Sparse Reconstruction-Based Contribution for Multiple Fault Isolation by KPCA
| Autor: | Kwami Anani, Gilles Mourot, Maya Kallas, Didier Maquin |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Optimization problem
Computer science Multiplicative function Process (computing) Continuous stirred-tank reactor Initialization 02 engineering and technology Fault (power engineering) Kernel principal component analysis 03 medical and health sciences 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Isolation (database systems) Algorithm 030217 neurology & neurosurgery |
| Zdroj: | MED |
| DOI: | 10.1109/med.2018.8442938 |
| Popis: | This paper addresses the problem of multiple fault isolation based on kernel principal component analysis and proposes a sparse fault estimation method to evaluate the reconstruction-based contribution. The fault magnitude estimation is here formulated as an optimization problem under nonnegativity and sum-to-one constraints. A multiplicative iterative scheme and its initialization procedure are proposed to solve it. The effectiveness of the proposed method is demonstrated on the simulated continuous stirred tank reactor (CSTR) process. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|