Bearing Damage Detection of BLDC Motors Based on Current Envelope Analysis

Chun-Yao Lee; Yu-Hua Hsieh

doi:10.2478/v10048-012-0040-7

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Bearing Damage Detection of BLDC Motors Based on Current Envelope Analysis

Measurement Science Review

Volume 12 (2012): Issue 6 (December 2012)

By: Chun-Yao Lee and Yu-Hua Hsieh

Open Access

|Dec 2012

Abstract

This paper proposes current envelope analysis (CEA) to analyze bearing fault signals in brushless direct current (BLDC) motors, and back propagation neural networks (BPNN) to automatically identify bearing faults. We made sample motors which contained different types of fault, recorded the current signals, and extracted the current features using CEA and Hilbert Huang transform (HHT) for BPNN fault identification. The results indicate that this approach can efficiently identify bearing faults in BLDC motors.

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Articles in this issue

DOI: https://doi.org/10.2478/v10048-012-0040-7 | Journal eISSN: 1335-8871

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Language: English

Page range: 290 - 295

Published on: Dec 15, 2012

Published by: Slovak Academy of Sciences, Institute of Measurement Science

In partnership with: Paradigm Publishing Services

Publication frequency: Volume open

Keywords:

Current envelope analysis,

back propagation neural networks,

Hilbert Huang transform

Related subjects:

Engineering,

Electrical engineering,

Control engineering, metrology and testing

© 2012 Chun-Yao Lee, Yu-Hua Hsieh, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons License.

Volume 12 (2012): Issue 6 (December 2012)