Journal
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
Volume 149, Issue -, Pages 619-630Publisher
ELSEVIER
DOI: 10.1016/j.psep.2021.03.025
Keywords
Kernel canonical correlation analysis; Nystrom approximation; Matter-element; Fault detection; Nonlinear industrial process
Categories
Funding
- National Natural Science Foundation of China [61873096, 61673181]
- Guangdong Basic and Applied Basic Research Foundation [2020A1515011057]
- Guangdong Technology International Cooperation Project Application [2020A0505100024]
- Fundamental Research Funds for the central Universities, SCUT [2020ZYGXZR034]
- Australian Research Council (ARC) [DP200100933]
- Australian Research Council [DP200100933] Funding Source: Australian Research Council
Ask authors/readers for more resources
The newly proposed M-NAKCCA framework demonstrates excellent performance in process monitoring, better applied for nonlinear fault detection, compressing high-dimensional datasets, and enhancing method sensitivity.
Process monitoring is essential and important strategy for ensuring process safety and product quality. However, due to the nonlinear characteristics and multiple working conditions in process industries, the traditional process monitoring method cannot be effectively applied. Therefore, we propose a novel process monitoring framework, termed as mixture enhanced kernel canonical correlation analysis framework (M-NAKCCA). The innovations and advantages of M-NAKCCA are as follows: 1). The traditional CCA method is re-boosted as a new method, M-NAKCCA, to better nonlinear fault detection. Also, a matter-element model (MEm) is assimilated into M-NAKCCA to make the information more refined. 2). To overcome the curse of dimensionality that usually occurs in the high-dimensional dataset, M-NAKCCA uses the Nystrom approximation technology to compress the kernel matrix. Moreover, the T-2 control chart is reconstructed and the corresponding control upper limit is re-configured to improve the method sensitivity and to better the fault detection performance. 3). The proposed M-NAKCCA framework is firstly used to monitor a wastewater treatment plant (WWTP) and chemical plant with diverse process behaviors. The experimental results showed that the M-NAKCCA framework achieved the best performance for both of case studies. (C) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available