The application of independent component analysis in process monitoring

被引：1
|
作者：
Li Hongguang [1 ]
Hui, Guo [1 ]
机构：
[1] Beijing Univ Chem Technol, Informat Sch Informat Sci & Technol, Beijing 100029, Peoples R China
来源：
ICICIC 2006: FIRST INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING, INFORMATION AND CONTROL, VOL 1, PROCEEDINGS | 2006年
关键词：
D O I：
10.7150/ijms.3.97
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A method of using Independent Component Analysis (ICA) to monitor process is proposed in this paper. The concept, model and algorithm of ICA are introduced first, and then ICA applications in the multivariable statistical process monitoring are discussed A simulation example is used to demonstrate this approach. The results show that the independent component analysis can be considered as a new effective tool providing for statistical process monitoring and fault diagnosis.
引用
下载
收藏
页码：97 / +
页数：2
相关论文
共 50 条
  • [21] Non-Gaussian Industrial Process Monitoring With Probabilistic Independent Component Analysis
    Zhu, Jinlin
    Ge, Zhiqiang
    Song, Zhihuan
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2017, 14 (02) : 1309 - 1319
  • [22] Introduction of dynamics to an approach for batch process monitoring using independent component analysis
    Albazzaz, Hamza
    Wang, Xue Z.
    CHEMICAL ENGINEERING COMMUNICATIONS, 2007, 194 (02) : 218 - 233
  • [23] A Kernel Time Structure Independent Component Analysis Method for Nonlinear Process Monitoring
    Cai, Lianfang
    Tian, Xuemin
    Zhang, Ni
    CHINESE JOURNAL OF CHEMICAL ENGINEERING, 2014, 22 (11-12) : 1243 - 1253
  • [24] Integrating independent component analysis and support vector machine for multivariate process monitoring
    Hsu, Chun-Chin
    Chen, Mu-Chen
    Chen, Long-Sheng
    COMPUTERS & INDUSTRIAL ENGINEERING, 2010, 59 (01) : 145 - 156
  • [25] Evolution of multivariate statistical process control: application of independent component analysis and external analysis
    Kano, M
    Hasebe, S
    Hashimoto, I
    Ohno, H
    COMPUTERS & CHEMICAL ENGINEERING, 2004, 28 (6-7) : 1157 - 1166
  • [26] Application of principal component analysis for monitoring and disturbance detection of a hydrotreating process
    Bezergianni, Stella
    Kalogianni, Aggeliki
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2008, 47 (18) : 6972 - 6982
  • [27] Wavelet kernel entropy component analysis with application to industrial process monitoring
    Yang, Yinghua
    Li, Xiaole
    Liu, Xiaozhi
    Chen, Xiaobo
    NEUROCOMPUTING, 2015, 147 : 395 - 402
  • [28] Wavelet - Based Principal Component Analysis for Process Monitoring With Experimental Application
    Alkaya, Alkan
    Eker, Ilyas
    2013 8TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ELECO), 2013, : 634 - 638
  • [29] Integrating Canonical Variate Analysis and Kernel Independent Component Analysis for Tennessee Eastman Process Monitoring
    Sun, Dongdong
    Gong, XiaoFeng
    Chen, Yonglu
    JOURNAL OF CHEMICAL ENGINEERING OF JAPAN, 2020, 53 (03) : 126 - 133
  • [30] Process monitoring based on independent component analysis-principal component analysis (ICA-PCA) and similarity factors
    Ge, Zhiqiang
    Song, Zhihuan
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2007, 46 (07) : 2054 - 2063
12345