1
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Zhang S, Bao X, Wang S. Common canonical variate analysis (CCVA) based modeling and monitoring for multimode processes. Chem Eng Sci 2023. [DOI: 10.1016/j.ces.2023.118581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
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2
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Wang S, Wang Y, Tong J, Chang Y. Fault Monitoring Based on the VLSW-MADF Test and DLPPCA for Multimodal Processes. SENSORS (BASEL, SWITZERLAND) 2023; 23:987. [PMID: 36679784 PMCID: PMC9866069 DOI: 10.3390/s23020987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 01/11/2023] [Accepted: 01/12/2023] [Indexed: 06/17/2023]
Abstract
Actual industrial processes often exhibit multimodal characteristics, and their data exhibit complex features, such as being dynamic, nonlinear, multimodal, and strongly coupled. Although many modeling approaches for process fault monitoring have been proposed in academia, due to the complexity of industrial data, challenges remain. Based on the concept of multimodal modeling, this paper proposes a multimodal process monitoring method based on the variable-length sliding window-mean augmented Dickey-Fuller (VLSW-MADF) test and dynamic locality-preserving principal component analysis (DLPPCA). In the offline stage, considering the fluctuation characteristics of data, the trend variables of data are extracted and input into VLSW-MADF for modal identification, and different modalities are modeled separately using DLPPCA. In the online monitoring phase, the previous moment's historical modal information is fully utilized, and modal identification is performed only when necessary to reduce computational cost. Finally, the proposed method is validated to be accurate and effective for modal identification, modeling, and online monitoring of multimodal processes in TE simulation and actual plant data. The proposed method improves the fault detection rate of multimodal process fault monitoring by about 14% compared to the classical DPCA method.
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3
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Chen X, Hu Y, Zhao C. Multiple Condition Indicator Decoupling and Hierarchical Monitoring for Large-Scale Nonstationary Processes. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c00013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Xu Chen
- State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Yunyun Hu
- State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Chunhui Zhao
- State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China
- State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China
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4
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A Review on Data-Driven Process Monitoring Methods: Characterization and Mining of Industrial Data. Processes (Basel) 2022. [DOI: 10.3390/pr10020335] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Safe and stable operation plays an important role in the chemical industry. Fault detection and diagnosis (FDD) make it possible to identify abnormal process deviations early and assist operators in taking proper action against fault propagation. After decades of development, data-driven process monitoring technologies have gradually attracted attention from process industries. Although many promising FDD methods have been proposed from both academia and industry, challenges remain due to the complex characteristics of industrial data. In this work, classical and recent research on data-driven process monitoring methods is reviewed from the perspective of characterizing and mining industrial data. The implementation framework of data-driven process monitoring methods is first introduced. State of art of process monitoring methods corresponding to common industrial data characteristics are then reviewed. Finally, the challenges and possible solutions for actual industrial applications are discussed.
