Abstract
In this paper, a data-driven multiblock concurrent projection to latent structures (CPLS) method is proposed for monitoring large-scale manufacturing lines, particularly for cold rolling continuous annealing processes (CAPs) fault diagnosis. The proposed method provides decentralized process monitoring and helps localize faults in both input variables and output variables concurrently. First, the CPLS-based process monitoring method is briefly reviewed. Second, a multiblock CPLS algorithm, which incorporates process block partition, is proposed to diagnose faults relevant to process inputs or outputs with a decentralized structure. For the CAP line application, tension-specific variations, roll-specific variations, and tension-roll covariations are analyzed in each partitioned block. Furthermore, within the roll-specific subspace of an abnormal block, a delay-alignment scheme based on strip transportation delay is proposed to diagnose defective processing materials. © 1982-2012 IEEE.
| Original language | English |
|---|---|
| Article number | 6729046 |
| Pages (from-to) | 6429-6437 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Industrial Electronics |
| Volume | 61 |
| Issue number | 11 |
| Early online date | 30 Jan 2014 |
| DOIs | |
| Publication status | Published - Nov 2014 |
| Externally published | Yes |
Funding
This work was supported in part by the Natural Science Foundation of China under Grant 61304107, Grant 61020106003, Grant 61290323, and Grant 61104084, in part by the China Postdoctoral Science Foundation funded project under Grant 2013M541242, in part by the International Postdoctoral Exchange Fellowship Program, in part by the Fundamental Research Funds for the Central Universities under Grant N130408002, and in part by the Integrated Automation of Process Industry (IAPI) Fundamental Research Funds under Grant 2013ZCX04 and Grant 2013ZCX05.