Research on Fault Diagnosis of Wind Turbine Mechanical Transmission System Based on Machine Learning
In order to accurately diagnose the faults of the mechanical transmission system of wind tur-bines,a fault diagnosis method of the mechanical transmission system of wind turbines based on machine learning is proposed.The vibration signal of the mechanical transmission system of the wind turbine is de-composed by the EMD method,and the IMF at different frequencies is obtained.After comparative analy-sis,the IMF component that can describe the characteristic frequency of the fault is obtained,and the fault signal is obtained through reconstruction and autocorrelation analysis is used to remove noise from faulty signals.The fault features of the mechanical transmission system of wind turbines are extracted through the Lasso regularized self-encoding neural network in machine learning,and the improved particle swarm algorithm is used to optimize the least squares support vector machine,and a classifier is constructed.The extracted samples are input into the classifier to accomplish fault diagnosis of wind turbine mechanical transmission systems.The experimental test proves that the proposed method can complete the fault diag-nosis and processing with high efficiency and high precision.
machine learningwind turbinesmechanical transmission system fault diagnosisEMD
国家科技期刊平台
NSTL
万方数据
维普
