Application of fast independent component analysis in fault detection of induction motors

• Main Authors: Xu, W., Hao, F. F., Hao, Q., Li, N. N., Yang, T., WANG, Zhaoxia
• Format: text
• Language: Chinese
• Published: Institutional Knowledge at Singapore Management University 2009
• Subjects: FastICA; Fault diagnosis; Feature extraction; Artificial Intelligence and Robotics; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/5640
• Institution: Singapore Management University

The stator currents of AC induction motors are measured and the stator currents obtained from normal motors and faulty motors are analyzed and compared. The technique of fast independent component analysis (Fast ICA) is used for extracting the dominating features from the measured signals to diagnose the fault of induction motors. The experimental results demonstrate that FastICA method can be well applicable for detecting fault of induction motors.