基于小波分析的结构损伤检测发展现状与展望

基于小波分析的结构损伤检测技术，以其良好的应用前景，已成为目前学术界、工程界研究的热点。在回顾和总结了小波分析理论及其在结构损伤检测中研究现状的基础上，对今后的发展进行了讨论和展望。     

基于MODWPT的Hilbert谱及其在齿轮故障诊断中的应用

在对基于最大重叠离散小波包变换(Maximal overlap discrete wavelet packet transform,简称MODWPT)的Hilbert谱方法进行介绍的基础上,将基于MODWPT的Hilbert谱应用于齿轮故障诊断当中。采用MOWDWPT可将多分量的复杂信号分解为若干个瞬时频率和瞬时幅值具有经典物理意义的单分量之和,然后求出各个单分量信号的瞬时频率和瞬时幅值,再进行组合便可以得到原始复杂信号完整的时频分布。对具有裂纹和断齿的齿轮故障振动信号的分析结果表明,基于MODWPT的Hilbert谱可以有效地提取齿轮振动信号的故障特征。     

Band Depth Clustering for Nonstationary Time Series and Wind Speed Behavior

We explore the behavior of wind speed over time, using a subset of the Eastern Wind Dataset published by the National Renewable Energy Laboratory. This dataset gives modeled wind speeds over three years at hundreds of potential wind farm sites. Wind speed analysis is necessary to the integration of wind energy into the power grid; short-term variability in wind speed affects decisions about usage of other power sources, so that the shape of the wind speed time series becomes as important as the overall level. To assess differences in intra-day time series, we propose a functional distance measure, the band distance, which extends the band depth of López-Pintado and Romo. This measure emphasizes the shape of time series or functional observations relative to other members of a dataset and allows clustering of observations without reliance on pointwise Euclidean distance. We show a method for adjusting for seasonal effects in wind speed, and use these standardizations as input for the band distance. We demonstrate the utility of the new method in simulation studies and an application to the MOST power grid algorithm, where the band distance improves reliability over standard methods at a comparable cost.     

广义解调时频分析方法在调制信号处理中的应用

介绍了一种新的信号处理方法-基于广义解调的时频分析方法,并将这种方法应用于调制信号的处理。广义解调时频分析方法采用广义解调将时频分布是曲线的信号变换为时频分布是平行于时间坐标轴的直线的信号,然后采用最大重叠离散小波包变换（Maximal overlap discrete wavelet packet transform,简称MODWPT）对广义解调后的信号进行分解,得到若干个瞬时频率和瞬时幅值都具有物理意义的单分量信号,再对各个单分量信号进行逆广义解调,进一步求出瞬时频率和瞬时幅值,从而得到原始信号完整的时频分布。采用广义解调时频分析方法对调幅-调频信号进行了分析,结果表明该方法能有效地提取调幅-调频信号的调制信息。     

分形信号的小波分析

本文提出了分形信号的小波分解与重构的一种快速算法。针对分形信号的自相似和长时相关的特点,采取离散小波变换（ＤＷＴ）对分形信号进行多尺度分解,使其成为各尺度上的近似平稳信号,从而可利用通常的Ｗｉｅｎｅｒ滤波＾［５］或Ｋａｌｍａｎ滤波＾［７］方法进行估计,然后再由ＤＷＴ进行多尺度重构,估计出被噪声污染了的原始信号。本文重点对分形信号的ＤＷＴ进行算法设计,并估计了计算复杂度。     

基于广义解调时频分析的多分量信号分解方法

广义解调时频分析方法是一种新的信号处理方法，该方法将广义解凋和最大重叠离散小波包变换相结合对复杂信号进行分解，得到若干个瞬时频率和瞬时幅值都具有物理意义的单分量信号，从而获得原始信号完整的时频分布。本文在介绍广义解调时频分析方法的基础上，将该方法用于多分量信号的分析，对该方法进行了改进，给出了由改进的广义解调时频分析方法分解多分量信号的具体步骤，从而由改进后的广义解调时频分析方法不仅可以得到原始信号中各个分量的时域波形，而且还可以得到相同的时频分布。采用改进后的广义解调时频分析方法对仿真信号进行了分析，同时和其它时频分析方法进行了比较，结果表明了该方法的有效性。最后，对广义解调时频分析方法中的相位函数选择问题进行了讨论。     

