结构基于振动损伤识别的发展概况

对目前关于结构基于振动损伤识别的基本方法和最新的研究进展进行了回顾,重点介绍了利用结构振动固有频率、位移振型、曲率模态振型、应变模态和神经网络法作了相关的讨论和评述.最后对这一研究领域的未来研究方向进行了展望.     

内齿轮成形磨削砂轮架振动特性实验研究

为提高内齿轮成形磨齿机砂轮架结构的稳定性,应用有限元对砂轮架进行了模态分析和谐响应分析,得到了磨削头的前6阶振型和固有频率,研究了砂轮架的应力和位移对频率的响应特性。基于响应曲面优化分析法对砂轮架结构参数进行多目标优化,确定最优的结构参数,提高振动特性。在多种磨削工况下对优化前后的磨削头进行振动试验,结构优化后的砂轮架在相同磨削工况下振动加速度比优化前小,磨削头工作稳定性得到明显提高,从而验证了有限元仿真建模和结构参数多目标优化的有效性和工程适用性。     

基于ANSYS的偏心轴模态分析

采用工程分析软件ANSYS进行偏心轴的建模与模态分析,把轴承弹性约束,分析该轴的前十阶固有频率和振型,有效预估结构的振动特性,为选择电机参数提供依据,并为谐响应分析及瞬态分析奠定基础。     

用低阶模型参数检测平台损伤

检测海洋平台损伤是项极其重要的探索研究。本文对空间框架结构的平台计算了损伤前和五种损伤状态的前四十阶特征值和特征矢量,损伤前后的前9阶和后7阶振型均属局部振动,第10阶至第33阶是整体振动。损伤前后第1阶整体振动的固有频率变化很小,损伤后只减小1%左右,但是,第2阶的固有频率损伤后最大的减少达到35%,第6阶开始固有频率减少趋于变小。特征矢量 U_y 在损伤部位损伤前后只是第2阶有比较大的变化,其他各阶变化甚小,因此用第2阶的固有频率和特征矢量 U_y 可以检测损伤,文中用第1,2,3阶整体振动的振型经正规化后的特征参数检测损伤,第2阶的位移特征参数 U_y~*在五种损伤状态检测能力都明显提高。同时还用第1、2阶整体振动的模态柔度比法检测损伤,得到五种损伤状态下第2阶的模态柔度比大大高于第1阶的模态柔度比的检测能力。因此提出用第2阶模型参数检测损伤更为有效。     

利用组合参数的结构损伤识别及试验研究

利用状态向量直接求导的新方法，全面地分析了基于结构振动模态参数(频率、特征向量和动柔度)关于设计参数(质量、刚度和阻尼)的相对灵敏度。该方法比传统的方法计算简单方便，而且弥补了传统方法中参数考虑不全的缺点，这样更符合实际工程。对一框架结构进行了数值模拟分析，研究表明动柔度矩阵关于结构刚度灵敏度相对于其他模态参数为最高，振型次之，频率为最小，这对选取损伤特征参数时有重要参考价值。提出由结构前几阶固有频率变化率、频率变化比值以及动柔度置信因子构成的组合参数作为神经网络的输入向量的损伤识别方法，对于多种工况进行了框架结构模型的振动试验。试验结果表明：采用组合参数训练的神经网络，对结构损伤位置和程度识别较采用单一参数具有更好的识别效果。     

振动筛振动模态测试及分析

模态分析是研究结构动力学特性的一种近代方法,是系统辨识方法在工程振动领域中的应用[1]。本文对某一型号振动筛进行实验模态分析,得到固有频率、阻尼比和振型等模态参数,分析该振动筛结构设计中存在的问题,为后续的仿真计算模型的修正和结构优化设计提供参考。     

利用静态响应并结合频率测试数据进行结构损伤识别

对土建结构进行动态测试,通常只能得到较准确的低阶固有频率而很难获得理论的振型测试结果。本文提出一套新的损伤识别算法。利用结构对静态加载的响应并结合低阶固有频率信息,对结构特性参数进行识别,由此确定可能的损伤位置。     

汽车座椅骨架固有频率的不确定度研究

工程中结构参数的随机性会导致结构固有频率不确定,而固有频率是影响结构振动和噪声的重要因素之一,因此研究结构固有频率不确定度尤为重要。提出一种基于响应面代理模型的固有频率不确定度研究方法。首先建立汽车座椅骨架有限元模型,利用试验设计筛选出对固有频率影响较大的设计变量,以便构建响应面代理模型。在考虑结构随机性因素基础上,基于响应面代理模型,分析设计变量满足不同分布时其对汽车座椅骨架的前3阶固有频率的不确定度和分布的影响。最后采用实验设计和蒙特卡洛相结合方法对结果进行验证。研究结果可为确定样本不同分布对固有频率的影响提供理论指导。     

