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.     

Manifold structure preservative for hyperspectral target detection

A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.     

钣金制件表面的相贯线求作方法

本文提出钣金制件表面相贯线求作的新方法。     

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。     

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。     

化学镀Ni—P合金等温处理的结构转变

利用电子显微术研究了化学镀Ni—P合金层在260℃等温不同时间的非晶-晶体转变。结果表明,晶体镍首先从非晶态中析出,Ni_3P相亦直接从非晶态中生成,而不经过亚稳过渡相。     

面天线检测数据处理方法的探讨

对面天线检测数据处理方法作了一些有益的探讨。从获取被测物的三维坐标后到获取真正有用的信息这一过程需要经过坐标转换和表面误差计算两个步骤 ,其中坐标转换是关键。在坐标转换方面 ,文中提出了曲面自由拟合、公共点转换和CAD面型转换三种方法 ,阐述了这些方法的数学模型 ,并且用实测数据进行了验证计算。理论分析和实际计算两方面显示 :CAD面型转换法既不需要天线的曲面方程 ,也不需要有已知的公共点 ,结果准确、可靠 ,是一种理想的方法 ;如果没有天线的CAD面型 ,但却存在公共点时 ,公共点转换法也是较理想的方法 ,其结果与给定的公共点误差有关 ;如果既没有天线的CAD面型又无公共点或公共点误差很大时 ,只能采用曲面自由拟合法 ,该法准确度最高 ,但容易使天线面型产生错位现象     

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。     

钛的相变织构及其影响因素研究

通过晶体学取向分布函数（ＣＯＤＦ）法研究了冷轧形变量、再结晶退火和相变循环次数等因素对钛相变织构形成的影响。结果表明冷轧形变量对相变织构的形成影响最大。再结晶退火后钛的相交织构漫散。多次循环相变并不改变相变织构的类型。