Identification of critical components of wind turbines using FTA over the time

摘要: Abstract Wind energy is currently the most widely implemented renewable source in global scale. Complex industrial multi-MW wind turbines are continuously being installed both onshore and offshore. Projects involving utility-scale require optimisation of reliability, availability, maintainability safety, order to guarantee financial viability large scale projects, particularly offshore, forthcoming years. For this reason, critical turbine components must be identified monitored as cost-effectively, reliably efficiently possible. The condition can qualitatively evaluated through Fault Tree Analysis (FTA). quantitative analysis requires high computational cost. In paper, Binary Decision Diagram (BDD) method proposed for reducing optimise BDD a set ranking methods events has been considered; Level, Top-Down-Left-Right, AND, Depth First Search Breadth-First Search. A approach find general solution (FT) presented. An illustrative case study FT based on different research studies developed. Finally, solved dynamically highlight identification under conditions, employing following heuristic methods: Birnbaum, Criticality, Structural Fussell-Vesely. results provided by methodology allow performance novel maintenance planning from point view.