자료융합에 의한 고정식 해양구조물의 준실시간 연속 비정상 변형율 예측

Title
자료융합에 의한 고정식 해양구조물의 준실시간 연속 비정상 변형율 예측
Alternative Title
Quasi real-time and continuous non-stationary strain estimation in bottom-fixed offshore structures by multimetric data fusion
Author(s)
RP Palanisamy; 정병진; 심성한; 이진학
KIOST Author(s)
Yi, Jin-Hak(이진학)
Alternative Author(s)
정병진; 이진학
Publication Year
2018-08-29
Abstract
Offshore structures are generally exposed to harsh environments such as strong tidal currents and wind loadings. Monitoring the structural soundness and integrity of offshore structures is crucial to prevent catastrophic collapses and to prolong their lifetime however, it is intrinsically challenging because of the difficulties in accessing the critical structural members that are located under water for installing and repairing sensors and data acquisition systems. Virtualsensing technologies have the potential to alleviate such difficulties by estimating the unmeasured structural responses at the desired locations using other measured responses. Despite the usefulness of virtual sensing, its performance and applicability to the structural health monitoring of offshore structures have not been fully studied to date. This study investigates the use of virtual sensing of offshore structures. A Kalman filter based virtual sensing algorithm is developed to estimate responses at the location of interest. Further, this algorithm performs a multi-sensor data fusion to improve the estimation accuracy under non-stationary tidal loading. Numerical analysis and laboratory experiments are conducted to verify the performance of the virtual sensing strategy using a bottom-fixed offshore structural model. Numerical and experimental results show that the unmeasured responses can be reasonably recovered from the measured responses
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23155
Bibliographic Citation
The 2018 World Congress on Advances in Civil, Environmental, & Materials Research (ACEM18), pp.1 - 9, 2018
Publisher
Int'l Association of Structural Engineering & Mechanics (IASEM)
Type
Conference
Language
English
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