학술논문

Study on the Intelligent Fault Recognition Algorithm for Wind Power Unit Drivetrain
Document Type
article
Source
Jixie chuandong, Vol 42, Pp 164-167 (2018)
Subject
Wind power unit
Drivetrain
Fault diagnosis
Support vector machine
Quantum genetic algorithm
Mechanical engineering and machinery
TJ1-1570
Language
Chinese
ISSN
1004-2539
Abstract
In order to improve reliability of wind power unit drivetrain,a fault diagnosis model based on quantum genetic algorithm and support vector machine( SVM) is presented. The model of SVM is conformed,and the penalty parameter and Kernel function coefficient are optimized by quantum genetic algorithm,which coding and renewal of initial population are completed with quantum encoding and rotation gate,the accuracy of optimal solution is improved. Through using the optimized SVM model,with the test and calculation for drivetrain in three types of normal condition,surface wear and missing teeth,the accuracy rate of fault diagnosis can be effectively solved.