混凝土结构中PZT传感器的多功能性分析及应用

针对混凝土结构被动监测中的压电陶瓷(也称锆钛酸铅,Pb-based lead zirconium titanate,简称PZT)传感器信号的多功能特性,提出了PZT传感器不同用途信号的提取方法。根据不同功能信号的频率范围差异,通过小波Mallat分解,得到用于反映结构整体动态信息的振动信号以及局部断裂破坏引起的声发射信号,通过与加速度传感器和声发射传感器信号比较,验证了提取方法的正确性,并将该方法应用到钢筋混凝土框剪结构模型地震破坏试验的实时监测中。试验结果表明,应用该方法提取到的振动信号能准确测得结构主频率等结构的动态信息,声发射信号部分能清楚捕捉局部损伤引起的能量释放情况。应用该方法可准确提取出结构的振动信号和声发射信号,利用同一PZT传感器能够实时评估和监测结构的整体动态特性和局部损伤状况。     

一种基于模型修改的结构多点损伤识别方法

可用于结构损伤识别的方法很多。一般来讲正向方法直接利用结构模态参数的变化，逆向方法则利用模态参数变化反演结构物理参数变化，还有些方法利用了神经网络和模式识别技术。文中利用模型修改的思想，通过逆向方法计算结构单元刚度变化系数来对结构的多点损伤进行识别。以一个七自由度弹簧阻尼质量系统作为研究对象，用数值模拟方法及特征系统实现算法计算系统的模态参数，并用这些模态参数验证所提出方法的可行性，结果表明该方法对多点损伤的识别是简单而可行的。     

A probabilistic damage identification approach for structures with uncertainties under unknown input

To avoid the false positives of damages in the deterministic identification method induced by uncertainties in measurement noise, a probabilistic method is proposed to identify damages of the structures with uncertainties under unknown input. The proposed probabilistic method is developed from a deterministic simultaneous identification method of structural physical parameters and input based on dynamic response sensitivity. The deterministic simultaneous identification method is first derived. The effect of uncertainties caused by measurement noise on the identified parameters is then investigated. The statistical parameters of the identified structural parameters are calculated. The damage index is derived from the statistical parameters of the physical parameters of intact and damaged structure. The probability of identified damage, defined as the probability of identified structural stiffness smaller than that of intact structure, is further derived using the probability method. A twelve-story building and a nine-bay three-dimensional frame structure are, respectively, analyzed numerically and experimentally using the proposed method. The research results indicate that the probabilistic simultaneous identification method for damage and input can decrease the false positives of damages in contrast with the deterministic method under intensive measurement noise, and it can also achieve an accurate identification for structural unknown input.     

藏式古建筑木结构损伤识别的数值模拟

为保护藏式古建筑木结构,针对实际中众多结构存在的梁、柱构件损伤问题进行了损伤识别理论的研究。基于实地勘查结果,对梁、柱构件的残损类型和残损机理进行了汇总和分析。以某典型藏式古建筑多层梁柱排架结构为损伤识别对象,在建立其有限元模型的基础上,采用振动响应灵敏度损伤识别方法对该结构梁、柱构件的3种不同损伤状态进行了数值模拟识别。为了模拟古建筑结构构件之间物理参数离散性大的特点,给每个构件的弹性模量添加了随机误差。识别时,为了减小离散的物理参数对结果收敛性和准确性的影响,采用修正的正则化方法求解识别方程。结果表明,该方法可以克服测量噪声的影响,准确识别出藏式古建筑木结构梁、柱构件的损伤,为该类型结构实际的损伤识别提供了理论依据。     

排列熵算法在水工结构损伤诊断中的应用

提出一种基于排列熵算法(permutation entropy,简称PE)的水工结构损伤诊断方法。首先,运用小波阈值-经验模态分解(empirical mode decomposition,简称EMD)降噪方法对原始信号进行降噪,减小环境噪声对结构损伤特征信息的干扰,提高信号的信噪比;其次,运用排列熵算法检测降噪后信号的复杂度,并计算其排列熵值。通过不同工况下信号熵值变化规律的对比,实现水工结构损伤的诊断。将该方法应用于泄流激励下悬臂梁模型的试验研究,结果表明,正常无损状态下结构振动信号的排列熵值最大;结构发生损伤时,其熵值降低,且损伤程度越大,熵值越小;排列熵对结构的初期损伤比较敏感;结构未发生损伤时,不同工况下的排列熵基本不变,说明排列熵能够有效确定结构的损伤,且具有较高的诊断精度。     