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5
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Wang Y, He Y, Gu D. Quality oriented multimode processes monitoring based on a novel hierarchical common and specific structure with different order information. Chin J Chem Eng 2021. [DOI: 10.1016/j.cjche.2020.09.067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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6
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Li L, Wang Y, Sun B, Qian Y. Operating Performance Assessment for Transition State of Industrial Processes. Chem Eng Technol 2020. [DOI: 10.1002/ceat.201900657] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Ling Li
- Central South University School of Automation Institute of Control Engineering 932 South Lushan Road 410083 Changsha China
| | - Yalin Wang
- Central South University School of Automation Institute of Control Engineering 932 South Lushan Road 410083 Changsha China
| | - Bei Sun
- Central South University School of Automation Institute of Control Engineering 932 South Lushan Road 410083 Changsha China
| | - Yingcan Qian
- Central South University School of Automation Institute of Control Engineering 932 South Lushan Road 410083 Changsha China
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7
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Zheng Y, Wang Y, Yan H, Wang Y, Yang W, Tao B. Density peaks clustering‐based steady/transition mode identification and monitoring of multimode processes. CAN J CHEM ENG 2020. [DOI: 10.1002/cjce.23778] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Ying Zheng
- The Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China
| | - Yang Wang
- The Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China
| | - Haolan Yan
- The Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China
| | - Yan Wang
- School of Electrical and Information Engineering Zhengzhou University of Light Industry Zhengzhou China
| | - Weidong Yang
- The Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China
| | - Bo Tao
- The State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China
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8
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Zou X, Zhao C, Gao F. Linearity Decomposition-Based Cointegration Analysis for Nonlinear and Nonstationary Process Performance Assessment. Ind Eng Chem Res 2020. [DOI: 10.1021/acs.iecr.9b05600] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Xiaoyu Zou
- State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China
| | - Chunhui Zhao
- State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, China
| | - Furong Gao
- Department of Chemical and Biomolecular Engineering, The Hong Kong University of Science and Technology, Hong Kong, Hong Kong
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9
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Gao Z, Jia M, Mao Z, Zhao L. Transitional phase modeling and monitoring with respect to the effect of its neighboring phases. Chem Eng Res Des 2019. [DOI: 10.1016/j.cherd.2019.03.023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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10
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Operation optimization research of circulating cooling water system based on superstructure and domain knowledge. Chem Eng Res Des 2019. [DOI: 10.1016/j.cherd.2018.12.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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11
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Liu Y, Wang F, Gao F, Cui H. Hierarchical Multiblock T-PLS Based Operating Performance Assessment for Plant-Wide Processes. Ind Eng Chem Res 2018. [DOI: 10.1021/acs.iecr.8b02685] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Yan Liu
- College of Information Science & Engineering, Northeastern University, Shenyang, Liaoning 110819, China
- State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, Liaoning 110819, China
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Fuli Wang
- College of Information Science & Engineering, Northeastern University, Shenyang, Liaoning 110819, China
- State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, Liaoning 110819, China
| | - Furong Gao
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Haonan Cui
- Zhongxing Telecommunication Equipment Corporation, Shenzhen, Guangdong 518000, China
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12
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Chang Y, Zou X, Wang F, Zhao L, Zheng W. Multi-mode plant-wide process operating performance assessment based on a novel two-level multi-block hybrid model. Chem Eng Res Des 2018. [DOI: 10.1016/j.cherd.2018.05.023] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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13
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Liu Y, Ma R, Wang F, Chang Y, Gao F. Inner-phase and inter-phase analysis based operating performance assessment and nonoptimal cause identification for multiphase batch processes. Chem Eng Res Des 2018. [DOI: 10.1016/j.cherd.2018.04.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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14
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He Y, Zhou L, Ge Z, Song Z. Dynamic mutual information similarity based transient process identification and fault detection. CAN J CHEM ENG 2018. [DOI: 10.1002/cjce.23102] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Yuchen He
- College of Mechanical and Electrical Engineering; China JiLiang University; Hangzhou 310018 Zhejiang P. R. China
- State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering; Zhejiang University; Hangzhou 310027 Zhejiang P. R. China
