Progress of data-driven and knowledge-driven process monitoring and fault diagnosis for industry process

被引:0
|
作者
Liu, Qiang [1 ,2 ]
Chai, Tian-You [1 ,2 ]
Qin, S-Joe [3 ]
Zhao, Li-Jie [1 ,4 ]
机构
[1] Key Laboratory of Process Industry Automation of Ministry of Education, Northeastern University, Shenyang 110819, China
[2] Research Center of Automation, Northeastern University, Shenyang 110819, China
[3] The Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles 90089, United States
[4] Information Engineering School, Shenyang Institute of Chemical Technology, Shenyang 110032, China
来源
Kongzhi yu Juece/Control and Decision | 2010年 / 25卷 / 06期
关键词
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:801 / 807
相关论文
共 50 条
  • [11] Fault diagnosis for open-circuit faults in NPC inverter based on knowledge-driven and data-driven approaches
    Kou, Lei
    Liu, Chuang
    Cai, Guo-wei
    Zhou, Jia-ning
    Yuan, Quan-de
    Pang, Si-miao
    [J]. IET POWER ELECTRONICS, 2020, 13 (06) : 1236 - 1245
  • [12] Integrating knowledge-driven and data-driven approaches to modeling
    Todorovski, L
    Dzeroski, S
    [J]. ECOLOGICAL MODELLING, 2006, 194 (1-3) : 3 - 13
  • [13] A General Paradigm of Knowledge-driven and Data-driven Fusion
    Hu, Fei
    Zhong, Wei
    Ye, Long
    Duan, Danting
    Zhang, Qin
    [J]. 2023 15TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE, ICACI, 2023,
  • [14] A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process
    Yin, Shen
    Ding, Steven X.
    Haghani, Adel
    Hao, Haiyang
    Zhang, Ping
    [J]. JOURNAL OF PROCESS CONTROL, 2012, 22 (09) : 1567 - 1581
  • [15] An adaptive data-driven fault detection method for monitoring dynamic process
    Chen, Zhiwen
    Peng, Tao
    Yang, Chunhua
    Li, Fanbiao
    He, Zhangming
    [J]. IECON 2018 - 44TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2018, : 5353 - 5358
  • [16] Monitoring a segmented fluid bed dryer by hybrid data-driven/knowledge-driven modeling
    Destro, Francesco
    Salmon, Andrew J.
    Facco, Pierantonio
    Pantelides, Constantinos C.
    Bezzo, Fabrizio
    Barolo, Massimiliano
    [J]. IFAC PAPERSONLINE, 2020, 53 (02): : 11638 - 11643
  • [17] Improved Fault Diagnosis in Online Process Monitoring of Complex Networked Processes: a Data-Driven Approach
    Rato, Tiago J.
    Reis, Marco S.
    [J]. 27TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PT B, 2017, 40B : 1681 - 1686
  • [18] A data-driven Bayesian network learning method for process fault diagnosis
    Amin, Md Tanjin
    Khan, Faisal
    Ahmed, Salim
    Imtiaz, Syed
    [J]. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2021, 150 : 110 - 122
  • [19] A data-driven multidimensional visualization technique for process fault detection and diagnosis
    Gajjar, Shriram
    Palazoglu, Ahmet
    [J]. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2016, 154 : 122 - 136
  • [20] A data-driven distributed process monitoring method for industry manufacturing systems
    Yin, Ming
    Tian, Jiayi
    Zhu, Dan
    Wang, Yibo
    Jiang, Jijiao
    [J]. TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2024, 46 (07) : 1296 - 1316