IGBT fault detection for three phase motor drives using neural networks

• Main Authors: Alavi, Marjan, Luo, Ming, Wang, Danwei, Bai, Haonan
• Other Authors: School of Electrical and Electronic Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/102805; http://hdl.handle.net/10220/16439
• Institution: Nanyang Technological University

Motor drives are widely used in industry for controlling the speed of three phase AC motors. Faults in motor drives degrade motor performance and can cause catastrophic failures. IGBT (Insulated Gate Bipolar Transistor) switch faults are one of the main roots of electrical faults in inverters and motor drives. In this paper, a method based on neural network is implemented to detect and isolate switch faults in a three phase voltage source inverter. Only the output signals of the inverter are monitored. The entropy of the phase current and voltage is selected as the switch fault feature. Single and multiple short and open circuit switch faults are isolable with this method.