Research on soft sensing method based on continuous hidden Markov model in fermentation process

被引:0
|
作者
Liu, Guo-Hai [1 ]
Jiang, Xing-Ke [1 ]
Mei, Cong-Li [1 ]
机构
[1] School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China
来源
Kongzhi yu Juece/Control and Decision | 2011年 / 26卷 / 11期
关键词
Hidden Markov models - Process control;
D O I
暂无
中图分类号
O21 [概率论与数理统计];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
A soft sensing modeling method based on continuous hidden Markov model(CHMM) is developed to deal with the problem that some biologic variables cannot be measured directly online in fermentation process. In order to reduce the computation quantity of modeling process, improved minimum classification error criteria is used to train the CHMMbased soft sensor. Meanwhile, a soft sensing credibility evaluation index is proposed to avoid blindness problem during the practical application of soft sensing result to monitoring in fermentation process. The testing result shows the effectiveness of the proposed method and the practical significance of the credibility evaluation index.
引用
收藏
页码:1753 / 1756
相关论文
共 50 条
  • [41] A method of gesture recognition based on the improved hidden markov model
    College of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an
    Shaanxi
    710054, China
    Open. Cybern. Syst. J., 1 (217-221):
  • [42] A Method of Fault Alarm Recognition based on Hidden Markov Model
    Guan, Fei
    Wu, Jie
    Cui, Weiwei
    2016 PROGNOSTICS AND SYSTEM HEALTH MANAGEMENT CONFERENCE (PHM-CHENGDU), 2016,
  • [43] Welding Quality Prediction Method Based on Hidden Markov Model
    Sun, Xiaobao
    Liu, Yang
    Wang, Dongyao
    Ye, Hang
    2022 IEEE 2ND INTERNATIONAL CONFERENCE ON INFORMATION COMMUNICATION AND SOFTWARE ENGINEERING (ICICSE 2022), 2022, : 236 - 240
  • [44] Line spectrum extraction method based on hidden Markov model
    Ma, Kai
    Luo, Guangcheng
    Cheng, Jian
    Cheng, Yusheng
    Li, Haitao
    ELECTRONICS LETTERS, 2021, 57 (12) : 486 - 488
  • [45] English speech recognition method based on Hidden Markov model
    Lv Cuiling
    2016 INTERNATIONAL CONFERENCE ON SMART GRID AND ELECTRICAL AUTOMATION (ICSGEA 2016), 2016, : 94 - 97
  • [46] Method of Turnout Fault Diagnosis Based on Hidden Markov Model
    Xu Q.
    Liu Z.
    Zhao H.
    Liu, Zhongtian (liuzht@bjtu.edu.cn), 2018, Science Press (40): : 98 - 106
  • [47] A Method of the Switchgear State Estimation Based on the Hidden Markov Model
    Chang, Fang-Yuan
    Li, Er-Xia
    Sheng, Wan-Xing
    Kang, Chao-Qun
    2015 International Symposium on Smart Electric Distribution Systems and Technologies (EDST), 2015, : 14 - 19
  • [48] Gesture recognition based on subspace method and hidden Markov model
    Iwai, Y
    Hata, T
    Yachida, M
    IROS '97 - PROCEEDINGS OF THE 1997 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOT AND SYSTEMS: INNOVATIVE ROBOTICS FOR REAL-WORLD APPLICATIONS, VOLS 1-3, 1996, : 960 - 966
  • [49] Application of Hidden Markov Model to Identify Disease Progression Process in Medical Research
    Madadizadeh, Farzan
    Yarahmadi, Mohammad
    Zeraati, Hojjat
    IRANIAN JOURNAL OF PUBLIC HEALTH, 2020, 49 (06) : 1200 - 1201
  • [50] Blind continuous hidden Markov model-based spectrum sensing and recognition for primary user with multiple power levels
    Liu, Boyang
    Li, Zan
    Si, Jiangbo
    Zhou, Fuhui
    IET COMMUNICATIONS, 2015, 9 (11) : 1396 - 1403