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Damage Detection for Continuous Bridge Based on Static-Dynamic Condensation and Extended Kalman Filtering

机译:基于静态动态冷凝和扩展卡尔曼滤波的连续桥梁损坏检测

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摘要

As an effective and classical method about physical parameter identification, extended Kalman filtering (EKF) algorithm is widely used in structural damage identification, but the equations and solutions for the structure with bending deformation are not established based on EKF. The degrees of freedom about rotation can be eliminated by the static condensation method, and the dynamic condensation method considering Rayleigh damping is proposed in order to establish the equivalent and simplified modal based on complex finite element model such as continuous girder bridge. According to the requirement of bridge inspection and health monitoring, the online and convenient damage detection method based on EKF is presented. The impact excitation can be generated only on one location by one hammer actuator, and the signal in free vibration is analyzed. The deficiency that the complex excitation information is needed based on the traditional method is overcome. As a numerical example, a three-span continuous girder bridge is simulated, and the corresponding stiffness, the damage location and degree, and the damping parameter are identified accurately. It is verified that the method is suitable for the dynamic signal with high noise-signal ratio; the convergence speed is fast and this method is feasible for application.
机译:作为有关物理参数识别一个有效的和经典方法,扩展卡尔曼滤波(EKF)算法被广泛用于结构损伤识别,但对于弯曲变形的结构方程和溶液不建立了基于EKF。度围绕旋转自由度可通过静态缩合的方法来消除,并且动态缩合方法考虑瑞利衰减,以便建立基于复杂的有限元模型的等效和简化模态诸如连续梁桥提出。根据桥梁检测和健康监测的要求,提出了一种基于扩展卡尔曼滤波的在线便捷的损伤检测方法。冲击激励只能由一个致动器锤的一个位置中产生,并且在自由振动的信号进行分析。不足的是,复杂的激励信息是根据传统的方法需要的是克服。作为一数字例子,一个三跨连续梁桥是模拟,以及相应的刚度,所述损伤的位置和程度,并且阻尼参数被精确地识别。据验证,该方法适用于具有高噪声信号比的动态信号;的收敛速度快,此方法是用于应用可行。

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