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• W3127624779 abstract "In this paper, a data-driven model combining multivariate nonlinear chirp mode decomposition (MNCMD) with multivariate Granger causality (MGC) is proposed to analyze root causes for multiple plant-wide oscillations in process control system. Firstly, an MNCMD-based detector is developed to capture the multiple plant-wide oscillations, where oscillating variables caused by different sources are automatically clustered into various groups. Then, MGC is applied to each group to obtain the root causes of multiple plant-wide oscillations. Compared with state-of-the-art detection methods, the proposed approach shows better performance in the following aspects: (i) ability to extract both single/multiple plant-wide oscillations; (ii) capability to process both time-invariant/time-varying oscillations and provide accurate time-frequency information. The effectiveness and advantages of the proposed approach are demonstrated with the help of both simulation and industrial case studies." @default.
• W3127624779 created "2021-02-15" @default.
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• W3127624779 date "2020-11-06" @default.
• W3127624779 modified "2023-09-27" @default.
• W3127624779 title "MNCMD-based Causality Analysis of Plant-wide Oscillations for Industrial Process Control System" @default.
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• W3127624779 doi "https://doi.org/10.1109/cac51589.2020.9327085" @default.
• W3127624779 hasPublicationYear "2020" @default.
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