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Multi-sensor Wireless System for Fault Detection in Induction Motors


This research presents a stand-alone multi-sensor wireless system for continuous real-time performance and condition monitoring of induction motors. The proposed wireless system provides a low-cost alternative to expensive condition monitoring technology available through dedicated current signature analysis or vibration monitoring equipment. The system employs multiple sensors (acoustic, vibration and current) mounted on a common wireless platform. The faults of interest are static and dynamic air-gap eccentricity and bearing damage.

The Hilbert-Huang Transform (HHT) of vibration data and power spectral density (PSD) of current and acoustic signals are used as the features in a hierarchical classifier. The proposed wireless system can distinguish a faulty motor from a healthy motor with a probability of 99.9% of correct detection and less than 0.1%

likelihood of false alarm. It can also discriminate between dierent fault categories and severity with an average accuracy of 95%.

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