COURSE OVERVIEW

 This practical and highly-interactive course includes various practical sessions and exercises. Theory learnt will be applied using our state-of-the-art simulators. 

 This course is designed to provide participants with a detailed and up-to-date overview of Electrical Motor Current Signature Analysis (MCSA). It covers the importance and applications of MCSA in predictive maintenance; the basic principles, benefits and limitations of MCSA; the basic electric motor principles; the types and characteristics of electric motors; the motor faults, failure modes, motor current signature and their interpretation; and the signal processing techniques, preprocessing techniques for noise reduction, time-domain analysis and frequency-domain analysis. 

 Further, the course will also discuss the relevant features from motor current signatures; the analysis techniques for fault detection and diagnosis; the pattern recognition algorithms for fault classification; the common motor faults and their corresponding current signature patterns; interpreting MCSA results to identify specific motor faults; the relationship between fault types and current signatures; the MCSA equipment and sensors the selection and installation of current sensors; the data acquisition systems for MCSA; and the calibration and verification of MCSA equipment.