The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
Motor Fault Diagnostics Based on Current Signatures: A Review
Abstract
Electric motors act as the backbone of industrial development. Their reliable and safe operation is essential to various industries. At present, motor fault diagnosis based on current signatures has progressively gained favour thanks to their non-invasive nature. This review summarizes recent advances in motor current signature analysis for fault diagnosis. First, motor diagnostic background and requirements are expounded, as well as the benefits of current signature analysis. Then, the mechanism and influence of common faults for the most widely used induction motor and permanent magnet synchronous motor are analyzed, and the detection criteria for typical motor defects, such as bearing fault, stator windings inter turn short circuit, and broken rotor bar, are summarized. Next, the motor diagnosis techniques based on current signature analysis are summarized from the technical perspectives of spectrum analysis, demodulation transformation, time-frequency analysis, parameter estimation, artificial intelligence, and etc. Pros and cons of each technology are also provided. Finally, according to the challenges faced by the existing technologies in engineering, future research is suggested to focus on influence analysis of electromechanical coupling on current signal, feature extraction for incipient fault, non-stationary signal analysis, unlabeled data utilization and fault severity assessment.
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Cites
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
Ince, T., Kiranyaz, S., Eren, L., Askar, M., & Gabbouj, M. (2016) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2016.2582729 · Cited by 1,407
The local mean decomposition and its application to EEG perception data
Smith, J. S. (2005) · Journal of The Royal Society Interface · doi:10.1098/rsif.2005.0058 · Cited by 983
Gangsar, P., & Tiwari, R. (2020) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2020.106908 · Cited by 605
Cause and analysis of stator and rotor failures in three-phase squirrel-cage induction motors
Bonnett, A. H., & Soukup, G. C. (1992) · IEEE Transactions on Industry Applications · doi:10.1109/28.148460 · Cited by 593
Noninvasive detection of broken rotor bars in operating induction motors
Kliman, G. B., Koegl, R. A., Stein, J., Endicott, R. D., & Madden, M. W. (1988) · IEEE Transactions on Energy Conversion · doi:10.1109/60.9364 · Cited by 525
Grubic, S., Aller, J. M., Lu, B., & Habetler, T. G. (2008) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2008.2004665 · Cited by 490
The detection of inter-turn short circuits in the stator windings of operating motors
Joksimovic, G. M., & Penman, J. (2000) · IEEE Transactions on Industrial Electronics · doi:10.1109/41.873216 · Cited by 471
DCNN-Based Multi-Signal Induction Motor Fault Diagnosis
Shao, S., Yan, R., Lu, Y., Wang, P., & Gao, R. X. (2020) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2019.2925247 · Cited by 442
Immovilli, F., Bellini, A., Rubini, R., & Tassoni, C. (2010) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2010.2049623 · Cited by 382
A Motor Current Signal-Based Bearing Fault Diagnosis Using Deep Learning and Information Fusion
Hoang, D. T., & Kang, H. J. (2020) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2019.2933119 · Cited by 378
Cited by
Harmonic Distortion Indices for Experimental Characterization of Variable Frequency Drives
Arranz-Gimon, A., Morinigo-Sotelo, D., Zorita-Lamadrid, A., & Duque-Perez, O. (2024) · IEEE Access · doi:10.1109/access.2024.3474176 · Cited by 5
Metadata
- Authors
- Niu, G., Dong, X., & Chen, Y.
- Venue
- IEEE Transactions on Instrumentation and Measurement
- Published
- 2023
- Volume
- 72
- Pages
- 1-19
- ISSN
- 0018-9456 (ISSN-L)
- 1557-9662
- OpenAlex
- W4380635141
- Cited by
- 269
- References
- 64
- FWCI
- 29.25
- Type
- journal article
- Language
- en
- Open access
- closed
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