基于频率变化识别结构损伤的摄动有限元方法

在结构有限元计算模型中定义了单元的损伤识别参数,将摄动理论与振动理论相结合导出结构振动特征值的一、二阶摄动方程,并由此建立了结构的一、二次损伤识别方程,给出了两种方程在欠定情况下求解损伤识别参数的优化算法。该方法仅使用在役结构固有频率测量值就能识别出结构的损伤位置和损伤程度,以及结构的老化程度,避免了使用模态振型识别结构损伤,因测量精度不高或自由度不足带来的误差。通过一座连续梁桥损伤识别的数值仿真结果,证明了该方法的有效性和实用性。该方法可用于大型结构的损伤识别或健康监测。     

基于有限元仿真的简支梁结构损伤分析

分析了简支梁结构的振动特性,建立了该结构损伤前后的有限元分析模型,模拟计算了简支梁结构在未损伤、一个损伤、两个损伤和三个损伤状况下的固有频率和振型,重点研究了不同损伤状况对它们的影响.发现损伤裂纹可使简支梁结构的固有频率降低,且其降低幅度随裂纹深度增大而增大,但不同位置的裂纹所产生的影响并不相同.模拟计算结果对简支梁结...     

Effects of local damage on vibration characteristics of composite pyramidal truss core sandwich structure

The effects of local damage on the natural frequencies and the corresponding vibration modes of composite pyramidal truss core sandwich structures are studied in the present paper. Hot press molding method is used to fabricate intact and damaged pyramidal truss core sandwich structures, and modal testing is carried out to obtain their natural frequencies. A FEM model is also constructed to investigate their vibration characteristics numerically. It is found that the calculated natural frequencies are in relatively good agreement with the measured results. By using the experimentally validated FEM model, a series of numerical analyses are conducted to further explore the effects of damage extent, damage location, damage form on the vibration characteristics of composite pyramidal truss core sandwich structures as well as the influence of boundary conditions. The conclusion derived from this study is expected to be useful for analyzing practical problems related to structural health monitoring of composite lattice sandwich structures.     

A compressive MUSIC spectral approach for identification of closely-spaced structural natural frequencies and post-earthquake damage detection

Motivated by practical needs to reduce data transmission payloads in wireless sensors for vibration-based monitoring of engineering structures, this paper proposes a novel approach for identifying resonant frequencies of white-noise excited structures using acceleration measurements acquired at rates significantly below the Nyquist rate. The approach adopts the deterministic co-prime sub-Nyquist sampling scheme, originally developed to facilitate telecommunication applications, to estimate the autocorrelation function of response acceleration time-histories of low-amplitude white-noise excited structures treated as realizations of a stationary stochastic process. Next, the standard multiple signal classification (MUSIC) spectral estimator is applied to the estimated autocorrelation function enabling the identification of structural natural frequencies with high resolution by simple peak picking in the frequency domain without posing any sparsity conditions to the signals. This is achieved by processing autocorrelation estimates without undertaking any (typically computationally expensive) signal reconstruction step in the time-domain, as required by various recently proposed in the literature sub-Nyquist compressive sensing-based approaches for structural health monitoring, while filtering out any broadband noise added during data acquisition. The accuracy and applicability of the proposed approach is first numerically assessed using computer-generated noise-corrupted acceleration time–history data obtained by a simulation-based framework examining white-noise excited structural systems with two closely-spaced modes of vibration carrying the same amount of energy, and a third isolated weakly excited vibrating mode. Further, damage detection potential of the developed method is numerically illustrated using a white-noise excited reinforced concrete 3-storey frame in a healthy and two damaged states caused by ground motions of increased intensity. The damage assessment relies on shifts in natural frequencies between the pre-earthquake and post-earthquake state. Overall, numerical results demonstrate that the considered approach can accurately identify structural resonances and detect structural damage associated with changes to natural frequencies as minor as 1% by sampling up to 78% below Nyquist rate for signal to noise ratio as low as 10dB. These results suggest that the adopted approach is robust and noise-immune while it can reduce data transmission requirements in acceleration wireless sensors for natural frequency identification and damage detection in engineering structures.     

Influence of Crack on Structure Vibration of Gear Tooth

This paper presents a theoretical model for analyzing the dynamic characteristic such as natural frequencies and vibration mode shapes of cracked gears. The influence of crack position and crack size on the dynamic characteristic of gears is thoroughly investigated using the proposed theoretical model as well as the finite element method (FEM) for the sake of model validation. The theoretical analysis and numerical simulation show that the influence of crack size and crack position on the dynamic responses of cracked gears is significant and that the influence of crack position is larger than that of crack size. The natural frequencies drop with the increase of crack size and the low order natural frequencies drop more notably. The natural frequencies drop more significantly when crack is located at tooth root than at tooth tip. The vibration mode shapes of cracked gear tooth are very different from those of gear tooth without crack, and the vibration amplitude increases significantly in crack neighborhood. These observations are very valuable for damage detection and fault diagnosis of gear system.     

