The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter
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Citations
Cites
Digital Spectral Analysis with Applications.
Porat, B., & Marple, S. L. (1988) · Mathematics of Computation · doi:10.2307/2008605 · Cited by 2,644
Digital Spectral Analysis with Applications
Marple, S. L., & Carey, W. M. (1989) · The Journal of the Acoustical Society of America · doi:10.1121/1.398548 · Cited by 1,984
(2022) · Modern Signal Processing · doi:10.1515/9783110475562-004 · Cited by 996
Wiggins, R. A. (1978) · Geoexploration · doi:10.1016/0016-7142(78)90005-4 · Cited by 960
New criteria for blind deconvolution of nonminimum phase systems (channels)
Shalvi, O., & Weinstein, E. (1990) · IEEE Transactions on Information Theory · doi:10.1109/18.52478 · Cited by 863
Randall, R. B. (1987) · Cited by 481
Self-citationMcFadden, P. D. (1987) · Mechanical Systems and Signal Processing · doi:10.1016/0888-3270(87)90069-0 · Cited by 220
EXTRACTION OF IMPACTING SIGNALS USING BLIND DECONVOLUTION
Lee, J.-Y., & Nandi, A. K. (2000) · Journal of Sound and Vibration · doi:10.1006/jsvi.1999.2778 · Cited by 121
Differential diagnosis of spall versus cracks in the gear tooth fillet region
Endo, H., Randall, R. B., & Gosselin, C. (2004) · Journal of Failure Analysis and Prevention · doi:10.1361/15477020420792 · Cited by 26
Self-citation
Cited by
Rolling element bearing diagnostics—A tutorial
Randall, R. B., & Antoni, J. (2011) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2010.07.017 · Cited by 2,744
Self-citationA summary of fault modelling and predictive health monitoring of rolling element bearings
El-Thalji, I., & Jantunen, E. (2015) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2015.02.008 · Cited by 447
Applications of stochastic resonance to machinery fault detection: A review and tutorial
Qiao, Z., Lei, Y., & Li, N. (2019) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2018.12.032 · Cited by 308
Zhao, M., & Jia, X. (2017) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2017.02.036 · Cited by 304
Improvement of kurtosis-guided-grams via Gini index for bearing fault feature identification
Miao, Y., Zhao, M., & Lin, J. (2017) · Measurement Science and Technology · doi:10.1088/1361-6501/aa8a57 · Cited by 282
Metadata
- Authors
- Endo, H., & Randall, R. B.
- Venue
- Mechanical Systems and Signal Processing
- Publisher
- Elsevier BV
- Published
- 2007-02
- Volume
- 21
- Issue
- 2
- Pages
- 906-919
- ISSN
- 0888-3270 (ISSN-L)
- OpenAlex
- W2033777252
- Cited by
- 434
- References
- 9
- FWCI
- 10.67
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter. https://app.cochat.ai/papers/10.1016/j.ymssp.2006.02.005
- The paper
- Endo, H., & Randall, R. B. (2007). Enhancement of autoregressive model based gear tooth fault detection technique by the use of minimum entropy deconvolution filter. Mechanical Systems and Signal Processing. https://doi.org/10.1016/j.ymssp.2006.02.005
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.
