基于小波的医学图像去噪方法研究

为有效地表现医学图像原有信息中有用的信息,降低医学图像受噪声干扰的现象,减少诊断误差,本文将现有的小波图像去噪方法运用于医学图像,并对各种方法进行实验分析比较,以提供医学参考。实验发现,与较常用的均值滤波与中值滤波相比,小波去噪方法有效提高了医学图像的去噪PSNR值。     

对南方山地勘探激发试验实施方式的新思考

针对南方山地野外地震采集过程中关于如何实施激发试验提出了两点疑问,并对疑问进行了深入的思考,同时在CXN地区进行了一系列激发试验研究探讨,主要研究了传统的井深试验、药量试验的特点,指出其存在的欠科学性,并对这些问题进行了重点分析,提出了相应的解决方法。     

改进的基于移动小波树的数据流异常检测方法

针对移动小波树数据流异常检测算法的不足,提出了一种改进的移动小波树异常检测方法,利用比率阈值去除颠簸数据的干扰,提高了检测精度;利用二分查找检测算法,提高了检测的效率;结合实时增量更新算法满足了数据流在线处理的要求;改进了阈值设定方法,可实现双边异常检测。用射线数据和电能质量扰动数据进行仿真实验,结果验证了方法的有效性。     

Hydrodynamics of gas-solid flow around immersed tubes in bubbling fluidized beds

A numerical study was conducted based on the gas-solid two-fluid model using the body-fitted coordinate system to analyze the behavior of particles and bubbles flow in bubbling fluidized beds without and with immersed tubes. The kinetic theory of granular flow was implemented in the model. The images of simulated instantaneous particle concentration and velocity gave the process of the formation, coalescence and eruption of bubbles. The effects of the tube pitch and superficial gas velocity on the fluidization in a bubbling fluidized bed were investigated. Calculated bubble frequencies without and with immersed tubes were in agreement with previous experimental and simulation findings. The wavelet multi-resolution analysis was used to analyze the simulated data of instantaneous particle concentration. From the random-like particle concentration fluctuations, the fluctuating components due to particle flow and bubble motion can be extracted based on the wavelet multi-resolution analysis over a time-frequency plane.     

基于K均值与WPA-RBF神经网络模拟电路故障诊断

针对模拟电路故障诊断进行了研究,提出了一种新的方法。该方法包括haar的小波分解,对数据的归一化处理,以及用K均值优化RBF的中心向量和宽度,用狼群算法优化RBF的权值。首先用haar小波对所得的电路原始故障数据集进行变换,然后对变换后的数据进行归一化处理,最终得出RBF神经网络训练所需的输入数据。针对RBF神经网络中隐层节点中心、基函数宽度及权值选取困难问题,这里用K均值优化RBF的中心向量和宽度,用狼群算法优化RBF的权值,以提高网络训练稳定性与诊断成功率。最终通过两个电路的诊断实例,来论述该方法的具体实现过程,验证用该方法进行模拟电路故障诊断的可行性。     

Bearing failure detection using matching pursuit

In this paper, a new approach to the detection of localized defects of rolling element bearings is proposed. It employs matching pursuit with time–frequency atoms to analyze bearing vibration and extract vibration signatures. In particular, this approach utilizes not only the temporal and spectral but also the scale characteristics of the vibration generated due to the presence of a defect for the detection. This leads to a high signal-to-noise ratio and facilitates considerably the detection at the early stage of failure development. Experimental results show that the proposed approach is sensitive and reliable and works better than continuous wavelet transform and envelope detection.     

基于改进的K-means聚类图像分割算法

介绍一种采用K—L变换、二维向量小波和改进的K—means结合的图像分割算法。阐述和分析了二维向量小波变换和Laws纹理能量测度，得出图像每个像素点可用9个纹理特性来描述的结论。运用K—means算法的思想对其进行改进，最后得出分割后的图像。试验结果证明，运用以上处理方法可显著提高分割速度和精度。     

基于虚拟仪器的溢流阀动态特性测试技术

在分析溢流阀动态特性测试原理的基础上，设计了溢流阀动态特性测试虚拟仪器系统。此系统应用小波降噪的方法提高测试信号的质量，然后提取信号特征点，得到溢流阀动态特性的各项参数。     

小波分析在液压缸泄漏检测中的应用

本文介绍了一种基于小波分析的液压缸泄漏故障检测方法，通过检测液压缸工作腔压力信号小波变换在适当尺度上的极大值点，提取出压力信号的突变特征，从而为液压缸泄漏检测提供了定量的依据。     

小波变换在管道弱超声回波奇异性检测中的应用

研究了小波变换在细尺度下检测信号奇异性的原理。通过对样管中标准缺陷的超声回波分析试验,证明6层db5小波变换可以有效地分离出湮没在噪声中的微弱缺陷信号,并可以有效地分离出信号的孤立奇异点,准确定位缺陷出现时刻。