Multirate Factor Analysis Models for Fault Detection in Multirate Processes

Generally, the measurements of modern industries are collected from different sources, which indicates that the traditional multivariate statistical process monitoring methods cannot be directly used in the multirate systems if one aims to utilize the complete multirate measurements. Hence, a set of...

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Bibliographic Details
Published in:IEEE transactions on industrial informatics 2019-07, Vol.15 (7), p.4076-4085
Main Authors: Zhou, Le, Wang, Yaoxin, Ge, Zhiqiang, Song, Zhihuan
Format: Article
Language:English
Subjects:
Algorithms
Anaerobic processes
Analytical models
Computer simulation
EM algorithm
Factor analysis
Fault detection
Informatics
Load modeling
Monitoring
multirate factor analysis
multirate process
Principal component analysis
Probabilistic logic
Statistical methods
Wastewater treatment
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Summary:Generally, the measurements of modern industries are collected from different sources, which indicates that the traditional multivariate statistical process monitoring methods cannot be directly used in the multirate systems if one aims to utilize the complete multirate measurements. Hence, a set of multirate factor analysis models is developed for process modeling and fault detection purpose in the multirate processes. In the proposed model, the cross correlations are described and bounded by the common factors and the model parameters are calibrated using the expectation-maximum algorithms. Also, the proposed models are further discussed both from theoretical and geometric perspective. Finally, the proposed fault detection methods are tested by a simulated Tennessee-Eastman process and a real R2S anaerobic reactor unit in the wastewater treatment process.
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2018.2889750