Multi-faults diagnosis of rolling bearings via adaptive customization of flexible analytical wavelet bases

Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features, as well as its easy burying in the complex, non-stationary structural vibrations and strong background noises. In this paper, a method based on the flexible analytical wavelet transform (FAWT) possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings. During the route of the proposed method, the proper FAWT bases are constructed via genetic optimization algorithm (GA) based on maximizing the spectral correlated kurtosis (SCK) which is firstly presented and proved to be efficient and effective in indicating interested fault mode. Via using the customized FAWT bases for each interested fault mode, the original vibration measurements are decomposed into fine frequency subbands, and the sensitive subband which enhances the signal-to-noise ratio (SNR) is selected to exhibit the fault signature on its envelope spectrum. The proposed method is tested via simulated signals, and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace, inner-race and roller defects. The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.     

子波变换在实验流体力学中的应用

介绍了子波分析的历史、基本知识以及在实验流体力学方面的应用。讨论了子波变换在客观辨识湍流边界层相干结构方面的应用。作者用子波变换的方法提出了确定湍流边界层相干结构挥发时间尺度的能量最大准则，提取了相干结构对应的速度信号波形。用于波变换研究了湍流边界层脉动速度信号的局部奇异性行为，发现相干结构发生处脉动速度信号的局部奇异性指数为负值。     

构件裂纹缺陷的超声识别

将小波包多分辨率分析与能量谱相结合,提出了金属材料缺陷特征提取的方法(小波包子带能量比较法)及不同缺陷的识别方法(小波分形神经网络法)。选取最能反映缺陷特征的参数——"能量特征向量"作为特征参数,进行缺陷的特征提取。缺陷的识别方法将小波包分解后各子带系数的分形维数作为特征矢量,对其进行径向基神经网络训练,从而可很明显区分出有无裂纹以及不同裂纹信号。以航天发射塔架钢连接构件疲劳裂纹超声检测信号为例,使用所提出的特征提取和模式识别方法,结果表明是行之有效的新方法,为金属材料缺陷检测与识别开拓了新思路。     

量子力学中的Heisenberg测不准原理的数学推导以及在小波分析中的应用

从傅里叶变换的定义出发,利用时变信号的短时傅里叶变换,推导出量子力学中的Heisenberg测不准原理,说明了两者之间存在这种联系的必然性,并给出了测不准原理在小波分析中的应用举例。     

基于小波分析的虚拟仪器

以小波分析原理为基础,开发出可视化和可操作的虚拟仪器,用于处理实验数据与药物分析.应用小波变换实现数据消噪,利用LabVIEW 和MATLAB软件开发出虚拟仪器.用该仪器可实现对数据进行消噪;在不经分离的情况下,对药物实现多组分的含量测定及对实验结果进行分析和预测,采用的方法和开发的软件在药学领域有其独到的应用价值.     

小波分析在航空发动机性能趋势监控中的应用

简要分析了小波变换的原理、应用和算法。利用MATLAB编程，初步探讨了小波分析在发动机性能监控方面的应用。最后，通过实际的发动机数据对这种方法进行了验证，并对结果和应用前景进行了讨论。     

Flight Flutter Modal Parameters Identification with Atmospheric Turbulence Excitation Based on Wavelet Transformation

针对基于大气紊流激励的飞机颤振试验数据具有信噪比低以及测量数据以加速度响应形式给出等特点,将小波变换与随机减量法相结合对飞机颤振模态参数进行识别,首先利用随机减量法获得结构在非零初始加速度条件下的自由衰减响应,然后对该自由衰减响应进行Morlet连续小波变换,为使变换简单,本文采用了Parseval定理和留数定理,利用Morlet的带通滤波特性,通过搜索小波变换系数在不同的尺度区域内的极大值,再根据小波变换系数的极大值、相角与固有振动频率及阻尼系数间的关系,即可识别出各模态参数。并对利用小波变换识别颤振模态参数时,实现模态解耦应满足的条件进行了分析研究。通过仿真和飞机颤振试验数据分析,验证了该识别方法不仅简单、有效和可行,而且具有较强的抗噪性。     

二维小波变换及其在医学图像处理中的应用

介绍了二维离散小波变换的一般形式，在图像分解的基础上．分析了二维小波变换在医学图像消噪和图像增强中的应用，同时给出应用实例。结果表明，应用小波分析进行医学图像处理，能够有效地改善图像质量，有利于医生对病情的诊断和治疗。     

强光光学零件加工误差频谱分析与控制方法研究

本文利用功率谱密度分析磁流变抛光表面的敏感频率误差,发现走刀步距与中高频误差具有直接的关联性,通过小波算法确定其分布区域后,采用大束径的光顺抛光法对敏感频率误差进行控制,测试结果表明中高频误差得到了有效控制。本研究对强光光学零件加工误差的频谱分析、表征和控制具有指导意义。     

A nonlinear background removal method for seismo-ionospheric anomaly analysis under a complex solar activity scenario: A case study of the M9.0 Tohoku earthquake

A precise determination of ionospheric total electron content (TEC) anomaly variations that are likely associated with large earthquakes as observed by global positioning system (GPS) requires the elimination of the ionospheric effect from irregular solar electromagnetic radiation. In particular, revealing the seismo-ionospheric anomalies when earthquakes occurred during periods of high solar activity is of utmost importance. To overcome this constraint, a multiresolution time series processing technique based on wavelet transform applicable to global ionosphere map (GIM) TEC data was used to remove the nonlinear effect from solar radiation for the earthquake that struck Tohoku, Japan, on 11 March, 2011. As a result, it was found that the extracted TEC have a good correlation with the measured solar extreme ultraviolet flux in 26–34 nm (EUV_26–34) and the 10.7 cm solar radio flux (F_10.7). After removing the influence of solar radiation origin in GIM TEC, the analysis results show that the TEC around the forthcoming epicenter and its conjugate were significantly enhanced in the afternoon period of 8 March 2011, 3 days before the earthquake. The spatial distributions of the TEC anomalous and extreme enhancements indicate that the earthquake preparation process had brought with a TEC anomaly area of size approximately 1650 and 5700 km in the latitudinal and longitudinal directions, respectively.