Fault Detection in Induction Motors

This chapter introduces recent developments in fault diagnostics of induction motors (IMs), by providing theoretical, simulative, and experimental results along with a number of implementation-related practical considerations and guidelines. The first section of the chapter is a short introduction in which the more common faults of IM are concisely described as well as their causes, consequences, and symptoms. The second section introduces an example of model-based approach for fault detection and isolation (FDI) in IMs based on dynamical observers. The remaining sections deal with diagnostic techniques based on signal analysis approaches. The techniques include classical motor current signature analysis (MCSA) based on the fast Fourier transform (FFT), Hilbert-transform (HT), discrete wavelet transform (DWT), continuous wavelet transform (CWT), Wigner-Ville distribution (WVD) approach, and instantaneous frequency (IF) approach