包装过程的故障检测与诊断

对于控制复杂、难以精确描述数学模型的包装过程,提出了基于小波变换的故障检测方法,故障诊断能过神经网络来实现。     

基于双正交小波变换的资源二号卫星与多光谱影像融合方法研究

针对基于Darbechies等正交小波函数的遥感影像融合时引起失真的现象,引入双正交小波函数,提出了基于双正交小波变换的融合方法,对资源二号卫星和TM的多光谱影像的融合进行研究,并把融合结果与主成分、IHS和Brovey等融合结果进行比较。通过对光谱特征曲线、相关系数、光谱扭曲程度等分析和空间细节的对比,说明双正交小波融合方法除了提高空间分辨率外,最好地保持了多光谱影像的光谱特征,有利于专题信息的提取。     

结构裂纹时序分析的几种识别法

本文利用随机时间序列模式识别技术对具有闭裂纹和开裂纹的工程梁结构进行了故障及其类型的诊断和判别。利用AR(n)模型建立并推导了Fisher 线性判别函数、广义残差方差判别函数、格林函数面积特征量和距离判别函数(即欧几里德距离、K—L 信息距离和广义残差方差距离)。对一悬臂梁在不同状态下的62组随机响应数据进行了故障诊断和判别分析。结果表明,本文所提出的识别方法具有良好的准确度和可靠性,可直接用于结构故障的实时在线诊断和状态监测。     

大跨空间结构风模拟的改进方法及其小波识别

大跨空间结构风速时程模拟需考虑风的时间相关性和空间相关性。利用线性滤波器法并结合快速Foutier变换（FFT）对球面网壳结构进行多点脉动风速时程模拟，较好地解决风速时程的模拟精度、模拟速度和计算稳定性问题。利用小波变换良好的时频局部化性质和可变的聚焦特性，针对模拟的风速时程低频含量较少的特点，利用haar小波对风速时程进行小波分解和识别，修正分解后的低频含量。计算显示，重构修正后的风速时程在时域和频域上均更逼近目标风速时程。     

抗亮度调整攻击的小波域图像数字水印方法

现有的许多小波变换域图像数字水印方法无法抵抗亮度调整攻击,为此,本丈提出了一个抗亮度调整攻击的小波变换域图像数字水印新方法.该方法在原始图像小波变换域的低频系数中嵌入水印,而在含水印图像小波变换域低频系数抗亮度调整修正后的值中提取水印.该方法简单、快速、有效,在提取水印时无需原始图像.实验结果表明:该方法具有很好的水印透明性,对亮度调整攻击非常稳健,并且对常见的其他图像处理攻击(如重采样、颜色抖动、平滑、加噪声和有损压缩等)具有很强的稳健性.     

一种强噪声背景下的微弱信号检测的新方法

基于自适应滤波算法对小波滤波器的构造方法进行了研究,重点在于解决对强噪声环境下微弱信号提取所需要的小波变换的子带自适应滤波器的构造,把小波变换技术和自适应滤波技术应用于微弱信号的检测。提出基于自适应小波变换的心电信号的检测,利用小波变换的子带编码理论,通过在多个子带权值的自适应匹配,回复后拟合微弱信号。仿真结果表明,该方法可进一步改善信号的检测能力,在检测微弱信号的特征和改善信噪比方面是一种十分有效的方法。     

Efficient and Stable Numerical Methods for Multi-Term Time Fractional Sub-Diffusion Equations

Some efficient numerical schemes are proposed for solving one-dimensional (1D) and two-dimensional (2D) multi-term time fractional sub-diffusion equations, combining the compact difference approach for the spatial discretisation and $L1$ approximation for the multi-term time Caputo fractional derivatives. The stability and convergence of these difference schemes are theoretically established. Several numerical examples are implemented, testifying to their efficiency and confirming their convergence order.     

滚动轴承振动信号的小波奇异性故障检测研究

该文以滚动轴承振动信号为分析对象 ,基于小波奇异性分析原理进行滚动轴承故障检测新方法的研究。通过求解待测信号的小波变换极大模来检测和识别信号中奇异点位置和奇异性大小 ,以及对噪声极大模的抑制处理 ,达到抑制或消除噪声的目的 ;最后 ,在剩余小波极大模的基础上进行信号重构 ,展现原待测信号中的故障信号模式。通过对铁路货车车轮用滚柱轴承振动信号的分析表明 ,此方法在大幅度地提高信噪比的同时 ,对由轴承损伤冲击造成的信号突变仍保持了较高的灵敏度和分辨率。为滚动轴承故障检测打下了良好的基础。     

A novel key-frame selection-based sign language recognition framework for the video data

ABSTRACT

Sign language is a medium of communication for people with hearing disabilities. Static and dynamic gestures are identified in a video-based sign language recognition and translated them into humanly understandable phrases to achieve the communication objective. However, videos contain redundant Key-frames which require additional processing. Number of such Key-frames can be reduced. The selection of particular Key-frames without losing the required information is a challenging task. The Key-frame extraction algorithm is used which helps to speed-up the sign language recognition process by extracting essential key-frames. The proposed framework eliminates the computation overhead by picking up the distinct Key-frames for the recognition process. Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Histograms of Oriented Gradient (HOG) are used for unique features extraction. We used the bagged tree, boosted tree ensemble method, Fine KNN, and SVM for classification. We tested methodology on video-based datasets of Pakistani Sign Language. It achieved an overall 97.5% accuracy on 37 Urdu alphabets and 95.6% accuracy on 100 common words.     

