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。     

压电柔性梁裂缝损伤识别实验

针对压电柔性悬臂梁裂缝损伤检测与损伤程度识别问题,采用小波包分析和小波神经网络相结合的方法进行裂缝深度识别实验研究.利用小波包频带能量谱构造柔性悬臂梁裂缝损伤指标,即能量比相对变化量的H2范数,并建立压电柔性梁裂缝损伤实验装置.激励柔性梁的振动,记录两路压电传感器采集的振动信号,进行小波包分解并计算损伤指标.将这些损伤指标进行组合,作为小波神经网络的输入特征参数,进行裂缝深度即损伤程度的识别.实验结果表明:能量比相对变化量的H2范数对柔性梁的裂缝损伤敏感,对测试噪声不敏感;采用的小波神经网络可以精确识别柔性梁的裂缝深度.     

基于小波熵指标的结构损伤检测

对小波熵在土木工程结构损伤检测中的适用性进行分析,利用小波变换时一频局部化性能,将小波分析和信息熵结合起来,建立小波能谱熵、小波时间熵和相对小波熵等结构损伤指标.通过数值模拟和工字梁的试验数据对各指标和损伤识别方法进行了分析检验,识别出模拟梁和试验梁的损伤位置.识别结果表明,基于小波熵的指标是一个对结构局部损伤敏感的、比较好的损伤指标.     

基于归一化主模态差的装配式钢桥导梁损伤识别

为了解决装配式钢桥在结构损伤下的识别问题,选取了归一化主模态差作为标示量,对装配式钢桥导梁结构进行损伤识别。通过实测模型与有限元分析模型的固有频率和对应振型比较,验证桥梁导梁有限元模型的正确性;提出了运用归一化主模态差曲线图识别桥梁导梁损伤的方法,利用结构损伤时归一化主模态比无损伤时的归一化主模态刚度下降,损伤节点处振幅相对于正常状态数值增大,产生归一化主模态差正向突变来反映结构局部损伤的位置和损伤程度。通过模拟六种工况得到结构损伤部位会引起主模态差曲线的正向突变;并且损伤程度越重,对应的归一化主模态差越大。验证了损伤状态和正常状态之间的主模态差曲线可以判别装配式钢桥导梁的损伤位置和损伤严重程度。     

梁板结构的微小缺陷检测方法研究

针对板梁结构的微小缺陷识别问题,对板梁结构的模态振型和模态频率进行了研究,提出了基于小波变换和移动质量法的板梁结构缺陷识别方法。对"质量块在结构表面移动过程中,质量块-板梁耦合结构的固有频率会随移动位置的变化而改变,且当质量块位于结构缺陷位置时,固有频率会发生微小突变"的性质进行了研究,得到了随质量块位置变化的结构频移曲面;通过改变辅助质量块的位置来探测结构的动态特性,提出了应用离散小波变换分解板梁结构的振型和频移曲面的方法,提取结构的微弱缺陷信息,为板梁结构的微小缺陷检测提供了理论支撑。研究结果表明:该方法能够有效地识别板梁结构的微小缺陷,为以后的工程应用提供了一种实用的新检测方法。     

工字截面梁轨结构裂纹损伤的小波有限元定量诊断

研究工字截面梁轨结构裂纹定量识别中的正反问题,即通过裂纹位置和深度求解结构的固有频率以及利用结构的固有频率,识别裂纹位置和深度.裂纹被看作为一扭转线弹簧,利用工字梁裂纹应力强度因子推导出线弹簧刚度,构造出结构的小波有限元刚度矩阵和质量矩阵,从而获得裂纹结构的前3阶固有频率.通过行列式变换,将反问题求解简化为只含线弹簧刚度一个未知数的一元二次方程求根问题,分别做出以不同固有频率作为输入值时裂纹位置与裂纹深度之间的解曲线,曲线交点预测出裂纹的位置与深度,试验结果验证算法的有效性.     

基于小波分析的裂纹梁的损伤识别

阐述了一种基于小波变换的含裂纹梁的损伤识别方法,利用含裂纹梁的一阶模态阵型作为小波分析的力学特征信号,识别损伤的位置和大小.利用小波分析系数的模极大值随分析尺度的传播定位损伤的位置,计算针对于损伤频率信号的能量判断损伤的大小.与以前的小波分析方法相比,此方法确定损伤位置的可靠性高,能识别微小的损伤.利用能量守恒定理和小波分析频段细化的能力,裂纹的定量分辨率高.     

