Large-scale on-line sensor fault detection and signal reconstruction in nuclear power plants
Gola, G. , Roverso, D.International Congress on Condition Monitoring and Diagnostics Engineering Management (COMADEM), 24, Stavanger, 2011-05-30--06-01. Proceedings /ed. by Maneesh Singh et al. - COMADEM International, U.K. - ISBN 0-9541307-2-3
- Publ. year
- Publ. type
- On-line sensor monitoring and diagnostics systems aim at detecting anomalies in sensors and reconstructing their correct signals during operation. Since 1994, research at the OECD Halden Reactor Project has focused on the problem of sensor monitoring and diagnostics, eventually leading to the development of the PEANO system for signal validation and reconstruction. PEANO combines empirical techniques like Fuzzy Clustering and Auto-Associative Neural Networks and has proved to be successful in a variety of practical applications. Nevertheless, using one single empirical model sets a limit to the number of signals that can be handled at a time. Recently, efforts have been made to extend the applicability of PEANO to the whole plant, which requires the validation and reconstruction of thousands of signals. This has entailed moving from a single-model to a model-ensemble approach. This paper presents the model-based ensemble approach hereby developed for plant-wide sensor monitoring and signal reconstruction and a practical application of the method to the reconstruction of signals measured at a Swedish nuclear power plant.