Fuzzy Phase Partition and Hybrid Modeling Based Quality Prediction and Process Monitoring Methods for Multiphase Batch Processes-Reference-Cited by-同舟云学术

Fuzzy Phase Partition and Hybrid Modeling Based Quality Prediction and Process Monitoring Methods for Multiphase Batch Processes

Published:2016-03-30 Issue:14 Volume:55 Page:4045-4058
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Luo Lijia¹²,Bao Shiyi¹,Mao Jianfeng¹,Tang Di¹,Gao Zengliang¹

Affiliation:

1. Institute of Process Equipment and Control Engineering, Engineering Research Center of Process Equipment and Remanufacturing, Ministry of Education, Zhejiang University of Technology, Hangzhou, Zhejiang 310014, China

2. Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.5b04252

Reference27 articles.

1. Multivariate SPC Charts for Monitoring Batch Processes

2. Monitoring batch processes using multiway principal component analysis

3. Tensor Global-Local Preserving Projections for Batch Process Monitoring

4. Statistical monitoring of multistage, multiphase batch processes

5. Online monitoring of batch processes using multi-phase principal component analysis

Cited by 23 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An improved transfer learning approach based on geodesic flow kernel for multiphase batch process soft sensor modeling;Transactions of the Institute of Measurement and Control;2024-02-16

2. Smart batch process: The evolution from 1D and 2D to new 3D perspectives in the era of Big Data;Journal of Process Control;2023-10

3. Multi‐stage fusion regression network for quality prediction of batch process;The Canadian Journal of Chemical Engineering;2023-05-03

4. Automatic segmentation of batch processes into multi-local state-space models for fault detection;Chemical Engineering Science;2023-03

5. Digitization in bioprocessing: The role of soft sensors in monitoring and control of downstream processing for production of biotherapeutic products;Biosensors and Bioelectronics: X;2022-12