The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Improved PLS Focused on Key-Performance-Indicator-Related Fault Diagnosis
Abstract
Standard partial least squares (PLS) serves as a powerful tool for key performance indicator (KPI) monitoring in large-scale process industry for last two decades. However, the standard approach and its recent modifications still encounter some problems for fault diagnosis related to KPI of the underlying process. To cope with these difficulties, an improved PLS (IPLS) approach is presented in this paper. IPLS is able to decompose the measurable process variables into the KPI-related and unrelated parts, respectively. Based on it, the corresponding test statistics are designed to offer meaningful fault diagnosis information and thus, the corresponding maintenance actions can be further taken to ensure the desired performance of the systems. In order to demonstrate the effectiveness of the proposed approach, a numerical example and Tennessee Eastman (TE) benchmark process are respectively utilized. It can be seen that the proposed approach shows satisfactory results not only for diagnosing KPI-related faults but also for its high fault detection rate.
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Cites
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Fault Detection and Diagnosis in Industrial Systems
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Self-citationModel-Based Fault Diagnosis Techniques: Design Schemes, Algorithms and Tools
Ding, S. X. (2013) · Advances in Industrial Control · doi:10.1007/978-1-4471-4799-2 · Cited by 667
Real-Time Implementation of Fault-Tolerant Control Systems With Performance Optimization
Yin, S., Luo, H., & Ding, S. X. (2014) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2013.2273477 · Cited by 644
Self-citationTotal projection to latent structures for process monitoring
Zhou, D., Li, G., & Qin, S. J. (2010) · AIChE Journal · doi:10.1002/aic.11977 · Cited by 472
Geometric properties of partial least squares for process monitoring
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Cited by
Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., & Bakiras, S. (2021) · IEEE Access · doi:10.1109/access.2021.3060863 · Cited by 616
Metadata
- Authors
- Yin, S., Zhu, X., & Kaynak, O.
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2015-03
- Volume
- 62
- Issue
- 3
- Pages
- 1651-1658
- ISSN
- 0278-0046 (ISSN-L)
- 1557-9948
- OpenAlex
- W2052828853
- Cited by
- 537
- References
- 21
- FWCI
- 99.00
- Type
- journal article
- Language
- en
- Open access
- closed
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