Aimed at the problems of abnormal wear caused by poor lubrication during the operation of the main gearbox of wind turbines,partial least square regression analysis(PLS)was proposed to process oil monitoring data,and the grey equidimensional grading model was used for fault prediction and diagnosis.Through the data initialization and principal component extraction of kinematic viscosity,acid value and the content of copper,silicon,zinc,phosphorus and iron elements in the oil monitoring data,the PLS model was constructed and the data fitting analysis was carried out.The results indicate that the linear regression equation fitted by the PLS method can accurately predict the abnormal wear element content in the gear box.Using the grey equidimensional grading model to predict the data and PLS model for diagnostic analysis,the change trend of Fe content in the future can be obtained,which can provide the basis for formulating the gearbox maintenance strategy.