基于位移响应协方差参数的数值仿真和实测损伤识别研究

本文使用结构位移响应协方差参数进行结构损伤识别,首先推导和建立位移响应协方差参数的解析公式,它是结构频率、振型和阻尼等模态参数的函数,结构物理参数的改变会导致该协方差参数的改变;对一个七层框架结构进行数值模拟分析来演示该方法的有效性,通过比较结构不同状态下各单元位移响应协方差参数CoD的分布曲线,研究各单元CoD与损伤程度的关系曲线,发现损伤位置处的CoD改变最大,其次是对称和附近单元,通过单损伤和多损伤工况研究分析,表明基于结构损伤前后CoD的改变,能成功判定损伤发生和识别出损伤位置,最后把该方法应用于一个实验室简支钢梁的损伤识别,通过对锤击振动下的加速度响应进行二次积分得到位移响应,并比较钢梁损伤前后的CoD,得到损伤概率向量,成功识别出损伤位置。该方法具有较好的噪声鲁棒性,无需结构分析模型,计算简便,具有较好的工程应用性。     

On irregularity-based damage detection method for cracked beams

A new damage detection technique using irregularity profile of a structural mode shape is proposed in this paper. The mode-shape of a cracked beam is first obtained analytically by using a general function. Its irregularity profile is then extracted from the mode shape by a numerical filter. The location and size of the crack in the beam can be determined by the peak value appearing on the irregularity profile. Two types of numerical filters, i.e., triangular and Gaussian, are examined. It has been found that the former filter is more effective in damage detection than the latter one. Numerical simulations suggest that the irregularity-based method requires a relatively low measurement resolution. Noise stress tests are carried out to demonstrate the effectiveness and robustness of this method under the influence of noise. As a validation, the proposed method is applied to detect crack damage in an E-glass/epoxy laminated composite beam. The successful detection of the crack in the composite beam demonstrates that the irregularity-based method is capable of assessing both the location and size of the crack and can be used efficiently and effectively in damage identification and health monitoring of beam-type structures.     

地震作用下基于响应敏感性的单层球面网壳冗余度分析方法研究

冗余特性是结构鲁棒性的重要组成部分,也是损伤情况下结构安全性的体现。在地震等动力荷载作用下单层球面网壳结构的倒塌模式由诸多因素决定,其中结构的冗余度是重要的影响因素。为合理评估地震作用下的结构冗余度,本文基于结构响应对单元材料弹性模量的敏感性提出地震作用下的结构构件冗余度评价方法,并对一星型网壳在地震作用下的弹性、弹塑性冗余度进行分析,以验证方法的有效性。结果表明,结构冗余度能够反映构件在结构中的重要性,冗余度值的大小是构件重要性的衡量指标,低冗余度构件是结构的关键构件。利用结构的冗余度分布,可以采取加强低冗余构件的措施,从而实现网壳结构倒塌模式的优化控制。     

基于拓扑优化的结构弹性成像方法

弹性模量是工程材料重要的性能参数, 可以衡量物体抵抗弹性变形的能力. 弹性成像是一种通过弹性模量表征生物体组织物理特性的医学成像方法. 为了将弹性成像应用于机械装备结构的缺陷识别, 提高弹性成像的局部表征和全局识别能力, 提出一种基于拓扑优化的结构弹性成像方法. 受拓扑优化理论启发, 采用结构离散单元的相对密度(弹性模量系数)作为弹性成像参数来表征损伤程度, 建立成像参数与弹性模量的插值模型, 基于有限元模型构建损伤表征、结构模型与物理响应的映射关系. 以损伤结构和无损结构位移响应的最小二乘为目标函数, 以成像参数上下限为约束, 建立结构弹性成像的优化模型. 以伴随法推导弹性成像问题的灵敏度, 并详细给出了弹性成像反演的数值实施方式. 二维悬臂梁和米歇尔梁算例表明, 本文提出的基于拓扑优化的弹性成像方法无需先验损伤信息, 可有效实现均质/非均质、单/多缺陷结构的弹性成像, 且弹性成像结果不依赖于特定的边界条件, 进一步将弹性成像方法扩展至三维悬臂梁问题验证了其通用性.      

