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基于不完全测量的结构损伤识别研究

     

摘要

自适应序贯非线性最小二乘法是一种新型的损伤识别方法.为了减少结构中传感器的数量,将有限元模型缩聚理论与自适应序贯非线性最小二乘法相结合,用于结构的损伤识别--基于缩聚模型的自适应序贯非线性最小二乘法.为了验证该方法的有效性,对一悬臂梁结构进行了试验研究,研究中考虑了白噪声、正弦、和EL-Centro地震波三种激励下的六种工况.研究结果表明,基于缩聚模型的自适应序贯非线性最小二乘法是一种有效的结构损伤识别方法,根据该方法,只需要使用少量的传感器即可准确地识别出结构中损伤的发生时刻、损伤的程度和位置.%Adaptive sequential nonlinear least-square estimation approach is a new structural damage identification technique. In order to reduce the number of sensors in structure health monitoring system, a reduced-order finite-element approach along with the adaptive sequential nonlinear least-square estimation approach is proposed to identify the local damages of complex structures, which is referred to as the reduced-order finite-element model based adaptive sequential nonlinear least-square estimation approach. To verify the capability of the proposed approach, at first a simulation test was performed on a 3-D truss, and three cases under two excitations were considered, including white noise excitation and EL-Centro earthquake excitation. Then experimental tests were performed on a scaled cantilever beam, and six cases under three excitations were considered, including white noise, sinusoidal, and El-Centro excitation. Simulation and experimental tests indicated that the proposed reduced-order finite-element model based sequential nonlinear least-square estimation approach is an effective structural health monitoring method. By using only a few sensors, the structural damages can be detected accurately, including the location and severity of the damage.

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