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• W1596758839 abstract "In this chapter, an integrated design framework incorporating unscented Kalman filter is developed to utilize multi-sensor data fusion techniques for process fault monitoring. The multi-sensor data fusion technique is presented via centralized and decentralized architectures. Detailed simulation studies have been conducted to demonstrate the performance of the proposed scheme on quadruple tank system and industrial boiler. It is established that the decentralized integrated framework retrieves more effectively the critical information about presence or absence of a fault from the dynamic model with minimum time delay and provides accurate unfolding-in-time of the finer details of the fault as compared to the centralized integrated framework, thus completing the overall picture of fault monitoring of the system under test." @default.
• W1596758839 created "2016-06-24" @default.
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• W1596758839 date "2013-11-05" @default.
• W1596758839 modified "2023-09-23" @default.
• W1596758839 title "Fault Diagnosis and Detection" @default.
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• W1596758839 doi "https://doi.org/10.1002/9781118700365.ch2" @default.
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