基于梁连续抗弯刚度与小波变换的结构损伤识别方法研究

为了解决基于小波变换系数难以识别结构边缘损伤的问题,以及试验中损伤对周边的影响导致小波系数难以精确定位损伤位置的问题,提出了基于梁连续抗弯刚度与小波变换的结构损伤位置识别方法。该方法结合梁结构连续抗弯刚度与小波系数边缘的特点,在未知无损梁结构振动参数的情况下,能有效识别出梁结构边缘损伤且能准确定位试验中梁结构的损伤,通过损伤梁的数值模拟与试验证明了该方法的正确性。     

基于实测挠度、转角和曲率的细长梁分段抗弯刚度识别研究

静载试验是获得结构真卖特性的重要方法和途径，具有直观、可靠的特点。本文基于静载试验实测的挠度、转角和曲率，建立目标函数，通过优化的方法，实现结构分段截面抗弯刚度参数的识别。研究了优化目标函数的建立、优化算法的选取与实现；通过数值算例和一片简支梁静载试验实例分析，对方法的正确性与可行性进行了验证，所得结果可用于结构损伤识别和安全性能评估。     

基于高次广义柔度灵敏度的结构损伤识别

柔度矩阵可以由结构的低价模态近似计算获得,因此被广泛用于结构的模型修正和损伤识别中。由普通柔度派生而来的广义柔度,可以由低价模态数据更加精确的获得,且随着广义柔度次数的增高其精度越高,往往只需要第一或二阶模态数据即可获得很准确的高次广义柔度。因此,广义柔度灵敏度方法自提出以来受到广泛关注。本文详细研究了基于高次广义柔度灵敏度的损伤识别计算方法,研究中发现,利用广义柔度灵敏度进行损伤识别计算时,并非越高次的广义柔度其识别结果越准确,随着广义柔度次数的增加,损伤识别结果精度呈现出先提高但随后显著降低的趋势。究其原因在于,虽然随着广义柔度次数的增加,广义柔度本身的精度更高,但与之相应的灵敏度方程组系数矩阵的条件数却也显著增大了,即方程组的病态性反而更加严重了,这导致了基于高次广义柔度计算所得的损伤参数的精度反而不如低次广义柔度的情况。因此,本文的研究表明,工程中利用广义柔度进行模型修正或损伤识别时,一般采用一次广义柔度或二次广义柔度即可,且计算中为了克服方程组的病态性和数据噪声的不利影响,本文提出了一种反馈奇异值截断法,能够明显提高计算精度,获得较准确的识别结果。     

Restoring force and dynamic loadings identification for a nonlinear chain-like structure with partially unknown excitations

Most of the currently employed vibration-based identification approaches for structural damage detection are based on eigenvalues and/or eigenvectors extracted from dynamic response measurements, and strictly speaking, are only suitable for linear system. However, the inception and growth of damage in engineering structures under severe dynamic loadings are typical nonlinear procedures. Consequently, it is crucial to develop general structural restoring force and excitation identification approaches for nonlinear dynamic systems because the restoring force rather than equivalent stiffness can act as a direct indicator of the extent of the nonlinearity and be used to quantitatively evaluate the absorbed energy during vibration, and the dynamic loading is an important factor for structural remaining life forecast. In this study, based on the instantaneous state vectors and partially unknown excitation, a power series polynomial model (PSPM) was utilized to model the nonlinear restoring force (NRF) of a chain-like nonlinear multi-degree-of-freedom (MDOF) structure. To improve the efficiency and accuracy of the proposed approach, an iterative approach, namely weighted adaptive iterative least-squares estimation with incomplete measured excitations (WAILSE-IME), where a weight coefficient and a learning coefficient were involved, was proposed to identify the restoring force of the structure as well as the unknown dynamic loadings simultaneously. The response measurements of the structure, i.e., the acceleration, velocity, and displacement, and partially known excitations were utilized for identification. The feasibility and robustness of the proposed approach was verified by numerical simulation with a 4 degree-of-freedom (DOF) numerical model incorporating a nonlinear structural member, and by experimental measurements with a four-story frame model equipped with two magneto-rheological (MR) dampers mimicking nonlinear behavior. The results show the proposed approach by combining the PSPM and WAILSE-IME algorithm is capable of effectively representing and identifying the NRF of the chain-like MDOF nonlinear system with partially unknown external excitations, and provide a potential way for damage prognosis and condition evaluation of engineering structures under dynamic loadings which should be regarded as a nonlinear system.     

