Publications

Detailed Information

Drive-Tolerant Current Residual Variance (DTCRV) for Fault Detection of a Permanent Magnet Synchronous Motor Under Operational Speed and Load Torque Conditions

Cited 6 time in Web of Science Cited 7 time in Scopus
Authors

Park, Chan Hee; Lee, Junmin; Kim, Hyeongmin; Suh, Chaehyun; Youn, Myeongbaek; Shin, Yongjin; Ahn, Sung-Hoon; Youn, Byeng D.

Issue Date
2021-03
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE Access, Vol.9, pp.49055-49068
Abstract
This paper proposes a novel method that uses stator current signals to detect motor faults under operational speed and load torque conditions. Previous studies on motor current signature analysis (MCSA) have been devoted to developing methods to detect faults in non-stationary conditions; however, they have limitations. Conventional methods require much domain knowledge or parameter selection for signal decomposition, and are applicable under limited variable conditions. Thus, this paper proposes a new feature, drive-tolerant current residual variance (DTCRV), for fault detection. This new approach requires no domain knowledge and is applicable under varying speed and load torque conditions. In the proposed method, first, the envelope of the current signal is calculated to extract its modulation. Second, the drive-related signal, which greatly varies based on speed and load torque conditions, is extracted from the enveloped current signal. Third, the drive-tolerant current residual (DTCR) is calculated; the DTCR is defined as the subtraction of the drive-related signal from the enveloped current signal. Finally, the new health feature is calculated as the variance of the DTCR. To demonstrate the proposed method, experimental studies were conducted under several operating conditions (i.e., different speed profiles and load torque levels) with two fault modes: 1) a stator inter-turn short and 2) misalignment. Results confirm the ability of DTCRV to promptly and accurately detect faults in a variety of conditions; in contrast, conventional methods are greatly affected by the operating conditions.
ISSN
2169-3536
URI
https://hdl.handle.net/10371/190530
DOI
https://doi.org/10.1109/ACCESS.2021.3068425
Files in This Item:
There are no files associated with this item.
Appears in Collections:

Altmetrics

Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Share