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Nuclear power plant PCCV structure monitoring based on BOTDA and its data processing using Kalman filter

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Indexed by:会议论文

Date of Publication:2017-09-12

Journal:11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017

Included Journals:EI、Scopus

Volume:1

Page Number:935-942

Abstract:Because prestressed concrete containment vessel (PCCV) is the last barrier of nuclear power plant (NPP), Brillouin Optical Time Domain Analysis (BOTDA) was used in monitoring PCCV structure. However, the layout of distributed optic fiber sensors was not ideal so that the elongation of optic fiber sensors wasn't uniform. If the monitoring data of a certain time was chosen as a standard, the result of strain variation would have a lot of disturbance points. Facing this problem, Kalman filter was used in data processing. Through Kalman filter, the results were smoother and the disturbance points were eliminated so that the manual work was decreased. As a result, Kalman filter is very useful in BOTDA data processing in the PCCV monitoring.

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