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Fault Diagnosis in Industrial Induction Machines Through Discrete Wavelet Transform
Open accessAbstract
This paper deals with fault diagnosis of induction machines based on the discrete wavelet transform. By using the wavelet decomposition, the information on the health of a system can be extracted from a signal over a wide range of frequencies. This analysis is performed in both time and frequency domains. The Daubechies wavelet is selected for the analysis of the stator current. Wavelet components appear to be useful for detecting different electrical faults. In this paper, we will study the problem of broken rotor bars, end-ring segment, and loss of stator phase during operation.
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Cited by
Data-based techniques focused on modern industry: An overview
Yin, S., Li, X., Gao, H., & Kaynak, O. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2308133 · Cited by 1,025
Leite, V. C. M. N., Borges da Silva, J. G., Veloso, G. F. C., Borges da Silva, L. E., Lambert-Torres, G., Bonaldi, E. L., & de Lacerda de Oliveira, L. E. (2015) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2014.2345330 · Cited by 274
Ali, Z., Terriche, Y., Hoang, L. Q. N., Abbas, S. Z., Hassan, M. A., Sadiq, M., Su, C.-L., & Guerrero, J. M. (2021) · IEEE Access · doi:10.1109/access.2021.3112383 · Cited by 104
Van, M., & Kang, H.-J. (2016) · Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science · doi:10.1177/0954406215573976 · Cited by 46
Hang, J., Zhang, J., Cheng, M., & Wang, Z. (2013) · 2013 IEEE Energy Conversion Congress and Exposition · doi:10.1109/ecce.2013.6647169 · Cited by 36
Metadata
- Authors
- Bouzida, A., Touhami, O., Ibtiouen, R., Belouchrani, A., Fadel, M., & Rezzoug, A.
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2011-09
- Volume
- 58
- Issue
- 9
- Pages
- 4385-4395
- ISSN
- 0278-0046 (ISSN-L)
- 1557-9948
- OpenAlex
- W2125669699
- Cited by
- 325
- References
- 0
- FWCI
- 26.55
- Type
- journal article
- Language
- en
- Open access
- green
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- Bouzida, A., Touhami, O., Ibtiouen, R., Belouchrani, A., Fadel, M., & Rezzoug, A. (2011). Fault Diagnosis in Industrial Induction Machines Through Discrete Wavelet Transform. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2010.2095391
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
