Early fault diagnosis of rolling bearings based on signal reconstruction through SDD-SVD and FWEO

An approach based on the singular spectrum decomposition (SSD)-singular value (SVD) and frequency weight energy operator (FWEO) was proposed for early fault diagnosis of rolling bearings. Since interference heavy noise in stage bearing fault, SSD could eliminate abundant noise, meanwhile adaptively decompose nonlinear, non-stationary signals into multiple mono-components which had distinct physical meanings. Subsequently, SVD adopted de-noising every because distributed throughout domain. In following, signal reconstruction performed selected with de-noising. Finally, FWEO employed envelop analysis is realized. Two groups experiment data concerning were investigated to valid effectiveness method, good identification effects obtained.