基于小波包变换的梁体损伤识别

由于小波包变换在分析非平稳信号方面较傅立叶变换更为有效，提出了基于小波包变换的能量变化率指标进行损伤识别的方法。首先，将得到的结构响应信号进行小波包分解，然后通过小波包能量变化率指标来进行损伤定位。通过3种不同损伤工况的梁体室内试验证明．损伤指标可以准确地识别损伤位置。     

基于小波方法的板结构损伤识别研究

进行不同边界条件下板结构损伤位置和大小的评估以及传感器布置和噪音对损伤识别影响研究。主要内容包括:首先,通过薄板结构的有限元模态分析,获取有无损伤板结构点的固有特性参数的分布状况,利用离散小波变换将矩形薄板的模态节点位移数据进行分解计算,获得损伤位置数据的高频信息和奇异值。其次,进行不同边界条件下的板结构损伤识别分析,利用小波系数的最大值变化率进行板结构损伤程度的定量化评估。最后,分析了传感器布置以及噪音情况下小波变换方法对板结构损伤识别的有效性。研究结果表明,四边固支约束下的小波系数比四边简支约束的小波系数大0.5%,比两边固支约束的小波系数大0.88%;在网格g=40 mm且通过小波变换对信号进行去噪处理之后都能够有效识别板结构损伤。说明该方法针对二维板结构损伤位置及程度的识别问题具有一定的有效性,能够为车辆结构损伤识别问题提供技术思路和参考价值。     

基于有限元的单梁式起重机结构损伤识别

针对单梁式起重机的缺陷问题,将有限元法和小波变换应用到结构缺陷识别中.建立了单梁式起重机梁的有限元分析模型,模拟计算了移动载荷作用下,梁结构在未损伤、微小损伤和较大损伤下的动态响应,重点研究了梁结构损伤对梁跨中响应信号的影响,发现损伤裂纹会使得梁跨中的响应信号产生间断点.通过MATLAB软件对仿真模拟得到的信号进行处理,可以明显判断损伤裂纹的空间位置,模拟计算结果对起重机结构损伤的检测和识别具有重要意义.     

Crack detection in simply supported beams without baseline modal parameters by stationary wavelet transform

There are significant changes in the vibration responses of cracked structures when the crack depth is significant in comparison to the depth of the structure. This fact enables the identification of cracks in structures from their vibration response data. However when the crack is relatively small, it is difficult to identify the presence of the crack by a mere observation of the vibration response data. A new approach for crack detection in beam-like structures is presented and applied to cracked simply supported beams in this paper. The approach is based on finding the difference between two sets of detail coefficients obtained by the use of the stationary wavelet transform (SWT) of two sets of mode shape data of the beam-like structure. These two sets of mode shape data, which constitute two new signal series, are obtained and reconstructed from the modal displacement data of a cracked simply supported beam. They represent the left half and the modified right half of the modal data of the simply supported beam. SWT is a redundant transform that doubles the number of input samples at each iteration. It provides a more accurate estimate of the variances at each scale and facilitates the identification of salient features in a signal, especially for recognising noise or signal rupture. It is well known that the mode shape of a beam containing a small crack is apparently a single smooth curve like that of an uncracked beam. However, the mode shape of the cracked beam actually exhibits a local peak or discontinuity in the region of damage. Therefore, the mode shape ‘signal’ of a cracked beam can be approximately considered as that of the uncracked beam contaminated by ‘noise’, which consists of response noise and the additional response due to the crack. Thus, the modal data can be decomposed by SWT into a smooth curve, called the approximation coefficient, and a detail coefficient. The difference of the detail coefficients of the two new signal series includes crack information that is useful for damage detection. The modal responses of the damaged simply supported beams used are computed using the finite element method. For real cases, mode shape data are affected by experimental noise. Therefore, mode shape data with a normally distributed random noise are also studied. The results show that the proposed method has great potential in crack detection of beam-like structures as it does not require the modal parameters of an uncracked beam as a baseline for crack detection. The effects of crack size, depth and location, and the effects of sampling interval are examined.     

