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Online Fault Diagnosis for Biochemical Process Based on FCM and SVM
Xianfang Wang1,2, Haoze Du3, Jinglu Tan4
1School of Computer and Information Engineering, Henan Normal University, Xinxiang, 453007, People's Republic of China. 2wangfang@163.com.
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.
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Classification of Systems-I
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as: