Statistical Monitoring and Fault Diagnosis of Batch Processes Using Two-Dimensional Dynamic Information-Reference-Cited by-同舟云学术

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Statistical Monitoring and Fault Diagnosis of Batch Processes Using Two-Dimensional Dynamic Information

Published:2010-10-20 Issue:20 Volume:49 Page:9961-9969
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Yao Yuan,Gao Furong

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ie100860x

Cited by 9 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. Dynamic Batch Process Monitoring Based on Time-Slice Latent Variable Correlation Analysis;ACS Omega;2022-10-31

2. Simplified Granger causality map for data-driven root cause diagnosis of process disturbances;Journal of Process Control;2020-11

3. Data-Driven Two-Dimensional Deep Correlated Representation Learning for Nonlinear Batch Process Monitoring;IEEE Transactions on Industrial Informatics;2020-04

4. Multiobjective Two-Dimensional CCA-Based Monitoring for Successive Batch Processes With Industrial Injection Molding Application;IEEE Transactions on Industrial Electronics;2019-05

5. Distributed Supervised Fault Detection and Diagnosis for a Non-Gaussian Process;Industrial & Engineering Chemistry Research;2019-03-25

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