基于EEMD和SVR的多自由度结构状态趋势预测

由于工程结构的复杂性和引起结构损伤原因的不确定性,结构早期微弱和潜在的损伤难以识别和预测。为此提出了基于聚类经验模式分解(EEMD)和支持向量机回归(SVR)的结构健康状态趋势预测方法。首先对多自由度结构渐进损伤的加速度振动信号进行聚类经验模式分解(EEMD);再进行希尔伯特变换(HT)计算瞬时频率;然后用回归支持向量机对反映结构健康状态的瞬时频率进行趋势预测。详细分析了各种参数对回归和预测精度的影响,提出了这些参数的选用方法和一般原则。研究表明:该方法具有训练样本少的特点;在采用二阶多项式核函数、回归步长m=3~5、误差惩罚因子C=100、敏感因子ε=0.01时,可以准确地和高精度地预测结构状态趋势,预测精度达到0.24781%。     

基于残余力向量法和改进遗传算法的结构损伤识别研究

提出了一种基于残余力向量法和改进遗传算法的结构损伤识别方法。文中首先对残余力向量法和遗传算法的基本理论进行了介绍。在无噪声的情况下,使用任意一阶模态数据,残余力向量法都能够对损伤进行准确定位。但是,振动测试数据中往往包含噪声,导致运用残余力向量法进行损伤识别完全不可行。考虑到这个问题,在常规模态分析的基础上,以节点的残余力向量构造用于遗传搜索优化的目标函数形式,然后利用改进的遗传算法重点进行了噪声条件下的结构损伤定位和定量研究。最后,本文用一个平面桁架模型进行了数值模拟,验证了所提出方法的有效性,并对方法应用中存在的一些问题进行了深入分析,得出了一些有益的结论。     

基于概率和非概率混合模型的结构鲁棒设计方法

讨论了同时存在概率不确定性量和非概率不确定性量时可行鲁棒性和目标函数鲁棒性的实现策略,提出了基于概率和非概率混合模型的结构鲁棒设计方法。基本做法是首先视非概率型不确定性量为参变量,按照传统概率统计的方法计算约束函数和目标函数的均值和标准方差,然后再考虑非概率型不确定性量的波动变化对约束函数和目标函数统计特征量的影响,以修正常规可行鲁棒性和目标函数鲁棒性的数学模型。所提方法应用于一个10杆桁架结构的最轻质量设计和节点位移鲁棒设计,获得了对不确定性量波动变化不敏感的设计方案。     

敲击扫描式梁式结构损伤检测方法

受到啄木鸟敲击树干找虫子等敲击现象的启发,论文针对梁式结构提出了一种敲击扫描式损伤检测方法.基于对敲击扫描过程的理论探讨,我们得到了该方法的灵敏度表达式,从而为该方法找到了可靠的理论基础.数值模拟和简单实验表明,该方法不但简单易行,而且在有干扰的环境下也可以有效地检测出结构的损伤.     

一种仅使用静态响应的梁结构损伤识别方法

提出了一种仅使用静态响应的梁结构损伤识别方法。此方法引入了一种倒数变量。采用倒数变量后,位移的泰勒展开式中仅含有倒数增量的线性项。构建了基于倒数变量的损伤求解模型,然后应用非负最小二乘法求解损伤参数,可同时确定损伤位置和程度。与未引用倒数变量的方法对比,求解的损伤参数更加逼近真实的损伤情况,且讨论了噪声的影响。通过数值模拟对三跨连续梁结构进行仿真分析,结果表明,提出的方法能够对梁结构的损伤做出有效识别。     

基于裂纹诱导弦挠度的梁开闭裂纹损伤识别

考虑裂纹缝隙效应,建立了Euler-Bernoulli梁中开闭裂纹位置、深度和初始张开角等损伤参数的识别方法．首先,基于梁中开闭裂纹的等效单向扭转弹簧模型,给出了开闭裂纹Euler-Bernoulli梁静力弯曲挠度的显式闭合解．在此基础上,证明了裂纹诱导弦挠度函数由分段三次多项式组成,并基于其构造特征,建立了基于测量挠度的梁中开闭裂纹位置、裂纹等效扭转弹簧柔度、裂纹初始张开角和裂纹上下侧属性等参数的数值识别方法．最后,通过数值实验考察了挠度测量误差和裂纹位置等对裂纹识别结果的影响,结果表明：裂纹位置、裂纹等效扭转弹簧柔度和裂纹初始张开角等的识别误差随挠度测量误差增大而增大,但裂纹识别结果具有较强的鲁棒性,在工程实际中具有一定的应用前景．     

基于L1正则化的随机梁式结构静力损伤识别方法

提出了一种结合摄动法和L1正则化方法的随机梁式结构静力损伤识别方法。考虑初始模型误差和测量误差的影响,建立了关于随机损伤指数的控制方程,并将摄动法和L1正则化方法相结合,对随机损伤指数的控制方程进行求解,进而从概率的角度对结构的损伤进行识别。损伤试验结果表明,和传统的最小二乘求解法相比,本文方法能够更为准确地识别多处局部损伤的位置及大小,对实际结构损伤检测具有较好的参考价值。     

