|
|
|
| Nonlinear Dynamic Fault Detection Method Based on Isometric Mapping |
| ZHANG Ni, TIAN Xue-Min |
(College of Information and Control Engineering, China University of Petroleum,
Dongying 257061, Shandong, China) |
|
|
|
|
Abstract The data collected from chemical process are strongly nonlinear and dynamic related. To solve this problem, a nonlinear dynamic fault detection method using dynamic isometric mapping (DISOMAP) manifold learning was proposed. It first extracts submanifold feature from original data set with adaptive neighbor parameters, which preserves geometric structure. Then linear regression projection mapping which maps the original high dimension space to a low dimension embedding space is used. Finally, T2 and SPE statistics are constructed in the process monitoring application. The simulation results of Tennessee Eastman process show that DISOMAP-based method is more effective than KPCA (kernel principal component analysis) for process monitoring and fault detection.
|
|
Published: 30 August 2011
|
|
|
|
|
|
| No related articles found! |
|
|
|
|
