小波变换在压电陀螺仪信号去噪中的应用

提出了基于小波变换的陀螺仪信号的去噪方法.陀螺仪作为重要的敏感测量器件,其测量信号的精度很大程度上决定了系统的性能.利用信号与噪声进行小波变换后在各尺度空间呈现的不同特性,应用Daubechies四阶正交小波(db4)对噪声信号进行多层小波变换,逐层估计小波变换的各层细节信号的阈值,分别进行软阈值滤波处理,然后进行小波逆变换重建信号以达到对信号消噪和恢复的目的.采用该方法可以有效提高陀螺仪噪声环境下的测量精度.     

小波变换在压电陀螺仪信号去噪中的应用

提出了基于小波变换的陀螺仪信号的去噪方法.陀螺仪作为重要的敏感测量器件,其测量信号的精度很大程度上决定了系统的性能.利用信号与噪声进行小波变换后在各尺度空间呈现的不同特性,应用Daubechies四阶正交小波(db4)对噪声信号进行多层小波变换,逐层估计小波变换的各层细节信号的阈值,分别进行软阈值滤波处理,然后进行小波逆变换重建信号以达到对信号消噪和恢复的目的.采用该方法可以有效提高陀螺仪噪声环境下的测量精度.     

小波变换在摆式列车倾摆控制系统故障诊断中的应用研究

小波变换在故障诊断中得到较广泛的应用，但采用不同的小波，分析结果往往会有很大差异。对常用的正交、半正交、双正交小波提取信号特征的能力进行分析比较，表明半正交B样条小波因具有线性相位和采用较长的分解系列，而具有较好的局部化特性和较小的变换误差，是摆式列车倾摆控制系统故障诊断中的较佳小波基。提出一种新的确定故障诊断阈值的方法，并通过实验证明了方法的有效性，为小波变换在摆式列车实车倾摆控制系统故障诊断中的应用提供理论依据。     

基于二维双正交小波变换的贝壳表面形貌评定

研究表明海洋贝壳表面形貌与防污性能存在一定的关系。为评定贝壳表面形貌,探讨贝壳表面形貌与其防污性能关系,采用接触式表面轮廓测量仪对贝壳的表面形貌进行测量;运用二维双正交小波变换消除贝壳表面形貌测量数据中的形状误差,计算常用的表面特征参数。结果表明:运用二维双正交小波变换将贝壳表面形貌测量数据中的形状误差消除后,可得到更加合理的表面特征参数评定结果,可用于贝壳表面形貌的评定。     

提高小波变换在钻削刀具状态监测中效率与准确性的研究

通过研究采用正交小波变换进行刀具振动信号分解方法的不足,提出了采用具有自适应小波基的小波变换进行刀具振动信号分解、提高钻削刀具状态监测效率与准确性的方法     

小波变换轮廓术中快速相位展开方法研究

针对小波变换轮廓术中相位展开的精确性和快速性问题,提出了一种新的适用于小波变换轮廓术的相位展开方法.在使用小波变换得到条纹图像的相对相位分布的基础上,详细分析了利用小波变换脊处的尺度因子建立质量图指导相位展开的理论依据和实现方法,这种质量图建立方法有效反映了条纹图像各点的可靠性.在相位展开方面,针对全局洪水相位展开算法计算时间较长的问题,提出了根据质量图将相对相位分布图分层,然后逐层采用不同算法展开的方法.与全场洪水相位展开算法相比,该方法在保持较高测量精度的同时极大减少了相位展开所需的运算时间.计算机仿真和实物测量实验说明使用该方法可以得到准确的绝对相位值,处理速度较快.     

