Decentralized Fault Diagnosis of Continuous Annealing Processes Based on Multilevel PCA
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 687-698 |
| Journal / Publication | IEEE Transactions on Automation Science and Engineering |
| Volume | 10 |
| Issue number | 3 |
| Online published | 24 Jan 2013 |
| Publication status | Published - Jul 2013 |
| Externally published | Yes |
Link(s)
Abstract
Process monitoring and fault diagnosis of the continuous annealing process lines (CAPLs) have been a primary concern in industry. Stable operation of the line is essential to final product quality and continuous processing of the upstream and downstream materials. In this paper, amultilevel principal component analysis (MLPCA)-based fault diagnosis method is proposed to provide meaningful monitoring of the underlying process and help diagnose faults. First, multiblock consensus principal component analysis (CPCA) is extended to MLPCA to model the large scale continuous annealing process. Secondly, a decentralized fault diagnosis approach is designed based on the proposed MLPCA algorithm. Finally, experiment results on an industrial CAPL are obtained to demonstrate the effectiveness of the proposed method. © 2012 IEEE.
Research Area(s)
- Fault diagnosis, Industrial processes, Principal component analysis (PCA), Process monitoring
Citation Format(s)
Decentralized Fault Diagnosis of Continuous Annealing Processes Based on Multilevel PCA. / Liu, Qiang; Qin, S. Joe; Chai, Tianyou.
In: IEEE Transactions on Automation Science and Engineering, Vol. 10, No. 3, 07.2013, p. 687-698.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