基于深度学习的导波特征提取及其激光超声检测

针对激光超声检测中波场的三维数据处理计算量大且损伤特征提取难的问题,提出了一种基于深度学习模型的导波波场分析方法.首先,以VGG-Net网络为框架,建立了基于VGG11(A-LRN)的残差网络模型,用于挖掘时间-空间波场数据中的导波特征;其次,以局部波数特征为物理机理,采用导波传播的解析式生成训练样本,解决了深度学习大数据获取的问题,获得了波场特征提取的神经网络模型;最后,以激光超声系统在含损伤结构中的实验数据作为测试样本,验证了所提出的网络模型能够提取表征损伤的导波特征,实现了结构的损伤成像,其损伤成像精度均在67%以上,损伤形貌的可视化效果好。     

融合应力集中因子与贝叶斯理论的结构健康评估方法

针对传统结构健康评估方法评估精度较低的现状,提出一种融合应力集中因子与贝叶斯理论的结构健康评估方法。首先,结合基于应力集中因子的序化模型策略与非齐次泊松过程,运用贝叶斯理论方法对试验信息及总体过程参数的序化关系进行有效融合,推导出适合不同初始损伤状态的过程参数先验分布。同时,基于应力集中递进因子与似然函数的概念,建立融合应力集中因子与贝叶斯定理非齐次泊松过程的参数后验分布预测方法。最后对提出的结构健康评估方法进行实例研究,并将预测结果与独立的试验结果进行比较。结果表明,提出方法的平均预测精度为91.99%,可以实现通过少量试验信息完成结构健康状态评估的目的,从而为结构健康的精确评估提供了一种思路。     

Structural damage detection with statistical analysis from support excitation

The unit impulse response (UIR) functions obtained from a structure under support excitation are used to identify local structural damages. The extraction of the UIR with the aid of discrete wavelet transform from the measured acceleration is described. The sensitivity matrix of these UIRs is then obtained based on the finite element model and the time-stepping integration method. Based on the computed sensitivity matrix of the UIRs from several accelerometers, a two-step model updating method is adopted for identifying the local damages. Statistical analysis is included into the damage identification procedure with the measurement noise taken as an independent random variable in the measured UIRs. A new damage localization index is proposed and the mean values of the identified parameters are taken as the damage severity. Finally, a nine-bay three-dimensional frame structure is analyzed numerically and experimentally using the proposed technique. The damage scenarios of multiple damages with different levels of noise are considered. The identified results are shown satisfactory, indicating the feasibility and effectiveness of the proposed technique.     

Development of scanning damage index for the damage detection of plate structures using modal strain energy method

This work presents a novel approach of nondestructive detection of damage in plate structures by using experimental modal analysis (EMA) and modal strain energy method (MSEM). An aluminum alloy 6061 thin plate with a surface crack is investigated in this study. EMA is conducted on the plate to obtain the mode shapes before and after damage. The modal displacements of each mode shape are then used to compute the modal strain energy. For all measured mode shapes, a damage index is defined by using the ratio of modal strain energies of the plate before and after damage. In fact, small damage causes very little change in system response, but it is an essential early warning of structure damage. As the second-order derivatives, modal strain energy is much more sensitive to the small change of structural response than frequencies and mode shapes. It is therefore feasible to approach the small damage by using a damage index defined by fractional MSE of the structure before and after damage. In this study, a scanning damage index (SDI) is developed by moving damage indices obtained from the local area throughout the structure as if a scanning sensor is used to inspect the structure. The damage indices in overlap areas are added up and the summation may intensify the signals of damage in the plate. Limited by the numbers of measured point, a differential quadrature method is employed to calculate the partial differential terms in strain energy formula. Experimental results show that SDI well identifies a surface crack location by using only few measured mode shapes of the aluminum plate. This novel approach provides a flexible, cost-effective, and nondestructive damage evaluation in either local or global structure. Its applicability to different types of structures and different sizes of damage is to be experimentally validated in the future work.     

