Health state prognostics of complicate equipments based on M-DSSE and RVM

Aiming at the health state prognostics problem of complicated equipments,of which the fault shows gradual failure,a new prognostics method based on the multiple features extraction was presented compounding multiple distance and shape similarity(M-DSSE)and relevance vector machine(RVM).The M-DSSE method was developed to evaluate the health index of equipments and the RVM regressive model was used to predict the performance trend based on the health index information,which greatly supported the predictive maintenance.The application on a certain aerial electromechanical device suggests the approach is capable to solve the health state prognostics problem of complicated equipments,and the results are consistent with the practical situation.