Fault diagnosis of chemical industry process based on FRS and SVM
Xianfan Wang · Kongzhi yu juece · 2015
In order to solve the problem about fault diagnosis for the chemical industry process, a fault diagnosis approach is proposed based on feature extraction by using fuzzy rough sets and support vector machines.The feature information is extracted by utilizing fuzzy rough sets and the fault diagnosis sets is built firstly. Then, the samples corresponding to the fault diagnosis sets are input into the SVM multi-classifier to realize the identification of different fault diagnosis in the chemical industry process. Finally, the effectiveness of the proposed method is illustrated through fault diagnosis in TEP chemical industry process.