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논문 기본 정보

자료유형
학술저널
저자정보
Yi, Ting-Hua (School of Civil Engineering, Faculty of Infrastructure Engineering, Dalian University of Technology) Li, Hong-Nan (School of Civil Engineering, Faculty of Infrastructure Engineering, Dalian University of Technology) Gu, Ming (State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University)
저널정보
테크노프레스 Smart structures and systems Smart structures and systems 제11권 제4호
발행연도
2013.1
수록면
331 - 348 (18page)

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Effective monitoring, reliable data analysis, and rational data interpretations are challenges for engineers who are specialized in bridge health monitoring. This paper demonstrates how to use the Global Positioning System (GPS) and accelerometer data to accurately extract static and quasi-static displacements of the bridge induced by ambient effects. To eliminate the disadvantages of the two separate units, based on the characteristics of the bias terms derived from the GPS and accelerometer respectively, a wavelet based multi-step filtering method by combining the merits of the continuous wavelet transform (CWT) with the discrete stationary wavelet transform (SWT) is proposed so as to address the GPS deformation monitoring application more efficiently. The field measurements are carried out on an existing suspension bridge under the normal operation without any traffic interference. Experimental results showed that the frequencies and absolute displacements of the bridge can be accurate extracted by the proposed method. The integration of GPS and accelerometer can be used as a reliable tool to characterize the dynamic behavior of large structures such as suspension bridges undergoing environmental loads.

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