Distinguishing between sensor fault, structural damage, and environmental or operational effects in structural health monitoring

Discrimination between three different sources of variability in a vibration-based structural health monitoring system is investigated: environmental or operational effects, sensor faults, and structural damage. Separating the environmental or operational effects from the other two is based on the assumption that measurements under different environmental or operational conditions are included in the training data. Distinguishing between sensor fault and structural damage utilizes the fact that the sensor faults are local, while structural damage is global. By localizing the change to a sensor which is then removed from the network, the two different influences can be separated. The sensor network is modelled as a Gaussian process and the generalized likelihood ratio test (GLRT) is then used to detect and localize a change in the system. A numerical and an experimental study are performed to validate the proposed method.     

基于受控结构动力特性和信息融合的损伤识别

提出了一种使用受控结构动力特性数据和运用信息融合技术进行结构损伤识别的方法。分别采用多损伤定位确信准则和结构的频率变化平方比相关性作为损伤识别指标,用状态反馈控制的方法有目的地对结构进行极点配置,得到所需的受控结构的特征频率和特征振型,以提高损伤识别指标对损伤的敏感度,然后用证据理论的方法将两者的识别结果进行决策级融合,得到一个更为可靠的损伤识别结果。数值仿真计算结果表明,所提出的方法能有效提高结构损伤识别的准确性。     

基于振型差小波变换的结构损伤检测方法

小波变换具有在时域和频域内表征信号局部特性的能力,能够在不同尺度下对结构响应中的突变信号进行放大和识别。在位移模态振型的基础上,提出了一种基于小波变换的结构损伤检测方法。将损伤前后结构的位移模态振型差作为原始信号进行小尺度小波变换,通过损伤前后位移模态振型差小波变换系数的变化,可判定损伤存在,确定损伤位置。并通过悬臂梁和海洋平台的数值模拟对该方法进行了验证。     

Quantitative damage detection for planetary gear sets based on physical models

Planetary gear set is the critical component in helicopter transmission train,and an important problem in condition monitoring and health management of planetary gear set is quantitative damage detection.In order to resolve this problem,an approach based on physical models is presented to detect damage quantitatively in planetary gear set.A particular emphasis is put on a feature generation and selection method,which is used for sun gear tooth breakage damage detection quantitatively in planetary gear box of helicopter transmission system.In this feature generation procedure,the pure torsional dynamical models of 2K-H planetary gear set is established for healthy case and sun gear tooth-breakage case.Then,a feature based on the spectrum of simulation signals of the dynamical models is generated.Aiming at selecting the best feature suitable for quantitative damage detection,a two-sample Z-test procedure is used to analyze the performance of features on damage evolution tracing.A feature named SR,which had better performance in tracking damage,is proposed to detect damage in planetary gear set.Meanwhile,the sun gear tooth-chipped seeded experiments with different severity are designed to validate the method above,and then the test vibration signal is picked up and used for damage detection.With the results of several experiments for quantitative damage detection,the feasibility and the effect of this approach are verified.The proposed method can supply an effective tool for degradation state identification in condition monitoring and health management of helicopter transmission system.     

基于递归理论的泵站压力管道运行状态监测

为了准确地识别建筑结构的模态参数,提出了一种基于多重信号分类算法（multiple signal classification,简称MUSIC）、经验小波变换（empirical wavelet transform,简称EWT）和同步提取小波变换（synchroextracting transform ,简称SET）的结构模态参数识别方法。首先,通过MUSIC-EWT对实测振动信号进行分解;其次,使用SET对单模态信号进行去噪处理;然后,采用自然环境激励技术（natural excitation technique,简称NExT）得到单模态信号的自由衰减响应;最后,利用Hilbert变换（hilbert transform,简称HT）和曲线拟合获得结构的自振频率和阻尼比。通过三层框架结构的数值模拟验证了该方法的准确性和鲁棒性。利用该方法对台风“达维”作用下广州中信广场的实测加速度数据进行分析,并将估计的结构模态参数和其他识别方法的分析结果进行对比,进一步证明了该方法的准确性和鲁棒性。     

