【作者】 冯勇明；

【导师】 周丽；

【作者基本信息】 南京航空航天大学 ， 工程力学， 2012， 博士

【摘要】 近年来在智能材料与结构领域取得的新进展，使得利用集成在结构中的先进驱动/传感元件网络，在线获取与结构状态相关的信息，识别结构的安全状况成为可能。应用结构健康监测系统及时获取有关结构损伤的性质、程度、分布和演变等信息，对及时做出决策来阻止结构性能的退化和失效，增加飞行安全，降低维护费用具有至关重要的意义。本文对航空复合材料结构健康监测中的若干技术方法进行研究，采用主动监测的方法，对结构进行在线的连续监测，近乎实时地监测到结构损伤发生和作用的位置。本文的主要研究内容和取得的成果有：（1）对运用Lamb波时间反转法对复合材料板结构损伤监测进行研究。首先采用弹性力学基本方程求导了Lamb波频散方程，建立了Lamb波传播的力学模型，对压电传感器驱动/感应Lamb波的原理进行了深入的探讨，通过有限元数值方法研究了Lamb波在结构中传播的特性；然后研究了Lamb波的时间反转法在复合材料损伤检测中的应用，提出了一种利用Lamb波时间反转法对复合材料结构进行损伤成像的方法；通过建立损伤指标，得到传感器通道的损伤系数，为损伤成像提供基准信息；对工业CT成像中的损伤概率成像算法进行改进，使其适用于无基准信号下的结构健康监测。实验验证所提方法的可行性及有效性。（2）对运用Lamb波匹配追踪方法的蜂窝复合材料损伤识别技术进行研究。首先详细介绍了匹配追踪方法，针对Lamb波监测方法的特点，提出了字典库为Chirplet原子的匹配追踪方法的快速实现方案，对Lamb波信号进行快速分解，提取相关的特征信息，并证明Chirplet原子能准确地匹配受弥散效应影响发生失真变形的窄带脉冲信号；提出一种基于Lamb波和匹配追踪方法的损伤识别方法，通过有限元仿真的结果加以验证，仿真结果表明匹配追踪方法能有效识别出Lamb波的模态，准确地提取出Lamb波中包含的损伤信息，实现对损伤进行精确定位，通过在各向同性板结构进行验证，实验结果表明匹配追踪方法能有效地分辨出多损伤的散射信号，精确定位损伤。最后将该方法应用于蜂窝夹层复合材料结构的冲击损伤识别中，分别采用椭圆定位技术和损伤成像技术定位冲击损伤位置。（3）对基于概率统计方法对复合材料损伤监测和识别进行研究，提出一种两步识别方法用于监测并识别环境变化下损伤发生与否及损伤的位置。该方法先采用信号处理方法提取信号的能力特征，通过对比结构损伤前后Lamb波信号的特征得到损伤差异系数，作为损伤指标；再采用概率统计方法来判断该损伤指标是由损伤引起还是由环境变化造成，从而判断结构是否发生损伤；最后采用损伤概率成像算法获取损伤存在的概率图像对损伤的位置和大小进行可视化识别。通过在复合材料层板和加筋结构实验研究以验证所提方法的有效性。更多还原

【Abstract】 Recent developments in the area of smart materials and structures have made it possible to obtaininformation about the state of structures and to identify the structural safety status online withadvanced actuator/sensor network integrated in the structures. It is important and crucial for impedingthe structural health monitoring system （SHMS） to obtain the information about the characteristics,extent, distribution and progress of the damages.This dissertation studies several methods and techniques in structural health monitoring ofaircraft structures.The active methods is applied to monitor the structures continuously and online toensure the structural safety. These techniques can indentify the damage loction and damage size, andconsider the effect of actual operational environment on damage detection and identification. After abrief introduction of the background of this study in Chapter1, the main contents of this dissertationare as follows:（1） In Chapter2, the problem of damage identification for composite plate structure is studied. Lambwave time reversal method is a new and tempting baseline-free damage detection technique forstructural health monitoring. With this method, damage can be detected without baseline data. In thepaper an online damage detection and identification method is presented using time reversal Lambwaves method and ultrasonic tomography for damage diagnosis of composites. The principle andcharacters of the time reversal lamb waves in a composite plate have been introduced firstly. Then thetime reversal method has been adapted to detect the local defects in composite plate structures, byusing an active sensing system mounted on a composite plate to excite and receive Lamb waves. Thismethod can identify the location and size of the damage in a composite plate quickly without relyingon past baseline date. The image that indicates the damage can be obtained by the ultrasonictomography algorithm. Experimental study results demonstrate the applicability and effectiveness ofthe proposed method.（2） In Chapter3, the multiple modes and dispersion nature of ultrasonic Lamb waves are investigatedin plate structure, the propagation of Lamb waves in damaged plate is simulated using the finiteelement method, and the electromechanical coupling behavior of piezoelectric ceramic piece and theinduced strain model are studied for the activation and sensation of Lamb waves; the matchingpursuits is introduced in detail, a fast implement method is proposed for matching pursuits methodwith a Chirplet dictionary, it can decompose the Lamb signals quickly and extract the characteristic information, and it is demonstrated that the Chirplet atoms can match the distorted narrow band pulsesaccurately; a damage identification method is proposed based on Lamb waves and matching pursuits,and it is verified by the results of finite element method, the simulation results show that matchingpursuits method can identify the modes of Lamb waves and extract the damage informationeffectively, it can locate the damage accurately, and an experiment device is established to verify thismethod, the experiment results show that the matching pursuits method can distinguish the overlappedscattered signals from several damages, and locate the damage accurately; finally the damageidentification method is employed to detect the impact damage in honeycomb sandwich of carbonfiber composite structure, the ellipse location method and damage imaging method are used to locatethe impact damage.（3） In chapter4, the problem of damage detection and identification for composite structures underenvironmental changes is studied. At first, reconstruction algorithm for probabilistic inspection ofdamage, which is a two step identification method, is proposed to firstly judge whether there isdamage in the structure, and secondly identify the location and size of the damage. In this method,signal processing methods are applied to extract the features of the Lamb wave signals. The differencecoefficient, which is called as damage index （DI）, is obtained by comparing the features of thereference and present signals. Then the probabilistic method is used to judge that the DI is caused byeither the structural damage or the environmental factors and decide whether the damage occurs. Andfinally, the damage imaging algorithm is applied to obtain a tomogram for damage identification. Inorder to verify the feasibility and effectiveness of this method, some structural damage identificationexperiments are carried out on composites. The experimental identification results are accurate andthe image is clearness.This study is partially supported by the National Natural Science Foundation of China GrantNo.11172128, and the Funds for International Cooperation and Exchange of the National NaturalScience Foundation of China （No.61161120323）, the Jiangsu Province for Six Kinds of ExcellentTalent of China （No.2010-JZ-004） and Jiangsu Graduate Training Innovation Project （CX09B₀70Z）.更多还原