Fuzzy synthetic condition assessment of wind turbine based on combination weighting and cloud model

Kai Zheng, Lina Han, Shuli Guo*, Zhenyu Wang, Xinmiao Zhang, Xinghui Dong

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

This paper presented an improved fuzzy synthetic model based on combination weighting and a cloud model to optimize wind turbine maintenance strategy and improve operational reliability. First, a condition assessment framework was proposed by analyzing the monitored physical quantities of a working wind turbine. Based on the establishment of a state health evaluation index and health status classification of wind turbines, the weight of each index was determined with a combination weighting method while the membership degree of each state grade was determined with a membership cloud model. A comprehensive evaluation of the health status of the wind turbine was carried out using the method of stratified evaluation. The results showed that the proposed method was effective and feasible. The results also showed that the condition assessment that utilized the improved method predicted the change of operating conditions and more closely matched real operating conditions than the traditional fuzzy assessment method.

Original languageEnglish
Pages (from-to)4563-4572
Number of pages10
JournalJournal of Intelligent and Fuzzy Systems
Volume32
Issue number6
DOIs
Publication statusPublished - 2017

Keywords

  • Wind turbine
  • cloud model
  • combination weighting
  • condition assessment
  • fuzzy synthetic

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