Detection of outer raceway bearing defects in small induction motors using stator current analysis

We investigate the application of induction motor stator current spectral analysis (MCSA) for detection of rolling element bearing damage from the outer raceway. In this work, MCSA and vibration analysis are applied to induction motor to detect outer raceway defects in faulty bearings. Data acquisition, recording, and fast fourier transform (FFT) algorithms are done by using the Lab VIEW programming language. Experimental results verify the relationship between vibration analysis and MCSA, and identify the presence of outer raceway bearing defects in induction machines. This work also indicates that detecting fault frequencies by motor currents is more difficult than detecting them by vibration analysis. The use of intensive resolution FFT is recommended in MCSA for detecting faults easily. Reinstalling a faulty bearing can alter the characteristic frequencies and it is difficult to compare results from different bearings or even from the same bearing in different installations.     

压力机机身振动特性的模态分析

机身的振型和固有频率与其振动现象的发生有密切联系。为了改善冲压件的加工质量,提高模具的使用寿命和减小振动、避免共振,利用有限元软件ANSYS对JG21压力机机身的振动特性进行模态分析。得出表征机身振动特性的主要的5阶振型、固有频率以及相应的应变分布云图。通过分析其各阶振型的具体特点,总结在机身设计和压力机运行过程中以及分析方法方面应注意的问题。     

Modal parameter identification and vibration based damage detection of a multiple cracked cantilever beam

This paper presents a detailed investigation on the modal parameter identification and vibration based damage detection of a multiple cracked cantilever beam with hollow circular cross-section. To consider multiple crack effects, a cantilever beam including cracks is considered for six damage scenarios. Finite element models are constituted in ANSYS software for numerical solutions. The results are validated by experimental measurements. Ambient vibration tests are performed to extract the dynamic characteristics using Enhanced Frequency Domain Decomposition (EFDD) and Stochastic Subspace Identification (SSI) methods. Calculated and measured natural frequencies and mode shapes for undamaged and damaged beams are compared with each other. Automated model updating is carried out using the modal sensitivity method based on Bayesian parameter estimation to minimize the differences for damage detection. In addition, modal assurance criterion (MAC) and coordinated modal assurance criterion (COMAC) factors are obtained from the mode shapes and two set of measurements to establish the correlation between the measured and calculated values for damage location identification.     

Plasticity including the Bauschinger effect,studied by a neural network approach

Summary The first known vibration analysis of composite cantilevered shallow shells having right triangular and trapezoidal planforms is conducted. Accurate frequencies are obtained using the Ritz method with algebraic polynomials. This is demonstrated by detailed convergence studies. The lowest six natural frequencies for these shallow shells with double curvature are listed. Effects of curvature, material orthotropy and lamination angle on the natural frequencies are investigated.     

Identification of the dynamical properties of structures using free vibration data and distributed genetic algorithms

The dynamical properties of structures, such as natural frequencies, damping ratios and mode shapes, can be obtained by several identification methods. Some are based on the direct signal processing in a time domain; others transform response data to the frequency domain. The development of these techniques is useful in the production of more accurate structural models; they can be also used to test the level of damage in structures (or verify their strength to support new load actions) by using experimental data. There are situations where frequency domain algorithms and conventional system identification techniques fail, do not allow adequate solution of the identification problems or become trapped in a local optimum. It is in these cases where evolutionary optimization techniques are important tools for evaluating the dynamical properties of structural systems in practical applications. This article presents a methodology to determine the dynamic properties of structures knowing their response in terms of displacement, velocities or accelerations in the time domain when they are subjected to a free vibration excitation. In order to do that, a specialized evolutionary algorithm capable of adapting its parameters to the different types of registers obtained from the dynamic time response of a structure is implemented in a robust way, making this approach useful in practical situations. A distributed real genetic algorithm (DRGA) based on an island model of different subpopulations is used to adjust a simulated response signal of a building to the real response signal. Initially, computer-generated synthetic response signals are used but, in future, the approach will be validated with signals obtained from free vibration experimental tests and will be extended to other types of dynamical excitation signals. Finally, the method will be tested with data obtained from earthquake events.     

基于混沌粒子群算法的冰箱压缩机隔振优化设计

冰箱压缩机隔振系统的参数寻优问题关系到隔振成败,传统参数优化设计存在容易陷入局部最优和迭代发散问题。针对该问题建立压缩机4 点隔振的动力学模型,提出以隔振系统的6 自由度能量最大程度解耦为优化目、以4 点支撑的各向刚度为设计参数的系统频率离散分配优化方法,首次采用基于罚函数约束的混沌粒子群算法进行隔振参数寻优求解。结果表明,优化后隔振系统固有频率分配更加合理,主要方向解耦率得到显著提高。混沌粒子群算法克服传统序列二次规划法容易陷入局部最优的缺点,所得系统隔振效果优良,相对于遗传算法优化结果解耦程度更高。动力学仿真分析验证所提优化方法的合理性和有效性。