SPA-Based Modified Local Reachability Density Ratio wSVDD for Nonlinear Multimode Process Monitoring
نویسندگان
چکیده
Many industrial processes are operated in multiple modes due to different manufacturing strategies. Multimodality of process data is often accompanied with nonlinear and non-Gaussian characteristics, which makes data-driven monitoring more complicated. In this paper, statistics pattern analysis (SPA) introduced extract low- high-order from raw data. Support vector description (SVDD), can deal problems, applied monitor multimode paper. To improve detection performance SVDD for training outliers, modified local reachability density ratio (mLRDR) proposed as a weight factor be embedded the weighted-SVDD (wSVDD) model, neighbors terms both space time considered. Finally, effectiveness superiority our method demonstrated by Tennessee-Eastman (TE) wastewater treatment (WWTP).
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1Department of Electrical Engineering and Computer Science, University of California at Berkeley, Berkeley, CA, USA 2Department of Aerospace Engineering and Mechanics, University of Minnesota, Minneapolis, MN, USA 3DSO National Laboratories, Singapore 4California Institute of Technology, Department of Control and Dynamical Systems, Pasadena, CA, USA 5Department of Mechanical Engineering, Univer...
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ژورنال
عنوان ژورنال: Complexity
سال: 2021
ISSN: ['1099-0526', '1076-2787']
DOI: https://doi.org/10.1155/2021/5517062