Intelligent diagnosis method for failure of wind generating set

Abstract

The invention discloses an intelligent diagnosis method for the failure of a wind generating set. The diagnosis method includes the steps that first, according to historical failure knowledge information of the wind generating set, a failure tree model of the wind generating set is established; then according to the structure of the failure tree model, a probability neural network structure modelis established, and historical failure sample data of the wind generating set are mapped into failure mode space to form a failure diagnosis network model with high fault tolerance and adaptive ability; finally, the failure data is input into the established failure diagnosis network model to obtain a diagnosis result, a failure mode is output and then matched with a corresponding failure tree branch, leaf nodes governed by the failure tree branch are positioned, and namely reasons or reason combinations leading to the failure are found out. Based on a failure tree and a probability neural network, intelligent diagnosis is performed on the multi-form failure of the wind generating set, multi-failure diagnosis analysis is performed on complex failures of the wind generating set under incomplete information, and failure reasons are accurately positioned.

Description

technical field [0001] The invention relates to the technical field of fault diagnosis of wind turbines, in particular to an intelligent fault diagnosis method for wind turbines based on fault trees and probabilistic neural networks. Background technique [0002] While my country's wind power industry is booming, it is facing the situation of frequent unit failures. However, in the case of wind turbine failures, the existing solutions still remain after the failure occurs, relying on manual experience to diagnose and analyze the operating status information of equipment failures, but For a complex system such as a wind turbine, the causes of certain faults are strongly coupled, so how to quickly screen the fault causes, and systematically and comprehensively diagnose and locate the cause of the fault is particularly important. [0003] In order to improve the reliability and intelligent level of fault diagnosis, people began to study various intelligent fault diagnosis method...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a fault intelligent diagnosis method for wind turbines, so that it can realize accurate and reliable fault intelligent diagnosis for multi-state faults of wind turbines, thereby overcoming the shortcomings of existing fault diagnosis methods

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