【作者】 宋振；

【导师】 郑世杰；

【作者基本信息】 南京航空航天大学 ， 工程力学， 2009， 硕士

【摘要】 智能结构是一种能感知周围环境变化,并能针对这种变化做出适当反应的自感知─自适应结构,基于压电、光纤等新型传感器的结构健康监测研究受到国内外学者的广泛关注,本文从航空航天等领域利用压电智能结构进行结构健康监测的工程背景出发,对压电智能结构的载荷识别方法进行了较深入、系统的研究。论文采用遗传算法和有限元相结合的方法,实现复合材料结构载荷大小和位置的识别,并着重对染色体的编码方式进行了深入研究。以荷载作用位置的结点号和荷载大小为参数的二进制编码方法简单、高效,但存在连续函数离散化时的映射误差,且其编码串的长度取决于所要求的识别精度,过长的染色体会影响算法的计算效率;以二进制编码表征载荷作用位置,浮点数编码表示载荷大小的混合编码方法,大大降低了染色体的长度,显著提高了计算效率和精度,可难以实现非网格结点处的载荷识别;论文首次提出了一种受载单元判别法,根据染色体所对应的载荷作用点的横、纵坐标和每个单元四条边间的几何关系,判断出集中载荷作用的单元,再根据力的等效分配原则,把载荷等效分配到所在单元的结点上,进而基于有限元分析和遗传算法自身优越的全局搜索能力实现作用于复合材料结构网格结点或单元内部任意位置处的载荷识别,与现有的神经网络识别法和有限元反分析法相比,本方法具有能够识别非网格结点处的载荷的优点,且仿真算例表明其识别精度更高;在对静载荷识别研究的基础上,本文研究了作用于任意位置处的冲击载荷时间历程反演和冲击位置判别方法。仿真算例表明了本文方法对冲击载荷历程反演及位置识别的有效性。更多还原

【Abstract】 Smart structure is a kind of self-sensing and self-adaptive structure that can sense the change of the surrounding environment and can make an appropriate response in response to this change. Structural health monitoring based on the new type of sensors such as piezoelectric, optical fiber sensors, has drawn extensive attention from scholars at home and abroad. In this article, a further and systematic study about the load identification of piezoelectric smart structure was conducted in the engineering background of using piezoelectric smart structures for structural health monitoring in the aviation and aerospace areas.This paper used the method of combining genetic algorithms and finite element method to achieve the identification of amplitude and location of the load acted on the composite material structure, having a deep research on the chromosome encoding methods. The method that encoded the load amplitude and location with binary encoding method is simple, efficient, but there is a mapping error in the continuous function discretization. The string length depends on the required identification accuracy, and long chromosome will affect the calculation efficiency; The hybrid coding method of encoding the location of load with binary encoding method and encoding the amplitude of load with floating-point encoding method has greatly reduced the length of chromosomes, and significantly improved the computation efficiency and accuracy, but it was difficult to achieve the identification of non-grid node points; A discriminance method was proposed to identify the element where the concentrated load locates, which was judged by the geometrical relationship between the abscissa, vertical coordinates of load point generated from GA and four edges of every element. Furthermore, the load was allocated to nodes of the element by the equivalent distribution principle. Finally, the location of arbitrary concentrated load was identified by finite element analysis and the superior global search capacity of GA. Compared with the identification methods of neural network and inverse finite element analysis method , the present method has the advantage of being able to identify the concentrated load locating at the interior of a element and numerical examples show that this method has higher accuracy. In addition, the inversion equation of dynamic load history and method of location identification are derived based on the identification of static load. The simulation with a specific example shows that the identification of the history and the location of impact load are feasible.更多还原