Name
Title | ||
|---|---|---|
Multimode Process Monitoring Based on Switching Autoregressive Dynamic Latent Variable Model. |
Abstract | ||
|---|---|---|
In most industrials, the dynamic characteristics are very common and should be paid enough attention for process control and monitoring purposes. As a high-order Bayesian network model, autoregressive dynamic latent variable (ARDLV) is able to effectively extract both autocorrelations and cross-correlations in data for a dynamic process. However, the operating conditions will be frequently changed... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TIE.2018.2803727 | IEEE Transactions on Industrial Electronics |
Keywords | Field | DocType |
Hidden Markov models,Switches,Monitoring,Process control,Numerical models,Principal component analysis,Adaptation models | Autoregressive model,Control theory,Fault detection and isolation,Latent variable model,Latent variable,Bayesian network,Process control,Production line,Engineering,Hidden Markov model | Journal |
Volume | Issue | ISSN |
65 | 10 | 0278-0046 |
Citations | PageRank | References |
1 | 0.35 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Le Zhou | 1 | 10 | 2.22 |
| Jiaqi Zheng | 2 | 1 | 0.35 |
| Zhiqiang Ge | 3 | 140 | 29.81 |
| Zhi-huan Song | 4 | 147 | 30.60 |
| Shengdao Shan | 5 | 1 | 0.35 |