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《Journal of Optoelectronics·Laser》 2018-06
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Fault isolation method based on Bayesian Lasso for industrial process

WU Ping;ZHANG Shen-bo;YAN Zheng-bing;ZHANG Zheng-jiang;DAI Yu-xing;College of Physics and Electronic Information Engineering,Wenzhou University;  
A novel method based on the combination of least absolute shrinkage and selection operator(Lasso)and Bayesian analysis is proposed.Firstly,the fault isolation problem is transformed into a quadratic programming problem.Then,Bayesian analysis is introduced to solve this problem.Then,the probability distribution of abnormality for each variable could be given.Through the analysis of the probability distribution diagram of variable faults,the most possible fault variables are found.The proposed method could identify the faulty variables when the fault directions are unavailable.Finally,numerical simulations of Tennessee Eastman process are carried out by using MATLAB for reactor,condenser,compressor,separator and stripper.The results show that the proposed method does not require fault direction or other process knowledge,improves the computational efficiency and practicability of fault diagnosis technology,and provides effective guidance for process maintenance and recovery.
【Fund】: 国家自然科学基金(61374167);; 浙江省自然科学基金(LQ14F030006)资助项目
【CateGory Index】: TP277
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