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.

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。

针对现行钢结构检测技术的不足和钢结构游泳馆在服役期间的实际使用状况，阐述钢结构游泳馆安全性检测的内容和检测方法，提出安全性检测的控制程序。对某实际工程，通过有限元仿真分析和现场试验，对提出的安全性检测的内容及方法进行了验证。建立仿真模型，进行结构的静、动力特性及影响因素分析，可以指导结构现场的安全性检测。在现场的动力试验中，采用多点随机激励法对结构进行激励，频域分解法（FDD法）对实测信号进行分析，以辨识结构的实际固有频率及振型，并与有限元动力仿真结果进行对比。研究结果表明，FDD法可以用来分析低频结构中含噪声的实际响应信号，所提出的安全性检测的内容、方法及控制程序是有效的、可靠的。

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。

在对张弦梁结构的撑杆与索的连接方式进行探讨的基础上，根据现有张弦梁施工中存在的撑杆竖向精度无法保证的问题，提出解决方法，即采用狗骨式调节器保证撑杆的竖向位置，同时介绍其优点和工作机理；其次对结构进行了静力分析并与实测值进行了比较，得到如下结论： 索张力与拱梁起拱值（实测值）在开始阶段呈非线性变化，其后呈线性变化，斜率与理论值基本相等，最后阶段起拱值迅速增大，斜率大于理论值；实际结构的刚度比理论值小；实际结构的狗骨式调节器发挥了保证撑杆竖向位置不动的作用；最后对单榀张弦梁的施工过程予以介绍。