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《中国化学工程学报(英文版)》 2012-06
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Multimode Process Monitoring Based on Fuzzy C-means in Locality Preserving Projection Subspace

XIE Xiang and SHI Hongbo ** Key Laboratory of Advanced Control and Optimization for Chemical Processes, East China University of Science and Technology, Ministry of Education, Shanghai 200237, China  
For complex industrial processes with multiple operational conditions, it is important to develop effective monitoring algorithms to ensure the safety of production processes. This paper proposes a novel monitoring strategy based on fuzzy C-means. The high dimensional historical data are transferred to a low dimensional subspace spanned by locality preserving projection. Then the scores in the novel subspace are classified into several overlapped clusters, each representing an operational mode. The distance statistics of each cluster are integrated though the membership values into a novel BID (Bayesian inference distance) monitoring index. The efficiency and effectiveness of the proposed method are validated though the Tennessee Eastman benchmark process.
【Fund】: Supported by the National Natural Science Foundation of China (61074079);; Shanghai Leading Academic Discipline Project (B054)
【CateGory Index】: TP274;TP18
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