复合材料结构损伤联合定位法试验研究

提出了复合材料结构损伤联合定位法,该法需首先获得复合材料结构在随机激励下的振动响应信号,计算结构的互相关函数幅值向量,通过对损伤结构的互相关函数幅值向量进行光滑拟合作为参考向量,再对损伤情况下的互相关函数幅值向量和参考向量分别进行连续小波变换,得到各自的小波系数,进而求得小波系数差的模,根据小波系数差的模的极值进行损伤的定位。该方法无需进行结构建模和模态识别,在无完好结构信息的情况下就可准确进行损伤定位。最后,还通过蜂窝夹层梁和玻璃纤维层合板的损伤检测试验,验证了该方法的有效性。     

基于小波分析的简支梁桥损伤识别

提出了基于小波子带信号能量曲率变化的损伤识别方法。分别对完好和损伤状态下结构的振动响应进行二进离散小波变换,通过信号子带分解与重构将响应分解到不同频带,使叠加的模态响应分离。定义了信号相对能量曲率差损伤指标,利用该指标对结构的损伤进行识别定位。应用此方法对一简支梁桥进行损伤数值分析,结果表明:二进离散小波变换可以对结构振动响应中叠加的多阶模态信息进行有效分离;信号相对能量曲率差指标可以对损伤进行有效识别,且不受激励位置及荷载大小影响。最后通过模型实验验证了该方法的正确性及可行性。     

Four-beam model for vibration analysis of a cantilever beam with an embedded horizontal crack

As one of the main failure modes, embedded cracks occur in beam structures due to periodic loads. Hence it is useful to investigate the dynamic characteristics of a beam structure with an embedded crack for early crack detection and diagnosis. A new four-beam model with local flexibilities at crack tips is developed to investigate the transverse vibration of a cantilever beam with an embedded horizontal crack; two separate beam segments are used to model the crack region to allow opening of crack surfaces. Each beam segment is considered as an Euler-Bernoulli beam. The governing equations and the matching and boundary conditions of the four-beam model are derived using Hamilton's principle. The natural frequencies and mode shapes of the four-beam model are calculated using the transfer matrix method. The effects of the crack length, depth, and location on the first three natural frequencies and mode shapes of the cracked cantilever beam are investigated. A continuous wavelet transform method is used to analyze the mode shapes of the cracked cantilever beam. It is shown that sudden changes in spatial variations of the wavelet coefficients of the mode shapes can be used to identify the length and location of an embedded horizontal crack. The first three natural frequencies and mode shapes of a cantilever beam with an embedded crack from the finite element method and an experimental investigation are used to validate the proposed model. Local deformations in the vicinity of the crack tips can be described by the proposed four-beam model, which cannot be captured by previous methods.     

采用EEMD和WPT的结构损伤特征提取方法

为了解决传统小波或小波包变换方法对结构损伤振动信号频率分辨率不高、易受邻近谐波交叠影响的问题,提出了一种基于聚类经验模式分解(EEMD)和小波包变换(WPT)的结构损伤特征提取方法.首先对原始信号进行EEMD分解,提取包含结构损伤信息的固有模式分量(IMF),再对其进行正交小波包分解,并计算小波包相对能量分布.该方法用于美国土木工程师学会(ASCE)提出的钢结构框架的损伤特征提取,结果表明:EEMD方法具有白噪声的剔除特性,可避免模式混叠的发生;不同检测节点处不同损伤工况的IMF小波包相对能量分布有显著的差异,可以作为一种理想指标表征结构损伤特征.     

An experimental study on damage detection of structures using a timber beam

Using vibration methods for the damage detection and structural health monitoring in bridge structures is rapidly developing. However, very little work has so far been reported on timber bridges. This paper intends to address such shortcomings by experimental investigation on a timber beam using a vibration based method to detect damage. A promising damage detection algorithm based on modal strain energy was adopted and modified to locate/evaluate damage. A laboratory investigation was conducted on a timber beam inflicted with various damage scenarios using modal tests. The modal parameters obtained from the undamaged and damaged state of the test beam were used in the computation of damage index, were then applied using a damage detection algorithm utilising modal strain energy and a statistical approach to detect location of damage. A mode shape reconstruction technique was used to enhance the capability of the damage detection algorithm with limited number of sensors. The test results and analysis show that location of damage can be accurately identified with limited sensors. The modified method is less dependent on the number of modes selected and can detect damage with a higher degree of confidence.     

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。     

Structural damage detection using the combination method of EMD and wavelet analysis

The use of the combination method of empirical mode decomposition(EMD) and wavelet analysis is explored for the detection of changes in the structural response data. Firstly, we adopt the EMD technique to decompose the response signal of structure vibration into several mono-component signals which become analytic signal by means of Hilbert transform. Then each mono-component signal is analysed via wavelet transform to detect the exact location and severity of damage. The results demonstrate that the combination method of EMD and continuous wavelet transform can be used to identify the time more sharply and effectively at which structural damage occurs than by using the wavelet transform method alone. The numerical simulation and the analysis of the response signal data from the shear building show that this method is effective.