The reliability of steam generators in nuclear power plants has always been a challenging issue. Various diagnostic models have been proposed in the literature. However, no work has been reported on the development of a robust prediction model for forecasting the future health state of steam generators. In this paper, we propose an ARIMA-based prognostic approach for tracking the degradation evolution in a steam generator and further predicting its Remaining Useful Life (RUL) before breakdown. A case study concerning real degradation datasets from different steam generators is extensively investigated to validate the performance of the proposed model.

A Data-Driven Approach for Predicting the Remaining Useful Life of Steam Generators

Zio E.;
2019-01-01

Abstract

The reliability of steam generators in nuclear power plants has always been a challenging issue. Various diagnostic models have been proposed in the literature. However, no work has been reported on the development of a robust prediction model for forecasting the future health state of steam generators. In this paper, we propose an ARIMA-based prognostic approach for tracking the degradation evolution in a steam generator and further predicting its Remaining Useful Life (RUL) before breakdown. A case study concerning real degradation datasets from different steam generators is extensively investigated to validate the performance of the proposed model.
2019
Proceedings - 2018 3rd International Conference on System Reliability and Safety, ICSRS 2018
978-1-7281-0238-2
ARIMA; nuclear power plant; prognostics and health management; remaining useful life; steam generators
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1122908
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