Study and Analysis of Bearing Temperature Prediction Model of Mechanical Equipment
This paper makes a survey and summary of the abnormal temperature change alarm model of industrial equipment,and the machine learning algorithm plays an important role in the process of temperature prediction and fault diagnosis.Based on the analysis of the temperature sample of high-speed bearing operation process,comparing the prediction error of linear regression model and GM(1,1)model,we found that the temperature change prediction of GM(1,1)model during the operation of mechanical equipment is more accurate than that of the linear regression model,and the model accuracy reached 99.59％.This paper has some reference significance for the early warning of abnormal temperature change in the operation process of mechanical equipment components.
mechanical equipmentgray predictionlinear regressionabnormal high temperature prediction
万方数据
维普
