Abstract:  The traditional life prediction of rolling bearings needed to carry out the whole life test, and a large number of test data needed to be processed by mathematical or physical models. Aiming at this problem, a nonequal interval grey prediction method for the remaining life of rolling bearings based on zero-failure data was proposed. First of all, using the zero-failure data model of rolling bearing and E-Bayes theory, the reliability estimation value of rolling bearing at each censoring time was calculated. Then, the reliability estimation value calculated by each censoring time of rolling bearing was transformed by equal interval. Taking the transformed reliability estimation value as the reference sequence, the grey prediction model GM ( 1,1 ) was used to predict the remaining life of rolling bearing. Finally, the proposed method was applied to the zero-failure data of rolling bearings obtained from the timing censoring test, and the predicted results were comparing with the E-Bayes calculated values. The results show that, comparing with the E-Bayes calculation value, the prediction residual and relative error of this method can be controlled within 3 % by the non-equidistant grey prediction method, which has high prediction accuracy. The method can provide a new idea for the accurate prediction of the remaining life of rolling bearings.

Key words:  rolling bearings residual life; whole life test;reliability estimation value of bearings;zero-failure data; unequal interval; grey prediction