Optimal sensor placement technique plays a key role in structural health monitoring of spatial lattice structures. This paper considers the problem of locating sensors on a spatial lattice structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterized. Based on the criterion of optimal sensor placement for modal test, an improved genetic algorithm is introduced to find the optimal placement of sensors. The modal strain energy (MSE) and the modal assurance criterion (MAC) have been taken as the fitness function, respectively, so that three placement designs were produced. The decimal two-dimension array coding method instead of binary coding method is proposed to code the solution. Forced mutation operator is introduced when the identical genes appear via the crossover procedure. A computational simulation of a 12-bay plain truss model has been implemented to demonstrate the feasibility of the three optimal algorithms above. The obtained optimal sensor placements using the improved genetic algorithm are compared with those gained by exiting genetic algorithm using the binary coding method. Further the comparison criterion based on the mean square error between the finite element method (FEM) mode shapes and the Guyan expansion mode shapes identified by data-driven stochastic subspace identification (SSI-DATA) method are employed to demonstrate the advantage of the different fitness function. The results showed that some innovations in genetic algorithm proposed in this paper can enlarge the genes storage and improve the convergence of the algorithm. More importantly, the three optimal sensor placement methods can all provide the reliable results and identify the vibration characteristics of the 12-bay plain truss model accurately.

针对网架结构特点，引入敏感模态的概念，提出了一种识别敏感模态的算法；基于剩余模态力理论，利用敏感模态进行损伤位置识别，并建立了基于模态应变能理论的损伤程度评估算法，采用非负最小二乘法求解超静定方程组，实现定量评估损伤程度。以某实际结构为仿真对象，分析了上述算法在网架结构损伤识别中联合应用的可行性，同时将评估结果与基于最小秩摄动理论的损伤程度评估结果进行了比较研究，并考虑测试噪声影响。结果表明，二者联合工作效果较好，不仅可以识别结构单处损伤，还可以识别结构多处损伤，且损伤程度评估结果同基于最小秩摄动理论损伤程度评估结果比，更可信，将其应用于网架结构的健康诊断是可行的。

为解决空间网格结构模态测试中的传感器位置优化布置问题，提高采集数据信息的完备性，采用遗传算法优化传感器布置位置。在解的编码过程中采用二维数组，每一行存储一个可行解；采用强制变异避免遗传算子操作过程中出现同一个位置重复布置的问题。为了提高收敛速度，将基于模态矩阵QR分解的传感器优化布置结果作为第一代父群。对单层球面网壳进行优化计算后，将基于遗传算法的优化结果和QR分解得到的结果进行了应变能指标和相关性矩阵（MAC）的比较，发现前者不仅在应变能指标有大幅度的提高,而且相关性矩阵也有相应改善。

斜拉网格结构是目前应用较为广泛的刚柔混合结构体系之一，由塔柱、拉索、网格结构组合而成。系统的对该类结构体系在我国的发展进行了回顾及展望。首先，对该混合结构的结构形式发展及部分工程应用进行了介绍；之后，分别回顾了斜拉平板网架结构和斜拉空间网壳结构的结构特性研究，从考虑结构几何非线性，参数振动和模态跃迁等因素，突出分析了斜拉空间网壳结构复杂的动力特性行为；最后，分析尚存的问题，对今后的发展进行了展望。

为了适应市场对大跨度楼盖结构的需要，在总结当前楼盖体系主要指标的基础上，提出一种新的“大跨度预应力空腹楼盖结构”体系。此结构不仅可满足跨度18m左右的建筑需要，且使楼盖结构层高度相对降低。并对这一结构进行了初步设计和内力分析，从而证实了其良好的空间工作性能，是一种具有广阔应用前景的新体系。