The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Rolling element bearing fault diagnosis using wavelet transform
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Cites
Neural Networks: A Comprehensive Foundation
Haykin, S. (1998) · Cited by 30,070
Data Mining: Practical Machine Learning Tools and Techniques
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An Introduction to Support Vector Machines
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The support vector machine under test
Meyer, D., Leisch, F., & Hornik, K. (2003) · Neurocomputing · doi:10.1016/s0925-2312(03)00431-4 · Cited by 777
SAMANTA, B., & AL-BALUSHI, K. R. (2003) · Mechanical Systems and Signal Processing · doi:10.1006/mssp.2001.1462 · Cited by 760
Fault diagnosis of ball bearings using machine learning methods
Kankar, P. K., Sharma, S. C., & Harsha, S. P. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2010.07.119 · Cited by 497
Self-citationRolling element bearing fault diagnosis using wavelet packets
Nikolaou, N. G., & Antoniadis, I. A. (2002) · NDT & E International · doi:10.1016/s0963-8695(01)00044-5 · Cited by 377
Intelligent condition monitoring of a gearbox using artificial neural network
Rafiee, J., Arvani, F., Harifi, A., & Sadeghi, M. H. (2007) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2006.08.005 · Cited by 330
Paya, B. A., Esat, I. I., & Badi, M. N. M. (1997) · Mechanical Systems and Signal Processing · doi:10.1006/mssp.1997.0090 · Cited by 327
Application of discrete wavelet transform for detection of ball bearing race faults
Prabhakar, S., Mohanty, A. R., & Sekhar, A. S. (2002) · Tribology International · doi:10.1016/s0301-679x(02)00063-4 · Cited by 307
Cited by
Wavelets for fault diagnosis of rotary machines: A review with applications
Yan, R., Gao, R. X., & Chen, X. (2014) · Signal Processing · doi:10.1016/j.sigpro.2013.04.015 · Cited by 1,446
A novel intelligent diagnosis method using optimal LS-SVM with improved PSO algorithm
Deng, W., Yao, R., Zhao, H., Yang, X., & Li, G. (2019) · Soft Computing · doi:10.1007/s00500-017-2940-9 · Cited by 490
Tran, M.-Q., Elsisi, M., Mahmoud, K., Liu, M.-K., Lehtonen, M., & Darwish, M. M. F. (2021) · IEEE Access · doi:10.1109/access.2021.3105297 · Cited by 158
Comparison of FDA-based and PCA-based features in fault diagnosis of automobile gearboxes
Gharavian, M. H., Almas Ganj, F., Ohadi, A. R., & Heidari Bafroui, H. (2013) · Neurocomputing · doi:10.1016/j.neucom.2013.04.033 · Cited by 62
Metadata
- Authors
- Kankar, P. K., Sharma, S. C., & Harsha, S. P.
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2011-05
- Volume
- 74
- Issue
- 10
- Pages
- 1638-1645
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W2012120314
- Cited by
- 278
- References
- 23
- FWCI
- 19.92
- Type
- journal article
- Language
- en
- Open access
- closed
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- Kankar, P. K., Sharma, S. C., & Harsha, S. P. (2011). Rolling element bearing fault diagnosis using wavelet transform. Neurocomputing. https://doi.org/10.1016/j.neucom.2011.01.021
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
