Detection of Rotor Faults in Brushless DC Motors Operating Under Nonstationary Conditions

Abstract

There are several applications where the motor is operating in continuous nonstationary operating conditions. Actuators and servo motors in the aerospace and transportation industries are examples of this kind of operation. Detection of faults in such applications is, however, challenging because of the need for complex signal processing techniques. Two novel methods using windowed Fourier ridges and Wigner-Ville-based distributions are proposed for the detection of rotor faults in brushless dc motors operating under continuous nonstationarity. Experimental results are presented to validate the concepts and illustrate the ability of the proposed algorithms to track and identify rotor faults. The proposed algorithms are also implemented on a digital signal processor to study their usefulness for commercial implementation