An Application of Fuzzy Fault Tree Analysis for Reliability Evaluation of Wind Energy System. Issue 6 (2nd November 2022)

• Record Type: Journal Article
• Authors: Akhtar, Iram; Kirmani, Sheeraz
• Is Part Of: IETE journal of research. Volume 68:Issue 6(2022)
• Page Start: 4265
• Page End: 4278
• Publication Date: 2022-11-02
• Subjects: Failure rate reliability -- Fault probability -- Fuzzy fault tree technique -- Fuzzy risk factor -- Wind energy system; Electronics -- Periodicals; Telecommunication -- Periodicals; Electronics; Telecommunication; Periodicals; 621.38
• DOI: 10.1080/03772063.2020.1791741
• Languages: English
• ISSNs: 0377-2063

Abstract

Abstract : In this paper, a fuzzy fault tree analysis technique for reliability evaluation of the wind energy system is presented. The technique combines the operational failures effect and the errors in the fuzzy environment for the wind energy system configuration. In conventional fault tree analysis, the acceptance of the risks probability values is not considered. Besides, it is very difficult to have a precise assessment of the wind system failure rates or the undesired events occurrence probability due to absence of adequate data. Therefore, to overcome these disadvantages, a fault tree analysis based on the fuzzy set theory is presented and applied to the wind energy system. Moreover, if the fault probabilities of the wind energy system fault are not exact values then the fault probabilities are regarded as a fuzzy number and the fuzzy failure rate is known by using fuzzy rules. Also, the fuzzy fault tree analysis is one of the powerful reliability judgment method, which provides the failure modes and its consequences, which are proved on a wind energy system. Furthermore, the risk analysis method is applied based on the fuzzy risk index (FRI) to know the exact impact of every basic event on the top event. Therefore, outcomes show that the fuzzy based fault tree technique combines the probabilities imprecision and engineering inaccuracy are more flexible and adaptive, and it has great use in reliability engineering.