谐波及无功分量实时检测的一种小波方法

从小波函数的带通性质出发,利用小波变换在不同尺度下对非正弦电流信号进行检测,由此得出了它的基波和谐波分量及其有效值. 通过重构基波分量与电源电压之间的相位差,求得了信号中的基波无功电流分量. 为说明所提出检测方法的有效性,进行了相应的仿真研究,并讨论了影响检测精度的因素.     

Comparison of Spectral and Wavelet Estimators of Transfer Function for Linear Systems

We compare spectral and wavelet estimators of the response amplitude operator (RAO) of a linear system, with various input signals and added noise scenarios. The comparison is based on a model of a heaving buoy wave energy device (HBWED), which oscillates vertically as a single mode of vibration linear system. HBWEDs and other single degree of freedom wave energy devices such as oscillating wave surge convertors (OWSC) are currently deployed in the ocean, making such devices important systems to both model and analyse in some detail. The results of the comparison relate to any linear system. It was found that the wavelet estimator of the RAO offers no advantage over the spectral estimators if both input and response time series data are noise free and long time series are available. If there is noise on only the response time series, only the wavelet estimator or the spectral estimator that uses the cross-spectrum of the input and response signals in the numerator should be used. For the case of noise on only the input time series, only the spectral estimator that uses the cross-spectrum in the denominator gives a sensible estimate of the RAO. If both the input and response signals are corrupted with noise, a modification to both the input and response spectrum estimates can provide a good estimator of the RAO. A combination of wavelet and spectral methods is introduced as an alternative RAO estimator. The conclusions apply for autoregressive emulators of sea surface elevation, impulse, and pseudorandom binary sequences (PRBS) inputs. However, a wavelet estimator is needed in the special case of a chirp input where the signal has a continuously varying frequency.     

GPU Computing based fast discrete wavelet transform for l1-regularized SPIRiT reconstruction

Parallel imaging is a technique to shorten the acquisition time by reducing the data size in phase encoding direction. Compressed Sensing is a technique to improve the performance of parallel imaging based reconstruction methods such as l₁-regularized SPIRiT by adding the regularization term, which leads to frequent calculations of Discrete Wavelet Transform (DWT) with high time cost. However, clinical practice of MRI scan requires fast or real-time reconstruction with high image quality. In this paper, by taking advantage of the properties of parallel imaging and GPU computing, we develop a fast three-dimensional DWT for parallel imaging based reconstruction methods such as l₁-regularized SPIRiT. Computational results show that fast DWT in l₁-regularized SPIRiT MRI reconstruction is approximately three times faster than the conventional DWT. Computational results also show that fast DWT for reconstructing an 80?×?150?×?32?×?80 Cardiac MRI dataset by l₁-regularized SPIRiT is approximately 20 per cent faster than l₁-regularized SPIRiT of the conventional DWT.     

铁磁性管道腐蚀远场涡流检测性能的改进

远场涡流检测由于信号微弱、探头过长等缺点限制了其进一步应用.本文结合有限元仿真和实验方法,研究了改进远场涡流技术性能的几种方法,即: 采用电磁屏蔽、磁路进行传感器优化设计以缩短探头长度、增大信号强度;改进信号调理电路以提高细微缺陷检出能力;利用同态滤波、小波变换以及误差修正等数字信号处理技术确保检测结果的可靠性.实验结果表明,采用上述方法后系统性能得到很大提高,可以有效检测出管道外壁的细微缺陷.     

An evolutionary optimization-based approach for simulation of endurance time load functions

A novel optimization method based on Imperialist Competitive Algorithm (ICA) for simulating endurance time (ET) excitations was proposed. The ET excitations are monotonically intensifying acceleration time histories that are used as dynamic loading. Simulation of ET excitations by using evolutionary algorithms has been challenging due to the presence of a large number of decision variables that are highly correlated due to the dynamic nature of the problem. Optimal parameter values of the ICA algorithm for simulating ETEFs were evaluated and were used to simulate ET excitations. In order to increase the capability of the ICA and provide further search in the optimization space, this algorithm was combined with simulated annealing (SA). The new excitation results were compared with the current practice for simulation of ET excitations. It was shown that the proposed ICA-SA method leads to more accurate ET excitations than the classical optimization methods.