Abstract
Fault detection and diagnosis is one of the key technologies on the effective application of multivariate statistical process control(MSPC). In order to overcome the historical fault information using shortage, considering the influence of principal components variable contributions and the reconstructive errors, the synthetical variable contributions were calculated by normalizing and summing these two different variable contributions. A novel MSPC fault detection and diagnosis method was proposed based on the integrated variable contributions, and the relevant algorithm and program were presented and implemented. A case study was illustrated through the Tennessee Eastman challenge process simulation platform. The experimental results demonstrate that the proposed method is feasible and valid.
| Original language | English |
|---|---|
| Pages (from-to) | 1295-1299 |
| Number of pages | 5 |
| Journal | Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics |
| Volume | 38 |
| Issue number | 10 |
| State | Published - Oct 2012 |
Keywords
- Fault detection and diagnosis
- Multivariable control systems
- Quality control
- Statistical process control
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