Design of support vector machine classifier for broken bar detection

This paper proposes method for broken bar detection in induction motors at very low slip. The proposed method consists of extracting reliable discriminative feature from a steady state one-phase current signal and design of optimal classifier via a support vector machine. The fault related features are extracted from frequency spectra of a modulus of a motor phase current Hilbert transform series. The features are fed to the support vector machine input and the output indicates rotor condition in respect of broken bar appearance independently of a slip value. Tests are conducted on 1.1kW two poles induction machine in an industrial environment. It is shown that proposed method is accurate, fast, reliable, not hardware costly.