When judging the health state of mechanical equipment through oil monitoring,it is difficult to select the parameters subjectively,so that the accurate demarcation of wear state is always the bottleneck.This is because the evaluation parameters of wear state are diversified and dynamic in different stages,and the final decision depends on the experience of technicians to a large extent.Therefore,the influence of particle information,pollution degree and lubrication oil product information on the wear state of wind power gearbox was studied,and the wear degree was quantified initially.The significance coefficient of the index is obtained based on denoised data by support vector machine,and then the weight of the parameter is calculated.The key factors is chosen as number of wear particles,mass fraction of ferromagnetic particles,average particle size so that the index of wear degree is simplified to improve the fault diagnosis efficiency of wind power gearbox.