The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Reconstruction-based contribution for process monitoring
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Citations
Cites
Process fault detection based on modeling and estimation methods—A survey
Isermann, R. (1984) · Automatica · doi:10.1016/0005-1098(84)90098-0 · Cited by 2,364
A survey of design methods for failure detection in dynamic systems
Willsky, A. S. (1976) · Automatica · doi:10.1016/0005-1098(76)90041-8 · Cited by 2,153
Fault Detection and Diagnosis in Engineering Systems
Gertler, J. J. (2017) · CRC Press eBooks · doi:10.1201/9780203756126 · Cited by 1,999
Statistical process monitoring: basics and beyond
Joe Qin, S. (2003) · Journal of Chemometrics · doi:10.1002/cem.800 · Cited by 1,582
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Multivariate SPC Charts for Monitoring Batch Processes
Nomikos, P., & MacGregor, J. F. (1995) · Technometrics · doi:10.1080/00401706.1995.10485888 · Cited by 1,422
A survey of design methods for failure detection in dynamic systems
(1977) · Microelectronics Reliability · doi:10.1016/0026-2714(77)90326-2 · Cited by 1,421
Fault Detection and Diagnosis in Industrial Systems
Braatz, L. H. C. (2001) · Measurement Science and Technology · doi:10.1088/0957-0233/12/10/706 · Cited by 1,416
Fault Detection and Diagnosis in Industrial Systems
Chiang, L. H., Russell, E. L., & Braatz, R. D. (2001) · Advanced Textbooks in Control and Signal Processing · doi:10.1007/978-1-4471-0347-9 · Cited by 1,318
The process chemometrics approach to process monitoring and fault detection
Wise, B. M., & Gallagher, N. B. (1996) · Journal of Process Control · doi:10.1016/0959-1524(96)00009-1 · Cited by 852
Identification of faulty sensors using principal component analysis
Dunia, R., Qin, S. J., Edgar, T. F., & McAvoy, T. J. (1996) · AIChE Journal · doi:10.1002/aic.690421011 · Cited by 526
Self-citationReconstruction-Based Fault Identification Using a Combined Index
Yue, H. H., & Qin, S. J. (2001) · Industrial & Engineering Chemistry Research · doi:10.1021/ie000141+ · Cited by 509
Self-citationGeneralized contribution plots in multivariate statistical process monitoring
Westerhuis, J. A., Gurden, S. P., & Smilde, A. K. (2000) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(00)00062-9 · Cited by 507
Subspace approach to multidimensional fault identification and reconstruction
Dunia, R. H., & Qin, S. J. (1998) · AIChE Journal · doi:10.1002/aic.690440812 · Cited by 382
Self-citationContribution plots: a missing link in multivariate quality control
Miller, P. C., Swanson, R. E., & Heckler, C. E. (1998) · International Journal of Applied Mathematics and Computer Science · Cited by 374
Detection and identification of faulty sensors in dynamic processes
Qin, S. J., & Li, W. (2001) · AIChE Journal · doi:10.1002/aic.690470711 · Cited by 157
Self-citationDetection, identification, and reconstruction of faulty sensors with maximized sensitivity
Qin, S. J., & Li, W. (1999) · AIChE Journal · doi:10.1002/aic.690450913 · Cited by 140
Self-citationPattern Matching in Multivariate Time Series Databases Using a Moving-Window Approach
Singhal, A. K., & Seborg, D. E. (2002) · Industrial & Engineering Chemistry Research · doi:10.1021/ie010517z · Cited by 79
Cited by
Wind Turbine Fault Detection Using a Denoising Autoencoder With Temporal Information
Jiang, G., Xie, P., He, H., & Yan, J. (2018) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2017.2759301 · Cited by 288
Challenges in the Development of Soft Sensors for Bioprocesses: A Critical Review
Brunner, V., Siegl, M., Geier, D., & Becker, T. (2021) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2021.722202 · Cited by 100
Metadata
- Authors
- Alcala, C. F., & Qin, S. J.
- Venue
- Automatica
- Publisher
- Elsevier BV
- Published
- 2009-07
- Volume
- 45
- Issue
- 7
- Pages
- 1593-1600
- ISSN
- 0005-1098 (ISSN-L)
- OpenAlex
- W2002268936
- Cited by
- 567
- References
- 18
- FWCI
- 26.75
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