Wavelet packet based damage identification of beam structures

Most of vibration-based damage detection methods require the modal properties that are obtained from measured signals through the system identification techniques. However, the modal properties such as natural frequencies and mode shapes are not such a good sensitive indication of structural damage. The wavelet packet transform (WPT) is a mathematical tool that has a special advantage over the traditional Fourier transform in analyzing non-stationary signals. It adopts redundant basis functions and hence can provide an arbitrary time-frequency resolution. In this study, a damage detection index called wavelet packet energy rate index (WPERI), is proposed for the damage detection of beam structures. The measured dynamic signals are decomposed into the wavelet packet components and the wavelet energy rate index is computed to indicate the structural damage. The proposed damage identification method is firstly illustrated with a simulated simply supported beam and the identified damage is satisfactory with assumed damage. Afterward, the method is applied to the tested steel beams with three damage scenarios in the laboratory. Despite the noise is present for real measurement data, the identified damage pattern is comparable with the tests. Both simulated and experimental studies demonstrated that the WPT-based energy rate index is a good candidate index that is sensitive to structural local damage.     

灰色相关性分析在结构静力损伤识别中的应用

基于灰色理论的相关性分析方法，首次提出了灰色曲率关联系数的概念并将其应用到结构的静力损伤识别中，提出了对局部损伤十分敏感的静态位移曲率置信因子SDCACi，通过该因子的大小对各节点所连接的单元是否会发生损伤进行精确的判断，然后运用最小二乘法对损伤区域的损伤程度进行识别．并将该方法应用于两端固支梁的损伤识别中，由识别结果可以证明：不论测量数据(用有限元仿真计算并考虑了测量误差)的多少，该方法对结构中的单损伤和多损伤都能进行准确的定位，因此该方法在大型结构及复杂结构的损伤识别中具有广阔的应用前景．     

Identification of multiple open and fatigue cracks in beam-like structures using wavelets on deflection signals

A novel method for damage detection of multi-cracked beam-like structures by analyzing the static deflection is presented. The damage incurred produces a change in the stiffness of the beam. This causes a localized singularity which can be identified by a wavelet analysis of the displacement response. The existence and location of the cracks can be revealed by positions of the peaks in the continuous wavelet transform (CWT). To achieve this, the static profile of beams is analyzed with Gauss2 wavelet to identify the cracks. Beams under some ideal boundary and prescribed load conditions are considered. The deflected shape of the beam with open and fatigue cracks has been simulated under static loading using lumped crack models adopted from fracture mechanics and involving various degrees of complexity. The deflection of cracked beam in closed form for several cases of loads, crack sizes, and crack locations is calculated, and an explicit expression for the damage index (DI), based on CWT, is developed; it is demonstrated that the proposed damage index does not depend on mechanical properties of a homogeneous beam, and that the DI of one crack does not depend on the size and location of other cracks in a multiple cracked beam. Hence, the obtained expression for the DI can be used to find the size of each crack independently. Numerical results show that the method can detect cracks of small depth and is also applicable under the presence of measurement noise.     

基于静力残余力向量的结构损伤评估方法

残余力向量法是一类常用的损伤识别方法,现有的残余力向量法都是基于动力测试的模态参数,和动力测试数据相比,静力测试数据往往精度更高,且无需模态分析等复杂操作.鉴于此,本文提出一种静力残余力向量法用于结构损伤评估.所提方法利用静力测试位移数据,并结合结构有限元模型的刚度矩阵,定义了静力残余力向量,根据该向量中不为零的元素来判断损伤自由度,再根据自由度和单元之间的对应关系来确定发生损伤的位置,并进一步提出一种求解损伤参数的代数解法.另外,针对实践中角位移难以测量的情况,进一步提出了一种静力缩聚残余力向量法,拓宽了所提方法的应用范围.以桁架结构和梁结构模型为例对所提方法进行了验证,数值算例结果说明所提方法合理有效.     

环境温度影响下基于支持向量机与强化飞蛾扑火优化算法的结构稀疏损伤识别

结构处于自然环境中常会受到环境温度变化的影响,引起实测动力响应出现较大误差,进一步影响对结构健康状况的判定.另外,基于优化算法的损伤识别在反演损伤位置及量化损伤程度时,易出现局部最优解,且计算效率低下.针对以上难题,本文提出一种结合支持向量机与强化飞蛾扑火优化算法的损伤识别方法,用于对环境温度影响下的结构稀疏损伤进行识...