title: Online Fault Diagnosis for Biochemical Process Based on FCM and SVM.
abstract: Fault diagnosis is becoming an important issue in biochemical process, and a novel online fault detection and diagnosis approach is designed by combining fuzzy c-means (FCM) and support vector machine (SVM). The samples are preprocessed via FCM algorithm to enhance the ability of classification firstly. Then, those samples are input to the SVM classifier to realize the biochemical process fault diagnosis. In this study, a glutamic acid fermentation process is chosen as an example to diagnose the fault by this method, the result shows that the diagnosis time is largely shortened, and the accuracy is extremely improved by comparing to a single SVM method.
authors.affiliation: School of Computer and Information Engineering, Henan Normal University, Xinxiang, 453007, People's Republic of China. 2wangfang@163.com.|School of Engineering, University of Missouri, Columbia, MO, 65211, USA. 2wangfang@163.com.
authors.forename: Xianfang
authors.initials: X
authors.lastname: Wang
authors.affiliation: School of Information Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, People's Republic of China.
authors.forename: Haoze
authors.initials: H
authors.lastname: Du
authors.affiliation: School of Engineering, University of Missouri, Columbia, MO, 65211, USA.
authors.forename: Jinglu
authors.initials: J
authors.lastname: Tan
mesh_terms: D000465:Algorithms; D017143:Fuzzy Logic; D060388:Support Vector Machine
keywords: Fault diagnosis; Fuzzy c-means; Glutamic acid fermentation process; Support vector machine