荷载是进行结构设计、结构动力优化、结构运营维护及结构健康监测不可或缺的基础数据。荷载识别是测量荷载的重要手段，但Bouc-Wen模型的强非线性以及结构动力学反问题计算的收敛性成为滞回非线性结构荷载识别理论发展的主要瓶颈。本项目以基于Bouc-Wen模型的非线性结构为研究对象，对Bouc-Wen模型的可微性及非线性结构荷载同伦识别算法进行研究。具体内容包括：提出Bouc-Wen模型非光滑点的处理方法，研究光滑参数对非光滑点的邻域范围、Bouc-Wen模型误差及其全局可微性的影响；研究荷载同伦识别算法中辅助参数对算法收敛区域、收敛速度的影响；研究响应残差反向传播模型；通过响应对荷载的灵敏度及响应之间的互信息，研究荷载同伦识别算法中测点位置的优化布置。本项目旨在提出一种高效的基于Bouc-Wen模型的滞回非线性结构荷载识别算法，为滞回非线性结构提供一种实用的荷载测量手段。

Loads are indispensable basic data for structure design, dynamic optimization, operation and maintenance and health monitoring; and load identification is one important method for measuring loads. However, strong nonlinearity of Bouc-Wen Model and the calculation convergence of structure dynamic inverse problems become the major bottlenecks for development of the load identification theory for hysteresis nonlinearity structures. This project focuses on nonlinear structures based on Bouc-Wen Model to study differentiability of Bouc-Wen Model and the homotopy identification algorithm for nonlinear structure dynamic loads, whose specific contents are as follows:.1) To put forward the processing method for non-smooth points of Bouc-Wen Model;.2) To study the relationships between smoothing parameters and the range of the domain of any non-smooth point, and the error of Bouc-Wen Model and its global differentiability;.3) To study the relationships between those auxiliary parameters and its convergence region and rate for the homotopy identification algorithm for loads; .4) To go into the response residual error back propagation model; and .5) To investigate the location layout optimization of measuring points through the sensitivity (responses vs. loads) and mutual information between responses..This study is to put forward an efficient load identification algorithm for hysteresis nonlinearity structures based on Bouc-Wen Model so that an practical load measurement method may be established for hysteresis nonlinearity structures.