基于小波分析的单个线圈靶速度测量

小波变换具有空间局部化性质，因此可利用小波变换的模极大值点检测动态测量信号的突变点。提出了用单个线圈靶测量水下弹丸初速的原理及方法，由实弹射击实验获得的线圈靶信号，利用小波变换分析了弹丸穿越线圈靶时产生的电动势，建立了弹丸穿越线圈靶时的时间间隔t及运动弹丸速度的计算方法，并与双线圈靶弹丸初速测试结果进行了比对，证明了该方法的可行性。     

靶场测量中多镜头大视场视频图像拼接

摘 要：目的：为了得到靶场测量中需要的大视场全景视频图像,建立了多镜头大视场视频图像自动拼接系统,对该系统所采用的图像匹配、标记重叠区、无缝拼接等算法进行研究。方法：首先,介绍小波变换和小波包原理。接着,分析了根据小波系数进行匹配的小波变换图像匹配算法。然后,分析了比较旋转标记重叠区算法,即先匹配出多个拟重叠区,旋转后再做匹配计算,进而标记出唯一重叠区。最后分析了基于小波包变换的图像无缝拼接算法,即对图像作小波包变换,按频率融合小波系数,再根据这些系数恢复图像。结果：实验结果表明：本系统将四个 1.1°×0.88°的视场拼接得到一个大约3.3°×1.76°的大视场,拼接图像平滑无明显裂缝,处理速度可达10帧/s。结论：基本满足了靶场测量中大视场视频图像的需求。     

基于信号的正交小波构造及其在电机故障特征提取中的应用分析

本文讨论了小波变换的基本理论及小波函数与信号的相关系数对信号去噪效果的影响。在此基础上提出了基于信号的正交小波构造方法:根据信号的频域特征,对各频带系数进行加权处理,确定多尺度分析的生成元,从而构造L2空间的正交小波函数。应用不同小波函数提取750W整数槽化纤电机的振动信号的故障特征,实验结果表明采用此方法构造的小波函数能更加有效地从强噪声中提取故障特征,从而实现对电机故障的精确诊断。     

小波变换在陀螺信号去噪中的应用

提出了基于小波变换的陀螺信号的滤波方法,利用正交小波使用软阈值对陀螺输出信号进行去噪处理,去除由噪声引起的细节项,从而消除其中的噪声干扰.试验结果表明正交小波对陀螺信号去噪具有比较好的效果.     

非平稳信号自适应滤波的小波模型与滤波方法

分析自适应滤波和小波滤波的原理与方法,建立非平稳信号的自适应滤波的小波模型和滤波方法。利用小波变换的多尺度分解,将分离出来的噪声成分作为自适应滤波器的输入信号。通过自适应滤波器组能同时实现对多种噪声成分的最佳滤波,是实现信噪分离的最佳滤波方法,具有优良的滤波性能。模型验证和工程实例应用表明,该方法能实现非平稳信号在同频段对噪声成分和有用信号的最佳估计。     

Higher-density dyadic wavelet transform and its application

This paper proposes a higher-density dyadic wavelet transform with two generators, whose corresponding wavelet filters are band-pass and high-pass. The wavelet coefficients at each scale in this case have the same length as the signal. This leads to a new redundant dyadic wavelet transform, which is strictly shift invariant and further increases the sampling in the time dimension. We describe the definition of higher-density dyadic wavelet transform, and discuss the condition of perfect reconstruction of the signal from its wavelet coefficients. The fast implementation algorithm for the proposed transform is given as well. Compared with the higher-density discrete wavelet transform, the proposed transform is shift invariant. Applications into signal denoising indicate that the proposed wavelet transform has better denoising performance than other commonly used wavelet transforms. In the end, various typical wavelet transforms are applied to analyze the vibration signals of two faulty roller bearings, the results show that the proposed wavelet transform can more effectively extract the fault characteristics of the roller bearings than the other wavelet transforms.     

