复合材料整体成型过程分层缺陷动态扩展研究

分层是复合材料层合板最主要的缺陷/损伤形式,当前研究多集中于复合材料使用过程中的分层损伤,对制造过程中的分层缺陷研究较少.复合材料层合板的分层缺陷在整体成型过程中因不均匀温度场、非对称结构等原因易发生扩展,采用预埋隔离纸模拟分层缺陷,研究分层缺陷在整体成型过程中的扩展行为,对分层扩展的驱动力进行了计算分析,并通过分析热循环对T300/QY8911复合材料层合板界面性能的影响以及计算裂纹尖端能量释放率,从实验研究和有限元计算两方面证明了分层扩展是一个动态过程.研究结果表明,热残余应力是T300/QY8911复合材料层合板整体成型过程中发生分层缺陷扩展的主要驱动力;增加热循环次数和提高热循环温度会显著降低T300/QY8911复合材料层合板的层间剪切强度,当能量释放率降低到低于层间断裂韧性值时,分层动态扩展过程则停止.     

FBG传感器在复合材料固化监测中的应用

FBG传感器广泛应用于复合材料结构健康监测中,将双光栅的FBG传感器埋入到玻璃纤维/环氧树脂预浸层合板结构中,监测热压固化过程中温度、内应力变化以及固化残余应变,分析了残余应变对FBG传感器性能的影响。实验表明FBG传感器可以有效监测复合材料结构固化过程的温度和内应力,以及由温度计算的粘度变化,为智能固化控制提供依据,且固化于复合材料结构内的传感器可用于结构的全服役周期健康监测。     

基于HHT的机翼盒段的健康监控

提出了一种基于HILBERTHUANG变换技术的结构微损伤检测方法.基于HHT方法,提取了同损伤相联系的特征量-瞬时频率变化量和瞬时能量变化量.给出了结构损伤前后瞬时频率的变化情况,根据结构损伤前后瞬时频率的变化量,可以判断结构发生了一定程度的损伤.最后研究了结构损伤前后瞬时能量的变换情况,并讨论了瞬时能量变化最大值与结构损伤程度之间的关系.结果表明,结构原始响应信号经过HHT变换后得到的瞬时能量变化最大值与结构损伤程度有一定的规律可寻.     

基于FBG单传感器的复合材料板低速冲击定位研究

由于复合材料结构先验知识获取的困难性及多传感器动态监测的冗余性,提出了一种基于归一化互相关的单传感器 冲击定位方法,并搭建了单传感器复合材料板低速冲击定位系统。首先,利用归一化互相关方法提取基于冲击位置的信号特征,并有效去除传感器的温度交叉敏感和冲击能量影响因素。然后,计算样本信号和待定信号的归一化互相关值,并进行比较。最后,选择待定位信号角度范围内前三个最大相关值的样本点组成定位参考区域,以三角区域质心来评估冲击位置,在 600ｍｍ×600复合材料层合板上进行单传感器低速冲击定位验证实验。结果表明利用该定位方法可以准确进行冲击定位,其中最大误差为45.91ｍｍ,平均误差为24.99ｍｍ,通过单传感器定位性能实验结果显示:单传感器位置变化不会影响平均误差范围变化,单传感器定位平均误差和最大误差等大于双传感器,但均符合工程应用范围。结果证明,此方法能够在保证监测准确率的情况下尽可能减少大型复合材料结构传感网络中传感器的数目,同时大大减小布线和数据处理的复杂性,为大型结构健康监测提供了依据。     

基于混沌激励与吸引子几何分析的连接损伤状态识别

工程结构在使用寿命周期内,各种环境因素会导致连接部位出现损伤,从而威胁结构的完整性和功能性,甚至诱发安全事故. 本文研究了一种利用混沌激励与吸引子几何特征进行连接损伤状态识别的方法,采用混沌振动信号激励待测结构,利用采集到的加速度响应时间序列信号进行相空间重构,并构造了一种基于吸引子局部方差计算的特征参量用于小程度连接损伤的识别,并对特征参量进行了统计分析计算. 设计了悬臂梁连接损伤识别实验,通过控制固定端螺栓的预紧力来模拟连接损伤,利用上述方法对连接的损伤状态进行了识别. 结果表明,本文方法能够有效识别连接的损伤状态,所构造的特征参量随损伤程度改变单调变化,特征参量能以一定置信度较好地区分不同的损伤水平.     

含孔复合材料层合板累积损伤仿真分析

针对面内静拉伸纤维增强复合材料含中孔层合板,发展了一种参数化三维逐渐损伤模型,并结合有限元三维逐渐损伤分析技术即应力分析、失效判定准则及损伤过程中材料性能退化等,对含孔层合板损伤扩展进行了仿真分析.本模型可以模拟含中孔层合板损伤起始、发展及最终结构破坏整个过程,并能较好地预测含孔层合板的破坏模式和破坏强度.该文同时对含孔层合板的损伤基本机理、类型及其相互关联作用进行了分析探讨,该文计算结果与文献实验结果非常吻合.     

