Prediction of Remaining Life of Gearbox Bearings for Industrial Heating Furnace Transmission
The transmission gearbox of industrial heating furnaces undertakes important work tasks,such as transmitting and regulating power,and bearing relatively large loads.In order to ensure the stability and reliability of gearbox bearings,it is necessary to predict the remaining life of the bearings and timely detect the health status of the bearings,in order to avoid equipment failures caused by bearing failure.To this end,a method for predicting the remaining life of bearings in industrial heating furnace transmission gearbox is studied.Based on the charac-teristics of continuity and independent decay in the remaining lifespan per unit time,the density of bearing features in different states following gamma is calculated.The maximum likelihood estimation method is combined with time and space to obtain the probability of bearing state transition,and the feature increment value is obtained as a reference for subsequent prediction conditions.Establish a prediction model based on grey theory to describe the regular changes in the eigenvalues index of the predicted sequence,calculate the time interval for each bearing state update,calculate the grey action value after the cumulative addition of the same time interval through a first-order linear differential equa-tion,and use the minimum two product algorithm to solve the residual gray residual of the original sequence and the predicted sequence,a-chieving effective bearing residual life prediction.Experimental data shows that the proposed method can achieve high-quality prediction for different states of gearbox bearings,and has certain practical value.
industrial heating furnacetransmission gearbox bearingsresidual life predictiongamma distribution function
万方数据
维普
