Structural health monitoring study demonstrates baseline dynamic property identification in a historic masonry pagoda, highlighting reliable assessment through low-amplitude seismic segmentation.
Historical structures are inherently prone to degradation, necessitating structural health monitoring for their preservation. This study proposes an inverse analysis methodology to determine structural dynamic properties, offering insights into fundamental behavior. The algorithm integrates Newmark’s time-stepping method with the Gauss-Newton scheme for improved accuracy. Its effectiveness is demonstrated using four seismic datasets from distant earthquakes. A Historic Masonry Pagoda in Chiang Mai, Thailand, was monitored via segmental low-amplitude earthquake data. Two 3-directional vibration sensors at the top and base recorded responses during seismic events. Given the low amplitude, each 120-s event was divided into twelve segments for enhanced analysis. The results show that segmenting seismic waves increases output data, reducing uncertainties through probabilistic techniques. As the pagoda’s structural properties remain partially unknown, the derived dynamic properties establish a baseline for future assessments of deterioration.
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Hansapinyo et al. (2025) studied this question.
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