Condition Monitoring of Electrical Machines

The course includes the need for condition monitoring. Three main subdivisions of the course are types of fault and their symptoms, diagnostic methods to identify these faults and a deep signal processing analysis for fault diagnosis. The various components prone to fault are stator, rotor, shaft, gear box, bearing etc. The diagnosis methods includes diagnosis based on temperature, infrared signal, vibration, noise, motor current signature analysis etc. various signal processing techniques such as fuzzy logic, neural network from fault diagnosis point of view are also included in this course.