基于递归理论的泵站压力管道运行状态监测

针对不利因素导致的管道运行异常问题,提出一种基于递归理论的泵站管道运行状态监测方法。首先,通过振动传感器提取压力管道关键部位的实测信息,并将同一位置不同方向的数据信息进行融合,得到一组反映结构整体动力特性的综合数据;其次,利用伪近临法与互信息法分别选取相空间重构参数m和τ;最后,绘制并计算代表管道动力特性的递归图及递归量化指标。将该方法应用于景泰川工程二期七泵站管道运行监测,通过设置不同的运行工况进行验证,结果表明：机组开关瞬间与稳定运行工况下,管道结构振动信号的递归图呈现不同模式,递归量化指标-确定性、对角线平均长度L、递归率及递归熵也呈现明显差异,能有效区分管道振动状态。该方法为压力管道的无损动态监测提供了新思路。     

Vibration based damage detection using large array sensors and spatial filters

In this paper, a novel approach for vibration based damage detection is proposed. The approach relies on the use of a large network of sensors (possibly hundreds of them) to which a programmable linear combiner is attached. The linear combiner is programmed to work as a modal filter. The frequency content of the output of the modal filter is proposed as feature for damage detection. It is shown that if a local damage is present, spurious peaks appear in the FRF of the modal filter whereas if temperature changes are considered, the FRF of the modal filter is shifted but its shape remains unchanged. The approach is interesting because of the ability to differentiate between local damage and global environmental changes to a structure. Issues about the practical implementation of the method are discussed.     

基于LTSA和RVM的复合材料损伤预测分析

提出一种基于局部切空间排序(local tangent space alignment,简称LTSA)和相关向量机(relevance uector machine,简称RVM)相结合的复合材料结构损伤演化与预测模型。针对复合材料结构损伤特性,采用疲劳振动试验进行结构损伤预测研究。首先,采用总体平均经验模态分解(ensemble empirical mode decomposition,简称EEMD)方法对多传感器采集的复合材料结构健康信息进行自适应分解,得到不同传感器下的多个本征模态分量(intrinsic mode function,简称IMF),并对IMF进行希尔伯特(Hilbert)变换,得到相应的Hilbert边际谱能量作为各传感器的特征信息;然后,采用LTSA进行多特征降维融合得到特征能量,对降维融合后得到特征能量采用距离形态相似度方法定义结构健康指数;最后,将结构健康指数作为建模数据,创建RVM预测模型,并通过预测结构健康指数完成复合材料结构损伤预测研究。验证结果表明,该模型可有效地对复合材料结构损伤进行预测。     

Damage detection and quantification using transmissibility

Structures experience various types of loads along their lifetime, which can be either static or dynamic and may be associated to phenomena of corrosion and chemical attack, among others. As a consequence, different types of structural damage can be produced; the deteriorated structure may have its capacity affected, leading to excessive vibration problems or even possible failure. It is very important to develop methods that are able to simultaneously detect the existence of damage and to quantify its extent. In this paper the authors propose a method to detect and quantify structural damage, using response transmissibilities measured along the structure. Some numerical simulations are presented and a comparison is made with results using frequency response functions. Experimental tests are also undertaken to validate the proposed technique.     

基于四电极法的CFRP结构损伤检测研究

碳纤维复合材料(CFRP)被广泛用于航空航天领域,实现其结构健康监测对提高适航审定的损伤容限探测水平、降低检测成本具有重要意义。针对飞机使用的CFRP层压结构材料,利用碳纤维的自传感特点及结构损伤的电学敏感特性,基于四电极法提出3种激励模式下的电阻抗无损检测方法,以实现非侵入、无辐射、低成本的快速无损结构健康监测。利用有限元分析软件COMSOL构建各向异性CFRP层压板模型,通过提取有效电压差与电压灵敏度参数,对比分析不同类型结构损伤检测效果,从而获取适用于CFRP层压板结构损伤检测的最优激励测量模式。综合实验结果表明,双电极激励模式整体表现较优。     

运用波传播和子结构技术检测结构损伤

提出了一种基于波传播和子结构技术来检测大型周期结构损伤的方法,分析了存在单一扰乱单元的有限周期结构的自由波传播,讨论了单元柔度变化对结构自振频率变化的敏感性。通过求解敏感性方程,用测得的自振频率的变化检测了大型周期结构的损伤位置和程度,并通过与子结构方法的结合,进一步提高了大型周期结构损伤检测的准确性和计算效率。对周期弹簧－质量结构损伤识别的数值结果说明,该方法不仅对结构损伤的位置和大小能够作出良好地预测,而且不需要知识未损伤结构的原始信息,只需要测得结构损伤前后的少数几个自振频率的变化,这对于实际的工程运用具有一定的吸引力。