Quality-Relevant Fault Monitoring Based on Locally Linear Embedding Orthogonal Projection to Latent Structure
| Autor: | Jing Wang, Jisheng Zhou, Y. W. Ren |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer science
General Chemical Engineering Orthographic projection Statistical model 02 engineering and technology General Chemistry 021001 nanoscience & nanotechnology Linear subspace Industrial and Manufacturing Engineering Expression (mathematics) Nonlinear system 020401 chemical engineering Benchmark (computing) 0204 chemical engineering 0210 nano-technology Projection (set theory) Algorithm Subspace topology |
| Zdroj: | Industrial & Engineering Chemistry Research. 58:1262-1272 |
| ISSN: | 1520-5045 0888-5885 |
| Popis: | A novel statistical model based on a locally linear embedding projection to latent structure (LLEPLS) is proposed, which not only has a concise expression and similar analytical solutions to the projection to latent structure (PLS) model but also has the ability to maintain the local geometric structure of the locally linear embedding (LLE) model. Furthermore, to eliminate the adverse effects of oblique decomposition, a locally linear embedding orthogonal projection to latent structure (LLEOPLS) model is also proposed. The input and output data spaces are projected to three subspaces, namely, a joint input–output subspace that captures the nonlinear relationship between the input and output, an output-residual subspace that monitors the unpredictable output faults, and an orthogonal input-residual subspace that detects the quality-irrelevant faults. Then, the corresponding monitoring strategies are established based on the LLEPLS and LLEOPLS models. The Tennessee Eastman process (TEP) benchmark is used to... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|