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        검색결과 2

        1.
        2017.06 KCI 등재 구독 인증기관 무료, 개인회원 유료
        The paper presents a new short-term dynamic displacement estimation method based on an acceleration and a geophone sensor. The proposed method combines acceleration and velocity measurements through a real time data fusion algorithm based on Kalman filter. The proposed method can estimate the displacement of a structure without displacement sensors, which is typically difficult to be applied to earthquake or fire sites due to their requirement of a fixed rigid support. The proposed method double-integrates the acceleration measurement recursively, and corrects an accumulated integration error based on the velocity measurement, The performance of the proposed method was verified by a lab-scale test, in which displacement estimated by the proposed method are compared to a reference displacement measured by laser doppler vibrometer (LDV).
        4,000원
        2.
        2016.10 서비스 종료(열람 제한)
        Measurement of dynamic displacement of large structure is one of the most challenging issues in structural health monitoring. With a Kalman filter based technique, the proposed displacement measurement system which consists of GPS-RTK, accelerometer, DAQ, and computer shows the huge potential for precise measurement of dynamic displacement of large structure. The performance of the system has been verified by modal shaker test. This paper presents a new system for dynamic and pseudostatic displacement measurement for a large-scale civil infrastructure. Even though dynamic displacement measurement on a large-scale structure is one of the most challenging issues in structural health monitoring, traditional displacement sensors as well as cutting edge noncontact sensors suffers from the lack of accuracy and precision due to field conditions such as measurement distance and requirement for a fixed support. With a Kalman filter based technique, the proposed displacement measurement system, which consists of a GPS-RTK, accelerometer, DAQ and computer, efficiently estimates bias contained in the acceleration record by fusing the acceleration with intermittently recorded GPS-RTK data, and estimate high precision and high accuracy displacement by removing the bias from the acceleration record and conducting double integration. Through a series of lab-scale tests using a vibration exiciter, the performance of the system has been verified and shows the potential for accurate and precise measurement of dynamic displacement of a large-scale structure.