Leakage Detection by Adaptive Process Modeling


Jaakko Talonen, Miki Sirola, and Jukka Parviainen. Leakage Detection by Adaptive Process Modeling. In Proceedings of DMIN'08, pages 49 – 52, 2008.


In this paper, we propose an adaptive linear approach for time series modeling and steam line leakage detection. Weighted recursive least squares (WRLS) method is used for modeling. Interpretive variables of an adaptive model should be linearly correlated to ensure a robust model. In this paper it is ensured by examining eigenvalues and eigenvectors of the principal component analysis (PCA). The method is applied to a time series from the boiling water reactor (BWR) type nuclear power plant. Model is updated and used each time step to detect leakage in steam lines. Developed leakage detection index is based on the model estimation error. Method is more convincing in small pipe flows, because there are other ways to detect bigger volume leakages.

Suggested BibTeX entry:

    author = {Jaakko Talonen and Miki Sirola and Jukka Parviainen},
    booktitle = {Proceedings of DMIN'08},
    pages = {49 -- 52},
    title = {{Leakage Detection by Adaptive Process Modeling}},
    year = {2008},

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