及时地对结构进行健康监测，诊断损伤的位置和程度，估计剩余使用寿命，对结构的全寿命管理、减小灾害损失具有重大意义。大多数结构当受到强激励或破坏时，结构会出现时变或非线性特性。然而，现有大多数损伤识别方法都假设结构是线性时不变系统，识别的结果不能反映结构的时变或非线性过程。本项目拟研究时变性和非线性特征结构的定性和定量的方法。小波函数具有非常好的时频特性，任意有限能量函数都可以有效并准确地用小波多尺度来合成。本课题将针对不同的结构时变性和非线性、响应数据情况，研究一系列基于小波多尺度近似的时变结构识别方法。申请人已有研究结果表明，基于小波多尺度近似的识别方法可以很好地识别和追踪剪切梁模型结构的时变参数。本项目拟拓展研究多层框架结构，深入探究梁、柱和节点性能时变性能的损伤识别方法，并以辅助实验验证方法的适用性。此项研究的发展对今后时变结构健康监测在实际工程结构上的应用有很好的指导作用。

Timely health monitoring of engineering structures and diagnosis of damage location, severity and remaining life have a great significance to their life-cycle management and hazard mitigation. Most structures could exhibit intrinsically time-varying and nonlinear characteristics when subjected to strong excitation or when damaged. However, most existing structural identification techniques assume that the structure is linear and time-invariant which cannot the underlying time-varying and nonlinear behavior if existed. This research proposal is to quantify and/or qualify the time-varying and nonlinear characteristics of structures. It is well known that arbitrary transient functions can be effectively and accurately approximated using wavelet multi-resolution approximation due to its good time-frequency localization property. We will develop series of time-varying structural identification techniques, considering different types of time-varying and nonlinear behaviors. Previous research results of the principal investigator show that the wavelet-based techniques can identify and track the time-varying parameters quite accurately for shear-beam buildings. In this research proposal, we will extend the techniques to general multi-story frame structure considering time-varying and nonlinear damage to beam, column and joints, respectively, along with numerical and experimental verifications. The end results of the research would demonstrate a great potential of practically applicable techniques in the structural health monitoring of time-varying and nonlinear structures.