Vibration analysis of rotating machinery using time-frequency analysis and wavelet techniques

Time-frequency analysis, including the wavelet transform, is one of the new and powerful tools in the important field of structural health monitoring, using vibration analysis. Commonly-used signal analysis techniques, based on spectral approaches such as the fast Fourier transform, are powerful in diagnosing a variety of vibration-related problems in rotating machinery. Although these techniques provide powerful diagnostic tools in stationary conditions, they fail to do so in several practical cases involving non-stationary data, which could result either from fast operational conditions, such as the fast start-up of an electrical motor, or from the presence of a fault causing a discontinuity in the vibration signal being monitored. Although the short-time Fourier transform compensates well for the loss of time information incurred by the fast Fourier transform, it fails to successfully resolve fast-changing signals (such as transient signals) resulting from non-stationary environments. To mitigate this situation, wavelet transform tools are considered in this paper as they are superior to both the fast and short-time Fourier transforms in effectively analyzing non-stationary signals. These wavelet tools are applied here, with a suitable choice of a mother wavelet function, to a vibration monitoring system to accurately detect and localize faults occurring in this system. Two cases producing non-stationary signals are considered: stator-to-blade rubbing, and fast start-up and coast-down of a rotor. Two powerful wavelet techniques, namely the continuous wavelet and wavelet packet transforms, are used for the analysis of the monitored vibration signals. In addition, a novel algorithm is proposed and implemented here, which combines these two techniques and the idea of windowing a signal into a number of shaft revolutions to localize faults.     

电能质量小波检测与定位及基于多尺度能量曲线分类

从小波变换模极大值与信号突变点之间的关系出发，分析了信号幅值扰动的小波检测和定位，进行了相应的算例实测。利用不同扰动信号的小波变换在不同尺度上能量分布存在差异的特性，提出了基于小波变换多尺度能量曲线电能质量扰动类型的分类方法，并通过算例实测验证了其有效性。     

An algorithm for improving the coefficient accuracy of wavelet packet analysis

On the basis of analyzing the cause of coefficients distortion inhered in the existing wavelet packet transform algorithms, a new method is presented to rectify the distortion and improve the accuracy. Its principle is to implement compensation calculation by using the complementary characteristic of wavelet filters. The simulation result of a typical signal shows the method is effective in improving the accuracy of wavelet packet coefficients. The influences of the compensation calculation times and vanishing moments of the wavelet are analyzed. Theoretically, the maximum error could be reduced to 25% with one time compensation calculation. The results show that with two and four times compensation calculations, the error is reduced to 10% and 2% respectively. The experiment result of the vibration signal of a roller bearing with outer ring fault shows that the proposed method can effectively magnify the amplitude of the fault frequencies in practice.     

SAMPLING PRINCIPLE AND TECHNOLOGY IN WAVELET ANALYSIS FOR SIGNALS

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离散小波分析导论（一）：小波变换的基本思想,展缩方程,展缩小波

介绍了离散小波分析的基本理论，详细阐述了离散小波变换的实现方法，并指出离散小波变换的一些应用前景。     

Analysis,filtering, and decomposition of electron microscope images based on orthogonal transformations

Methods for estimating the integral characteristics of electron microscope image periodograms, based on Hartley transform, Q-transform, and cosine transform, are proposed. It is shown that the cosine transform is more appropriate for filtering and improvement of psychophysical image perception on its basis. Various approaches to implementing matched filtering via cosine transform are considered. A procedure of electron microscope image decomposition with the use of various orthogonal transforms and filters based on Fourier patterns of Gauss and Morle wavelets is proposed and studied. It is shown that electron microscope image structure analysis using scalograms of orthogonal image transforms is promising.     

平面四杆机构函数输出的小波变换分析

简述了小波变换的基本理论;给出了四杆机构输出函数的小波描述和小波分解的特性;利用Ｄａｕｂｅｃｈｉｅｓ正交小波对机构的输出函数进行了变换和分析,提出了机构输出函数小波特征参数的概念,为机构的函数尺寸综合时的参数识别提供了依据,最后给出了一个尺度综合的算例。