Dynamic Batch Process Monitoring Based on Time-Slice Latent Variable Correlation Analysis-Reference-Cited by-同舟云学术

Dynamic Batch Process Monitoring Based on Time-Slice Latent Variable Correlation Analysis

Published:2022-10-31 Issue:45 Volume:7 Page:41069-41081
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Du Le¹²,Jin Wenhao¹,Wang Yang³,Jiang Qingchao¹²^ORCID

Affiliation:

1. Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China

2. Key Laboratory of Complex System Safety and Control, Ministry of Education, Chongqing University, Chongqing 400044, P. R. China

3. School of Electric Engineering, Shanghai Dianji University, Shanghai 200240, P. R. China

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Shanghai Rising-Star Program

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c04445

Reference38 articles.

1. Data-driven methods for batch data analysis – A critical overview and mapping on the complexity scale

2. Optimal selection of time resolution for batch data analysis. Part I: Predictive modeling

3. Batch Process Modeling and Monitoring With Local Outlier Factor

4. A Survey of Fault Diagnosis and Fault-Tolerant Techniques—Part I: Fault Diagnosis With Model-Based and Signal-Based Approaches

5. A Review on Basic Data-Driven Approaches for Industrial Process Monitoring

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