| | - Le Zhou
- School of Automation and Electrical Engineering; Zhejiang University of Science and Technology; Hangzhou 310023 Zhejiang P. R. China
| | - Zhiqiang Ge
- State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering; Zhejiang University; Hangzhou 310027 Zhejiang P. R. China
| | - Zhihuan Song
- State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering; Zhejiang University; Hangzhou 310027 Zhejiang P. R. China
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15
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Wang L, Yang C, Sun Y. Multimode Process Monitoring Approach Based on Moving Window Hidden Markov Model. Ind Eng Chem Res 2017. [DOI: 10.1021/acs.iecr.7b03600] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Lin Wang
- State Key Laboratory of Industrial
Control Technology, Institute of Industrial Process Control, Zhejiang University, Hangzhou, Zhejiang 310027, P. R. China
| | - Chunjie Yang
- State Key Laboratory of Industrial
Control Technology, Institute of Industrial Process Control, Zhejiang University, Hangzhou, Zhejiang 310027, P. R. China
| | - Youxian Sun
- State Key Laboratory of Industrial
Control Technology, Institute of Industrial Process Control, Zhejiang University, Hangzhou, Zhejiang 310027, P. R. China
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16
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Ha D, Ahmed U, Pyun H, Lee CJ, Baek KH, Han C. Multi-mode operation of principal component analysis with k-nearest neighbor algorithm to monitor compressors for liquefied natural gas mixed refrigerant processes. Comput Chem Eng 2017. [DOI: 10.1016/j.compchemeng.2017.05.029] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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17
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Qin Y, Zhao C, Zhang S, Gao F. Multimode and Multiphase Batch Processes Understanding and Monitoring Based on between-Mode Similarity Evaluation and Multimode Discriminative Information Analysis. Ind Eng Chem Res 2017. [DOI: 10.1021/acs.iecr.7b02981] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Yan Qin
- State
Key Laboratory of Industrial Control Technology, College of Control
Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Chunhui Zhao
- State
Key Laboratory of Industrial Control Technology, College of Control
Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Shumei Zhang
- State
Key Laboratory of Industrial Control Technology, College of Control
Science and Engineering, Zhejiang University, Hangzhou 310027, China
| | - Furong Gao
- Department
of Chemical and Biomolecular Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong Special Administration Region
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18
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Jiang H, Wang R, Gao J, Gao Z, Gao X. Evidence fusion-based framework for condition evaluation of complex electromechanical system in process industry. Knowl Based Syst 2017. [DOI: 10.1016/j.knosys.2017.03.011] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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19
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Liu Y, Wang F, Chang Y. Operating optimality assessment and nonoptimal cause identification for multimode industrial process with transitions. CAN J CHEM ENG 2016. [DOI: 10.1002/cjce.22513] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Yan Liu
- College of Information Science & Engineering; Northeastern University; Shenyang Liaoning, 110819 China
| | - Fuli Wang
- College of Information Science & Engineering; Northeastern University; Shenyang Liaoning, 110819 China
- State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University); Shenyang Liaoning, 110819 China
| | - Yuqing Chang
- College of Information Science & Engineering; Northeastern University; Shenyang Liaoning, 110819 China
- State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University); Shenyang Liaoning, 110819 China
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20
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Wang F, Tan S, Yang Y, Shi H. Hidden Markov Model-Based Fault Detection Approach for a Multimode Process. Ind Eng Chem Res 2016. [DOI: 10.1021/acs.iecr.5b04777] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Fan Wang
- Key Laboratory of Advanced
Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
| | - Shuai Tan
- Key Laboratory of Advanced
Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
| | - Yawei Yang
- Key Laboratory of Advanced
Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
| | - Hongbo Shi
- Key Laboratory of Advanced
Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
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21
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Zhang S, Wang F, Zhao L, Wang S, Chang Y. A Novel Strategy of the Data Characteristics Test for Selecting a Process Monitoring Method Automatically. Ind Eng Chem Res 2016. [DOI: 10.1021/acs.iecr.5b03525] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Shumei Zhang
- College of Information Science & Engineering and ‡Northeastern University Stat Key Laboratory of Integrated Automation of Process Industry Technology and Research Center of National Metallurgical Automation, Northeastern University, Shenyang, Liaoning 110819, P. R. China
| | - Fuli Wang
- College of Information Science & Engineering and ‡Northeastern University Stat Key Laboratory of Integrated Automation of Process Industry Technology and Research Center of National Metallurgical Automation, Northeastern University, Shenyang, Liaoning 110819, P. R. China
| | - Luping Zhao
