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

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

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 diagnos...

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Bibliographic Details
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
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Institution: Singapore Management University
Language: Chinese
Description
Summary: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.

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