Weighted preliminary-summation-based principal component analysis for non-Gaussian processes. (June 2019)

• Record Type: Journal Article
• Authors: Li, Ning; Guo, Shaojun; Wang, Youqing
• Is Part Of: Control engineering practice. Volume 87(2019)
• Page Start: 122
• Page End: 132
• Publication Date: 2019-06
• Subjects: Process monitoring -- Preliminary-summation-based PCA (PS-PCA) -- Generalized central limit theorem (CLT) -- Gaussian verification -- Weighted preliminary-summation-based PCA (WPS-PCA); Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2019.03.015
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: For industrial chemical process, preliminary-summation-based principal component analysis (PS-PCA), an amended PCA method was recently provided for coping with both Gaussian and non-Gaussian characteristics. By summing the training and monitoring data respectively, PS-PCA is capable of resolving the issue of non-Gaussian processes and achieves higher fault detection rate than the traditional PCA. However, in the PS-PCA summation operation, all data samples are regarded as the same weight, which results in the fault information of newly-samples may be diluted, leading to significant detection delays. To address this challenge, in this paper, we propose a novel weighted PS-PCA (WPS-PCA) method that employs an exponential weighting scheme to put more emphasis on recent information. Subsequently, a mathematical argument demonstrates that when the number of variables is enough plentiful, the obtained summation combined with the generalized central limit theorem conforms to approximately a Gaussian distribution. The kurtosis relationships indicate this conversion will bring out well-pleasing feasibility for conventional PCA. Ultimately, the proposed technique verifies detection performance using the Tennessee Eastman process, which is compared with the existing PCA and PS-PCA schemes, in terms of the fault detection time and fault detection rate. The simulation studies reveal that the proposed method is efficient and superior.