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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 국제구조공학회 Structural Engineering and Mechanics, An Int'l Journal Structural Engineering and Mechanics, An Int'l Journal Vol.79 No.3
- 발행연도
- 2021.1
- 수록면
- 327 - 336 (10page)
이용수
초록· 키워드
오류제보하기
Most of the existing output-only damage detection methods require the number of sensors should be larger than the number of unknown excitation force, and the force location should be available. This paper presents a novel output-only damage detection method without these requirements. The proposed method is based on the correlation function of acceleration responses. When the structure is under white noise excitations (or ambient excitations), the correlation function of acceleration responses can be treated as free vibration responses with unknown initial conditions. The unknown structural parameters and initial conditions can be simultaneously identified by minimizing the difference between the measured and calculated correlation functions. The unknown initial conditions are identified with state space method and the unknown structural parameters are updated with sensitivity method. Numerical studies of a 2D truss and a five-bay 3D frame structure are conducted to demonstrate the accuracy, effectiveness, and robustness of the proposed method. Experimental studies on an eight-floor steel frame are further carried out. Results show that the proposed method is not only insensitive to environmental noise but also applicable when the number of sensors is less than that of unknown excitations. Also, the proposed method can be used for damage detection when the force location is unknown.
목차
등록된 정보가 없습니다.
참고문헌 (17)
참고문헌 신청
Bernal, D. / 2013 / Kalman filter damage detection in the presence of changing process and measurement noise / Mech. Syst. Signal Pr. 39(1-2):361~371
Caicedo, J. M. / 2004 / Natural excitation technique and eigensystem realization algorithm for phase I of the IASC-ASCE benchmark problem : Simulated data / J. Eng. Mech 130(1):49~60
Chu, S. Y. / 2011 / Application of the on-line recursive least-squares method to perform structural damage assessment / Struct. Control Hlth. Monit 18(3):241~264
Ghiasi, R. / 2016 / A machinelearning approach for structural damage detection using least square support vector machine based on a new combinational kernel function / Struct. Hlth. Monit 15(3):302~316
Gobbato, M. / 2014 / A recursive Bayesian approach for fatigue damage prognosis : An experimental validation at the reliability component level / Mech. Syst. Signal Pr 45(2):448~467
Caicedo, J. M. / 2004 / Natural excitation technique and eigensystem realization algorithm for phase I of the IASC-ASCE benchmark problem : Simulated data / J. Eng. Mech 130(1):49~60
Chu, S. Y. / 2011 / Application of the on-line recursive least-squares method to perform structural damage assessment / Struct. Control Hlth. Monit 18(3):241~264
Ghiasi, R. / 2016 / A machinelearning approach for structural damage detection using least square support vector machine based on a new combinational kernel function / Struct. Hlth. Monit 15(3):302~316
Gobbato, M. / 2014 / A recursive Bayesian approach for fatigue damage prognosis : An experimental validation at the reliability component level / Mech. Syst. Signal Pr 45(2):448~467
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