A New Modeling Method for Fault Prediction of Wind Turbine Gearbox Based on Partial Least Squares Regression Analysis

Abstract

The oil of wind turbine gearbox contains a lot of information related to wear state. Through the real-time monitoring of oil abrasive particle concentration, moisture, viscosity, density, temperature, acid value, dielectric constant and other parameters, we can get the relevant information about gearbox wear state. Thus, a modeling method of wind turbine gearbox fault prediction based on partial least squares regression analysis is proposed. This modeling method can establish the regression analysis between wear state and key oil parameters, which provides a scientific basis for fault prediction of fan gearbox and has broad application prospects.