- College of Information Science & Engineering and ‡Northeastern University Stat Key Laboratory of Integrated Automation of Process Industry Technology and Research Center of National Metallurgical Automation, Northeastern University, Shenyang, Liaoning 110819, P. R. China
| | - Shu Wang
- College of Information Science & Engineering and ‡Northeastern University Stat Key Laboratory of Integrated Automation of Process Industry Technology and Research Center of National Metallurgical Automation, Northeastern University, Shenyang, Liaoning 110819, P. R. China
| | - Yuqing Chang
- College of Information Science & Engineering and ‡Northeastern University Stat Key Laboratory of Integrated Automation of Process Industry Technology and Research Center of National Metallurgical Automation, Northeastern University, Shenyang, Liaoning 110819, P. R. China
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22
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Quiñones-Grueiro M, Prieto-Moreno A, Llanes-Santiago O. Modeling and Monitoring for Transitions Based on Local Kernel Density Estimation and Process Pattern Construction. Ind Eng Chem Res 2016. [DOI: 10.1021/acs.iecr.5b03902] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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23
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Operating optimality assessment and nonoptimal cause identification for non-Gaussian multimode processes with transitions. Chem Eng Sci 2015. [DOI: 10.1016/j.ces.2015.06.016] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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24
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Zhang S, Wang F, Tan S, Wang S, Chang Y. Novel Monitoring Strategy Combining the Advantages of the Multiple Modeling Strategy and Gaussian Mixture Model for Multimode Processes. Ind Eng Chem Res 2015. [DOI: 10.1021/acs.iecr.5b00373] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
| | | | - Shuai Tan
- Key
Laboratory of Advanced Control and Optimization for Chemical Processes
of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
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25
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Liu Y, Wang F, Chang Y, Ma R. Comprehensive economic index prediction based operating optimality assessment and nonoptimal cause identification for multimode processes. Chem Eng Res Des 2015. [DOI: 10.1016/j.cherd.2015.03.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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26
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Li S, Zhou X, Shi H, Qiao Z, Zheng Z. Monitoring of Multimode Processes Based on Subspace Decomposition. Ind Eng Chem Res 2015. [DOI: 10.1021/ie504730x] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | | | | | - Zhi Qiao
- NUS
Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, 117456, Republic of Singapore
- Department
of Physics and Centre for Computational Science and Engineering, National University of Singapore, Singapore, 117542, Republic of Singapore
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27
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Song B, Shi H, Ma Y, Wang J. Multisubspace Principal Component Analysis with Local Outlier Factor for Multimode Process Monitoring. Ind Eng Chem Res 2014. [DOI: 10.1021/ie502344q] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Bing Song
- Key Laboratory of Advanced
Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
| | - Hongbo Shi
- Key Laboratory of Advanced
Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
| | - Yuxin Ma
- Key Laboratory of Advanced
Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
| | - Jianping Wang
- Key Laboratory of Advanced
Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
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28
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Miao A, Ge Z, Song Z, Zhou L. Time Neighborhood Preserving Embedding Model and Its Application for Fault Detection. Ind Eng Chem Res 2013. [DOI: 10.1021/ie400854f] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Aimin Miao
- State Key
Laboratory of Industrial
Control Technology, Institute of Industrial Process Control, Department
of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, P. R.China
| | - Zhiqiang Ge
- State Key
Laboratory of Industrial
Control Technology, Institute of Industrial Process Control, Department
of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, P. R.China
| | - Zhihuan Song
- State Key
Laboratory of Industrial
Control Technology, Institute of Industrial Process Control, Department
of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, P. R.China
| | - Le Zhou
- State Key
Laboratory of Industrial
Control Technology, Institute of Industrial Process Control, Department
of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, P. R.China
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29
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Ma H, Hu Y, Shi H. Fault Detection and Identification Based on the Neighborhood Standardized Local Outlier Factor Method. Ind Eng Chem Res 2013. [DOI: 10.1021/ie302042c] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Hehe Ma
- Key Laboratory
of Advanced Control and Optimization
for Chemical Processes of the Ministry of Education, East China University of Science and Technology, Shanghai
200237, P.R. China
| | - Yi Hu
- Key Laboratory
of Advanced Control and Optimization
for Chemical Processes of the Ministry of Education, East China University of Science and Technology, Shanghai
200237, P.R. China
| | - Hongbo Shi
- Key Laboratory
of Advanced Control and Optimization
for Chemical Processes of the Ministry of Education, East China University of Science and Technology, Shanghai
200237, P.R. China
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