基于小波包能量谱的钢轨扣件松脱检测研究

提出了基于小波包能量谱的钢轨扣件松脱识别方法,对获得的振动信号进行小波包分解,结合扣件松脱前后振动信号频域内能量变化,构造损伤指标(DI).在此基础上,开展了5种工况下的轨道结构动力响应测试,进行了轨道结构状态识别分析.实验结果表明:DI能够有效地识别轨道结构状态,且随着松脱程度的增加而增加;同一工况下得到的损伤指标DI变化波动均在±0.5以内,验证了该方法具有很好的鲁棒性和抗干扰能力.     

基于机电阻抗法的复合材料层压板低速撞击损伤监测

由于复合材料结构对外部低速撞击非常敏感,易产生目视不可检的内部损伤,提出了基于机电阻抗(Electromechanical Impedance, EMI)技术的复合材料层压板低速撞击损伤实时在线监测方法。对复合材料层压板施加阶梯能量撞击,每次撞击后采集粘贴在复合材料结构表面的压电传感器阵列的电阻信号。随后提取谐振峰电阻(Resonant Peak Resistance, RPR)作为特征信号,对复合材料结构在不同撞击能量下的阻抗演化规律和损伤扩展进行表征。实验结果显示,基于EMI的RPR特征信号随撞击损伤的扩展逐步减小,且对撞击损伤的检测结果的重复性好。结果表明,此方法对低速撞击产生的微小损伤灵敏度较高,能够有效地反映复合材料层压板内部低速撞击损伤的扩展。     

基于虚拟仪器技术的复合材料损伤实时监测系统软件开发

本文将虚拟仪器技术和主动监测技术相结合 ,研制了一种新型复合材料损伤监测系统。该系统可以实时监测蜂窝复合材料及碳纤维层合板的冲击损伤。文中介绍虚拟仪器的软件开发技术 ,着重论述了 HP VEE与 MATL AB及 Visual C++间接口的实现方法。     

基于RFID传感标签的弯曲应变无线监测方法及实验

为解决结构应变有线监测方法存在的布线量大、安装维护费用高、可靠性差等问题,提出一种基于RFID传感标签技术的无线监测新方法。详细介绍了由应变信号调理电路、MSP430单片机和nRF905无线收发模块组成的标签硬件设计和软件实现。根据有限元分析的结果,在碳纤维增强复合材料层合板实验试件上布置了多个电阻应变片,利用设计的传感标签和读写器,在万能材料试验机上构建了结构应变无线监测的实验系统。弯曲实验结果表明分布的传感标签可有效获取结构应变信号并实现信号的无线传输与处理;多通道数据分析处理结果与实验现象一致,验证了该系统实现结构应变无线监测的有效性。     

无方向数据采集的相控阵结构健康监测研究

超声相控阵结构健康监测过程中由于按角度扫描的数据采集持续时间长,结构损伤前后采集的数据易受环境和结构变化的影响,针对这一问题,提出无方向数据采集的相控阵结构健康监测成像定位方法。基于相控阵方法,对采集后数据根据发射和接收过程进行时间延迟的计算,然后将监测结果进行二维成像。该方法在玻璃纤维复合材料板结构上的实验研究证明,采用无方向数据采集的相控阵结构健康监测方法能够精确监测结构中损伤并对损伤进行清晰成像;并且该方法可以大大缩短监测时间,从而使监测过程不受环境条件变化的影响,为超声相控阵监测方法的工程化奠定基础。     

虚拟仪器技术在结构远程健康监测中的应用

本文分析了虚拟仪器技术应用于土木工程结构健康监测和远程诊断系统中的重要性，介绍了结构健康监测和远程诊断系统的框架，并利用美国NI（National Instruments）公司开发的虚拟仪器编程语言Lab Windows／CVI实现数据在TCP／IP协议下的远程传输。     

Fast orthogonal search (FOS) versus fast Fourier transform (FFT) as spectral model estimations techniques applied for structural health monitoring (SHM)

In the last decade, structural health monitoring (SHM) systems became essential to accurately monitor structural response due to real-time loading conditions, detect damage in the structure, and report the location and nature of this damage. Spectral analysis using Fourier transform has been widely used in SHM. In this research, a novel approach for the characterization of in structure damage in civil structure is introduced. The target is to develop vibration-based damage detection algorithms that can relate structural dynamics changes to damage occurrence in a structure. This article presents a new method utilizing high resolution spectral analysis based on Fast Orthogonal Search (FOS) techniques. FOS is a signal processing tool developed to provide high-resolution spectral estimation. In addition, it is a general-purpose non-linear modeling technique that finds functional expansions using an arbitrary set of non-orthogonal candidate functions. In order to examine the proposed method, the IASC-ASCE structural health monitoring benchmark structure is used in this study to illustrate the merits and limitation of the proposed approach. We also discuss the merits and the limitations of FOS as applied to SHM.     

