<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

Bearing Damage Detection of BLDC Motors Based on Current Envelope Analysis

Department of Electrical Engineering, Chung Yuan Christian University, Taoyuan County, 32023, Taiwan

Measurement Science Review

{"article-title":"Bearing Damage Detection of BLDC Motors Based on Current Envelope Analysis"}

This paper proposes current envelope analysis (CEA) to analyze bearing fault signals in brushless direct current (BLDC) motors, and back propagation neural...

Bearing Damage Detection of BLDC Motors Based on Current Envelope Analysis

Data publikacji: 15 gru 2012

Zakres stron: 290 - 295

DOI: https://doi.org/10.2478/v10048-012-0040-7

Słowa kluczowe
Current envelope analysis, back propagation neural networks, Hilbert Huang transform

This content is open access.

Bearing Damage Detection of BLDC Motors Based on Current Envelope Analysis

Data publikacji: 15 gru 2012

Zakres stron: 290 - 295

DOI: https://doi.org/10.2478/v10048-012-0040-7

Słowa kluczoweCurrent envelope analysis, back propagation neural networks, Hilbert Huang transform

This content is open access.

Słowa kluczowe
Current envelope analysis, back propagation neural networks, Hilbert Huang transform