1. Reconstruction based fault prognosis for continuous processes
- Author
-
Li, Gang, Qin, S. Joe, Ji, Yindong, and Zhou, Donghua
- Subjects
- *
MULTIVARIATE analysis , *CONTINUOUS functions , *TIME series analysis , *PREDICTION models , *WAVELETS (Mathematics) , *PRINCIPAL components analysis , *ESTIMATION theory - Abstract
Abstract: In this paper, a multivariate fault prognosis approach for continuous processes with hidden faults is proposed based on statistical process monitoring methods and multivariate time series prediction. It is assumed that the fault is a slowly time-varying autocorrelated process and can be completely reconstructed. Fault magnitude is estimated first via reconstruction, then predicted by a vector AR model with wavelet based denoising. Given the fault direction, a new index is proposed to detect the fault, which integrates fault detection and prognosis together. Case studies on a continuous stirred tank reactor and the Tennessee Eastman process demonstrate the effectiveness of the proposed approaches. [Copyright &y& Elsevier]
- Published
- 2010
- Full Text
- View/download PDF