TY - GEN
T1 - Dynamic Processes Modeling and Monitoring based on a Novel Dynamic Latent Variable Model
AU - Zhou, Le
AU - Ge, Zhiqiang
AU - Song, Zhihuan
AU - Qin, S. Joe
PY - 2019/7
Y1 - 2019/7
N2 - For dynamic process modeling and monitoring purpose, it is desirable to extract both the auto-correlations and the cross-correlations in measurements. Besides, the proposed dynamic model is also expected to provide an accurate prediction, visualization and an explicit interpretation of the data structures. From this perspective, the dynamic latent variable model is more suitable compared to the traditional dynamic principal component analysis (DPCA). In this paper, a novel independent dynamic latent variable model is proposed to explicitly extract several independent dynamic latent variables with which to capture process dynamics in the measurements. The proposed model is derived in the probabilistic framework and the model parameters are estimated via the expectation-maximum algorithm. Finally, a case study is illustrated to evaluate the performance of the proposed method for dynamic modeling and process monitoring.
AB - For dynamic process modeling and monitoring purpose, it is desirable to extract both the auto-correlations and the cross-correlations in measurements. Besides, the proposed dynamic model is also expected to provide an accurate prediction, visualization and an explicit interpretation of the data structures. From this perspective, the dynamic latent variable model is more suitable compared to the traditional dynamic principal component analysis (DPCA). In this paper, a novel independent dynamic latent variable model is proposed to explicitly extract several independent dynamic latent variables with which to capture process dynamics in the measurements. The proposed model is derived in the probabilistic framework and the model parameters are estimated via the expectation-maximum algorithm. Finally, a case study is illustrated to evaluate the performance of the proposed method for dynamic modeling and process monitoring.
KW - Dynamic modelling
KW - Independent Dynamic Latent Variable
KW - Process Monitoring
UR - http://www.scopus.com/inward/record.url?scp=85094662259&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85094662259&origin=recordpage
U2 - 10.1109/SAFEPROCESS45799.2019.9213443
DO - 10.1109/SAFEPROCESS45799.2019.9213443
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781728106823
T3 - Proceedings of ... CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes, SAFEPROCESS
SP - 589
EP - 595
BT - 2019 CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS 2019)
PB - IEEE
T2 - 11th CAA Symposium on Fault Detection, Supervision, and Safety for Technical Processes (SAFEPROCESS 2019)
Y2 - 5 July 2019 through 7 July 2019
ER -