Because the fault signal of the motor bearing has nonlinear and non-stationary characteristics, it is difficult to extract the fault signal feature and make the fault diagnosis. This paper puts forward a complete set of empirical mode decomposition based on adaptive add white noise improvement and support vector machine with its fault diagnosis method. The four types of signals of the motor bearing normal operation, rolling needle fault, outer and inner race faults measured by Case Western Reserve University are decomposed by CEEMDAN and EEMD to get multiple mode component, and then the featur...
