Online Fault Diagnosis for Biochemical Process Based on FCM and SVM

被引：7

作者：

Wang, Xianfang ^{[1
,3
]}

Du, Haoze ^{[2
]}

Tan, Jinglu ^{[3
]}

机构：

[1] Henan Normal Univ, Sch Comp & Informat Engn, Xinxiang 453007, Peoples R China

[2] Nanjing Univ Aeronaut & Astronaut, Sch Informat Sci & Technol, Nanjing 210016, Jiangsu, Peoples R China

[3] Univ Missouri, Sch Engn, Columbia, MO 65211 USA

来源：

INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES | 2016年 / 8卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Fuzzy c-means; Support vector machine; Fault diagnosis; Glutamic acid fermentation process;

D O I：

10.1007/s12539-016-0172-9

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页码：419 / 424

页数：6

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