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Process Monitoring and Fault Detection Method Based On Independent Component Analysis

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4 Author(s)
Yinghua Wu ; School of Information Science and Engineering, Northeastern Univ., Shenyang, 110004 ; Yinghua Yang ; Shukai Qin ; Xiaobo Chen

Multivariate statistical process control (MSPC) are based upon the assumption that the observed data must be subject to normal probability distribution, which sometimes can not be satisfied in many industrial applications. Independent component analysis (ICA) is a recently developed method, which can overcome the need of the data distribution. In this paper, a new method is introduced for process monitoring and fault detection based on ICA method. Use ICA to extract the independent components, use I2, Ie2 and SPE charts for fault detection. At last, the simulation results of fractional distillation process monitoring reveal this method is very effective

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2006 6th World Congress on Intelligent Control and Automation  (Volume:2 )

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