis result are taken into account to design a new dynamic diagnosis strategy which can locate the fault at the lowest cost. Finally, a case study is given to verify the developed approach and to demonstrate its effectiveness.

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“…Besides, the algorithm considers only the single data type of crisp value. Reference [26] presents a dynamic fault diagnosis method based on DFT and Bayesian network. Firstly, a DFT is used to construct a system fault model, and then the fuzzy sets and domain experts are used to obtain the fuzzy failure rate of components.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis Strategy for Complex Systems Based on Multi-Source Heterogeneous Information Under Epistemic Uncertainty

Huang

Duan

et al. 2020

IEEE Access

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Technological innovation in modern systems has significantly improved their performance. However, fault characteristics such as epistemic uncertainty and dynamic failure modes often occur when these systems break down, which greatly raises some new challenges in fault diagnosis. A new fault diagnosis strategy for complex systems is presented based on multi-source heterogeneous information considering epistemic uncertainty in this paper. Specifically, in view of the epistemic uncertainty, the failure distribution parameters of basic events are described with interval numbers and test cost of these events are evaluated using domain experts and intuitionistic fuzzy linguistic set; Aiming at the problem of dynamic failure modes, a dynamic fault tree (DFT) is used to establish the dynamic failure model and is converted into a dynamic evidential network to calculate some reliability parameters; Furthermore, a diagnostic decision table is constructed based on multi-attribute heterogeneous information such as test cost and some reliability results; Finally, a novel fault diagnosis strategy is designed based on distance-based VIKOR algorithm, which can provide some decision support for fault diagnosis and locate the fault as quickly as possible.

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Diagnosis strategy for complex systems based on reliability analysis and MADM under epistemic uncertainty

Cited by 11 publications

References 18 publications

Dynamic diagnostic strategy based on reliability analysis and distance-based VIKOR with heterogeneous information

Dynamic diagnostic strategy based on reliability analysis and distance-based VIKOR with heterogeneous information

Dynamic Diagnosis Strategy for Redundant Systems Based on Reliability Analysis and Sensors under Epistemic Uncertainty

Fault Diagnosis Strategy for Complex Systems Based on Multi-Source Heterogeneous Information Under Epistemic Uncertainty

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