Authors: Xianfang Wang Haoze Du Jinglu Tan
Publish Date: 2016/04/29
Volume: 8, Issue: 4, Pages: 419-424
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 cmeans 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 methodThe project was supported by the National Natural Science Foundation of China No 61173071 the Science and Technology Research Project of Henan Province No 122102210079 the 2013 Program of China Scholarship Council Countries about Senior Research Scholar and Visiting Scholar No 201308410018 the Innovation Talent Support Program of Henan Province Universities No 2012HASTIT011 and the Doctoral Started Project of Henan Normal University No 1039 Therefore it is necessary for the stability conditions to be investigated in the multiregions
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