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
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
收藏
页码:419 / 424
页数:6
相关论文
共 50 条
  • [31] Application of LDA and SVM method in fault diagnosis of chemical process
    Ji F.-C.
    Yu Y.-S.
    Zhang Z.-X.
    Gao Xiao Hua Xue Gong Cheng Xue Bao/Journal of Chemical Engineering of Chinese Universities, 2020, 34 (02): : 487 - 494
  • [32] Fault diagnosis in technical process: a data mining and SVM setting
    Addison, Rios-Bolivar
    Francisco, Hidrobo
    Pablo, Guillen
    CIENCIA E INGENIERIA, 2014, 35 (03): : 125 - 134
  • [33] Roller Bearing Fault Diagnosis Based on Integrated Fault Feature and SVM
    Wang, Mengjiao
    Chen, Yangfan
    Zhang, Xinan
    Chau, Tat Kei
    Iu, Herbert Ho Ching
    Fernando, Tyrone
    Li, Zhijun
    Ma, Minglin
    JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES, 2022, 10 (03) : 853 - 862
  • [34] Roller Bearing Fault Diagnosis Based on Integrated Fault Feature and SVM
    Mengjiao Wang
    Yangfan Chen
    Xinan Zhang
    Tat Kei Chau
    Herbert Ho Ching Iu
    Tyrone Fernando
    Zhijun Li
    Minglin Ma
    Journal of Vibration Engineering & Technologies, 2022, 10 : 853 - 862
  • [35] Fault diagnosis and accommodation based on online multi-model for nonlinear process
    Li, Jun
    Bo, Cuimei
    Zhang, Jiugen
    Du, Jie
    COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS, 2006, 4114 : 661 - 666
  • [36] Gray fault diagnosis method based on LSA and SVM
    Hu Mingjie
    He Yuzhu
    Li Jianhong
    2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 1, 2009, : 108 - 112
  • [37] Network fault diagnosis based on Dual-SVM
    Wen, Xiang-Xi
    Meng, Xiang-Ru
    Ma, Zhi-Qiang
    Kongzhi yu Juece/Control and Decision, 2013, 28 (04): : 506 - 510
  • [38] Turbine Fault Diagnosis Based on Fuzzy Theory and SVM
    Xia, Fei
    Zhang, Hao
    Peng, Daogang
    Li, Hui
    Su, Yikang
    ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, PROCEEDINGS, 2009, 5855 : 668 - +
  • [39] Node Fault Diagnosis in WSN Based on RS and SVM
    Yu, Cheng-bo
    Hu, Jing-jing
    Li, Rui
    Deng, Shun-hua
    Yang, Ru-min
    2014 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATION AND SENSOR NETWORK (WCSN), 2014, : 153 - 156
  • [40] Fault diagnosis of rolling bearings based on ISSA - SVM
    Li X.
    Jin W.
    Zhendong yu Chongji/Journal of Vibration and Shock, 2023, 42 (06): : 106 - 114