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http://dx.doi.org/10.7842/kigas.2019.23.4.19

Development of Monitoring System for the LNG plant fractionation process based on Multi-mode Principal Component Analysis  

Pyun, Hahyung (School of chemical and Biological Engineering, Seoul National University)
Lee, Chul-Jin (School of Chemical Engineering and Materials Science, Chung-Ang University)
Lee, Won Bo (School of chemical and Biological Engineering, Seoul National University)
Publication Information
Journal of the Korean Institute of Gas / v.23, no.4, 2019 , pp. 19-27 More about this Journal
Abstract
The consumption of liquefied natural gas (LNG) has increased annually due to the strengthening of international environmental regulations. In order to produce stable and efficient LNG, it is essential to divide the global (overall) operating condition and construct a quick and accurate monitoring system for each operation condition. In this study, multi-mode monitoring system is proposed to the LNG plant fractionation process. First, global normal operation data is divided to local (subdivide) normal operation data using global principal component analysis (PCA) and k-means clustering method. And then, the data to be analyzed were matched with the local normal mode. Finally, it is determined the state of process abnormality through the local PCA. The proposed method is applied to 45 fault case and it proved to be more than 5~10% efficient compared to the global PCA and univariate monitoring.
Keywords
fault detection; multi mode monitoring; liquefied natural gas (LNG); principal component analysis (PCA); k-means clustering; k-nearest neighbors;
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