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Support vector regression modeling in recursive just-in-time learning framework for adaptive soft sensing of naphtha boiling point in crude distillation unit

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Petroleum Science 2021年第4期18卷 1230-1239页

作者： Venkata Vijayan S Hare Krishna Mohanta Ajaya Kumar Pani Department of Chemical Engineering Birla Institute of Technology and SciencePilaniRajasthan333031India

Prediction of primary quality variables in real time with adaptation capability for varying process conditions is a critical task in process *** article focuses on the development of non-linear adaptive soft sensors for prediction of naphtha initial boiling point(IBP)and end boiling point(EBP)in crude distillation *** this work,adaptive inferential sensors with linear and non-linear local models are reported based on recursive just in time learning(JITL)*** different types of local models designed are locally weighted regression(LWR),multiple linear regression(MLR),partial least squares regression(PLS)and support vector regression(SVR).In addition to model development,the effect of relevant dataset size on model prediction accuracy and model computation time is also *** show that the JITL model based on support vector regression with iterative single data algorithm optimization(ISDA)local model(JITL-SVR:ISDA)yielded best prediction accuracy in reasonable computation time.

关键词： Adaptive soft sensor just in time learning Regression Support vector regression Naphtha boiling point

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JITL based Fault Detection of DAB DC-DC Converter with EPS Control

JITL based Fault Detection of DAB DC-DC Converter with EPS C...

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第三十九届中国控制会议

作者： Yu Zhang Rui Yang Huiqing Wen College of Electrical Engineering and Automation Shandong University of Science and Technology School of Advanced Technology Xi'an Jiaotong-Liverpool University Research Institute of Big Data Analytics Xi'an Jiaotong-Liverpool University

As the most important part of the power system, the reliability of dual-active-bridge（DAB） DC-DC converter determines the safe operation of equipment. Thus, this paper proposes a fault detection scheme based on just-in-time-learning（JITL）in DAB DC-DC converter with extended-phase-shift（EPS） control. The performance of the DAB DC-DC converter under the two different control methods are analyzed, and the faults in the primary circuit are detected using JITL method. The simulation model is established using Matlab and the experimental results are analyzed to verify the effectiveness of the method.

关键词： Dual-Active-Bridge Converter just in time learning Fault Detection

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