Current Frequency Spectral Subtraction and Its Contribution to Induction Machines' Bearings Condition Monitoring

Induction machines are widely used in industrial applications. Safety, reliability, efficiency, and performance are major concerns that direct the research activities in the field of electrical machines. Even though the induction machine is very reliable, many failures can occur such as bearing faults, air-gap eccentricity, and broken rotor bars. The challenge is, therefore, to detect them at an early stage in order to prevent breakdowns. In particular, stator current-based condition monitoring is an extensively investigated field for cost and maintenance savings. In this context, this paper deals with the assessment of a new stator current-based fault detection approach. Indeed, it is proposed to monitor induction machine bearings by means of stator current spectral subtraction, which is performed using short-time Fourier transform or discrete wavelet transform. In addition, diagnosis index based on the subtraction residue energy is proposed. The proposed bearing faults condition monitoring approach is assessed using simulations, issued from a coupled electromagnetic circuits approach-based simulation tool, and experiments on a 0.75-kW induction machine test bed.