Electric Fault Diagnosis in induction Machines using Motor Current Signature Analysis (MCSA)

Abstract

Electric fault diagnosis is an important subject for ensuring the operational efficiency and reliability of induction machines, which are widely used in the industrial sector. Motor current signature analysis (MCSA) is an effective, non-invasive technique that has been useful for diagnosing faults in these machines. MCSA is applied on the acquired stator currents during the induction machine operation to detect and identify specific characteristics related to distinct faulty conditions. In this work, different methodologies for electric current analysis as instantaneous space phasor (ISP) module, spectral examination through Fourier transform, multiresolution inspection utilizing wavelet transform, and current phasor observation with fuzzy logic, are proposed for detecting and classifying short-circuit faults among coils of a stator winding in an induction motor, which has been modified to induce short-circuit faults with different severity degrees on its windings.