Multi-sensor signal fusion technology-based fault diagnosis method for wind turbine blades

Abstract

The invention discloses a multi-sensor signal fusion technology-based fault diagnosis method for wind turbine blades. According to the method, the problems of lack of fault information and the like caused by the insufficiency of sensors is solved by adopting a plurality of sensors. An independent classifier is used for performing primary diagnosis on information acquired by each sensor, so as to determine the possibility that to-be-diagnosed faults belong to different faults; and the decision fusion diagnosis is performed by adopting a fuzzy integral fusion technology based on that the importance degree of information output by each classifier is adequately considered. According to the fault diagnosis method disclosed by the invention, classified results of all the classifiers are integrated, and the importance degree of each classifier is considered, thus effectively improving the accuracy of the fault diagnosis on the wind turbine blades.

Description

technical field [0001] The invention belongs to the technical field of on-line monitoring and fault diagnosis, in particular to a method for fault diagnosis of wind turbine blades based on multi-sensor signal fusion technology. Background technique [0002] In recent years, due to the shortage of resources and the deterioration of the environment, countries around the world have begun to pay attention to the development and utilization of renewable and emission-free energy. As a green and environment-friendly resource, wind power has been paid more and more attention by people. On a global scale, a large number of wind turbines have been put into production, making the safe and stable operation of wind turbines arouse people's attention. Since wind turbines work in harsh environments such as the field, exposure, and thunderstorms for a long time, the wind conditions in the wind field are complex and changeable, which can easily cause various faults. Therefore, online monito...

AI Technical Summary

Problems solved by technology

The Bayesian method requires prior information, which is often difficult to obtain in practical applications; and the elements of the decision set are required to be independent of each other, which is too harsh

The D-S Evidence Reasoning Act requires that the evidence used must be independent of each other, which is generally difficult to meet. In addition, there will be combination explosions, event conflicts, etc.

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