输入输出信息有限观测下的结构损伤诊断

Structural Damage Detection Technique with Limited Input and Output Measurement Signals

为解决工程结构中外激励和响应信息有限观测情况下的结构损伤诊断问题,提出依次使用扩展卡尔曼估计算法和最小二乘算法,分别识别结构参数和未知外激励,推导出相应的递推解析解。所提方法与经典卡尔曼滤波算法相比,可用于荷载未知情况。通过追踪结构内单元的刚度变化,对结构损伤进行诊断。分别通过一个小型平面桁架、一个简支梁的损伤诊断数值算例和一个8层剪切钢框架的损伤识别试验,验证了该方法的可行性和有效性。

To solve the problem of structural damage detection with limited input and output measurement signals, a technique based on sequential application of the extended Kalman estimator and least-squares estimation is proposed in this paper for the identification of structure parameters and unknown excitations. Compared with the classical extended Kalman filter approach, the proposed technique can be used under unknown excitations. Structural damage can be detected by tracking the changes in the identified values of dynamic parameters at element level, e.g., the degrading of stiffness parameters. Numerical examples of damage detection of a plan truss and a beam in finite element model and experimental study of damage detection of an 8-DOF shear framed building are used to validate the feasibility of proposed technique.