Identification of coexistent load and damage

Load reconstruction and damage identification are crucial problems in structural health monitoring. However, it seems there is not much investigation on identification of coexistent load and damage, although in practice they usually exist together. This paper presents a methodology to solve this problem based on the Virtual Distortion Method. A damaged structure is modeled by an equivalent intact structure subjected to the same loads and to virtual distortions which model the damages. The measured structural response is used to identify the loads, the distortions and to recover the stress-strain relationship of the damaged elements. This way both the damage type and extent are identified. The approach can be used off-line and online by repetitive applications in a moving time window. A numerical experiment of a truss with 5% measurement error validates that the two tested damage types (constant stiffness reduction and breathing crack) can be identified along with the loads.     

Optimal control of mobile monitoring agents in immune-inspired wireless monitoring networks

This paper studies optimal control of mobile monitoring agents in artificial-immune-system-based (AIS-based) monitoring networks. In AIS-based structural health monitoring (SHM) networks, the active structural health monitoring is performed by a group of mobile monitoring agents equipped with damage pattern recognition algorithms. The mobile monitoring agents mimic immune cells in the natural immune system and patrol a structure to detect damage patterns using their receptors (feature vectors), damage pattern recognition algorithms, and the dynamic response data of the structure. The optimal control of mobile monitoring agents includes agent generation and distribution. The generation of mobile monitoring agents is optimized to minimize the response time for the mobile monitoring agents to diagnose structural damage in a sub-network and maximize the average affinity of monitoring agents′ receptors to the damaged sensor data feature vector. The objective functions for distributing mobile monitoring agents are to increase the detection probability and extend network life by balancing energy consumption of sensor nodes in the network. The presented optimization algorithms are developed using multi-objective genetic algorithms. The impact of the algorithm parameters on the performance of the algorithm is also investigated.     

An integrated approach for structural damage identification using wavelet neuro-fuzzy model

Structural damage can be identified by processing structural vibration response signals and excitation data, and thus the suitability of signal processing methods is essential to structural damage identification. To explore an intelligent signal processing method for structural damage identification, the paper integrated wavelet real-time filtering algorithm, Adaptive Neruo-Fuzzy Inference System (ANFIS) and interval modeling technique to process structural response signals and excitation data. With Wavelet Transform (WT) algorithm filtering random noise, ANFIS was found to model the structural behavior properly and interval modeling technique to quantify damage index accurately. The rapid identifications of several unknown damages and small damages indicate the efficiency of this integrated method. The comparison of these results and some other signal processing methods shows that, the proposed method can be used to identify both the time and the location when the structural damage occurs unexpectedly.     

频域加权陷波多声发射源定位与伪源辨识方法

针对信号处理中的稀疏阵列有时会出现栅瓣和伪峰的现象,进而影响波束形成法在结构损伤定位中应用的问题,提出了基于频域加权波束零陷的未知真实声发射源数量的声发射定位与伪源辨识方法。首先,推导研究了波束零陷思想在二维频域加权波束形成方法中的作用机理;然后,基于频域加权陷波的波束形成方法,提出了在未知真实声发射源数量情况下的伪声发射源的辨识和真实声发射源的定位流程;最后,在存在较多伪声发射源干扰情况下进行了单声发射源和同时多声发射源的定位试验,验证了所提出方法的准确性。研究结果表明,所提出的方法对于推广波束形成法在结构健康监测领域的应用具有价值。     

面向无线传感结构健康监测的压缩感知方法研究

无线传感器网络在结构健康监测方面有着广泛的应用,但由于该领域的传感器数量和种类众多,数据压缩对系统的高效运行起着关键作用。因此,提出了一种基于压缩感知的无线传感结构健康监测方法,对航空铝板的结构振动信号采用高斯随机矩阵将高维信号序列投影到低维空间,获得稀疏采样的线性测量值,实现信号的压缩采样。研究改进的正交匹配追踪算法来实现稀疏信号的重构。实验结果表明,与已有的无线传感结构健康监测相比,采用压缩采样的监测方法具有良好的抗噪性,并能获得较好的数据压缩效果,节省了网络的带宽和能量;通过信号的近似重构（重构误差在±0.13）,能实现航空铝板损伤准确识别（误差0.84mm）。     

Design and development of microstrip patch antenna with circular and rectangular slot for structural health monitoring

Structural health monitoring (SHM) is the technique to identify the damage in the building or physical structures. Several structural health monitoring has been proposed in recent years. Increase in number of sensors and its wiring mechanism causes issue in signal processing demand, efficiency, and unreliability. In current state, already present sensors cannot be used for Structural Health Monitoring because of its high cost and low battery capacity, although none of these techniques are capable of monitoring the condition of complex physical structures. The measurement of strain can be done by using patch antenna as strain sensors. In currently available sensors only the wireless range. The main objective of this paper is to investigate the feasibility of using circular and rectangular slotted microstrip patch antenna as a strain sensor for structural health monitoring without these afore mentioned problems. These antenna sensors’ (slotted rectangular and circular microstrip patch antennas) simulation results are confirmed. From the simulation results, the sensor provides information about crack orientation.