An HMM-based semi-nonparametric approach for fault diagnostics in rotary electric motors

In this paper¹, a semi-nonparametric approach based on hidden Markov model (HMM) is introduced for fault diagnostics in the rotary electric motors. The introduced approach uses multiple HMMs to capture various underlying trends for each probable fault in the electric motors. In this work, only two major faults in the rotary motors, namely, bearing faults and unbalanced rotor are tried to be distinguished from the health condition. The experimental results are provided for single HMM for each fault, multi HMMs for each fault and multi-HMMs using semi-non parametric approach to recognize the faults.