基于非线性关联维特征提取的机械自动化监测系统

提取天然气压缩机故障状态下振动信号的故障特征是设计机械自动化检测系统的核心技术。提出一种基于非线性关联维特征提取的机械自动化监测系统设计方法,在故障诊断原理基础上,进行故障振动信号时间序列分析,设计故障振动信号相空间重构方法,改进了相空间重构最佳时延和嵌入维数参数计算的关键技术,通过提取关联维故障特征,在Simulink平台上设计了自动化监测系统。系统实验结果表明,该算法和系统能使各类故障状态下提取的关联维特征的标准差显著性降低,特征分布聚类能力明显提高,系统能有效检测各类故障,实现了机械设备的自动化监测,在自动化故障诊断仪表设计等领域具有较好的工程实践价值。     

一种灰色模糊油田区块水驱指标评价模型

针对油田开发中的不确定因素,结合油藏开发因素中的定性化指标,提出了一种基于油田开发水驱指标的模糊综合评价模型.通过灰色关联法定量筛选影响油田开发水驱因素的九项指标,运用层次分析法确定了各指标的权重,结合模糊数学中的判断矩阵实现了油田各区块的模糊综合评价.此方法不仅可以对所有区块进行总体评价,还能对各个具体区块进行精细的评价,为油田开发与管理提供了有效的指导.最后,通过实际例子验证了模型的有效性以及可行性.     

Prediction of liquid film mass transfer coefficients in packed columns using liquid holdup

A unique characteristic linear dimension (d), defined as the cube root of the specific liquid holdup (h_sp) in the packed column, was used to correlate successfully the liquid film mass transfer coefficient k_La for gas absorption-desorption for sparingly soluble gases in liquids below loading. To produce this simple, dimensionless correlation, k_La data reported in literature were used, covering a wide range of physical properties of liquids, packings and operating conditions. This new approach showed operating holdup as an important factor in gas liquid mass transfer.     

基于相关性阈值的NSCT图像去噪方法研究

利用非下采样Contourlet变换(NSCT)平移不变性、多分辨率、多方向的优点,提出一种基于尺度相关与阈值去噪相结合的非下采样Contourlet变换图像去噪方法。首先对噪声图像进行非下采样Contourlet变换,得到各个尺度各个方向子带的系数,然后采用相关系数归一的方法,结合Bayesian自适应阈值来达到更好的去噪效果。仿真实验表明,该方法在提高去噪后图像的峰值信噪比的同时,有效保留了图像的纹理信息,避免伪吉布斯现象,改善了图像的视觉效果。     

基于Fisher字典学习稀疏表示的高光谱图像分类

近年基于稀疏表示的分类框架(Sparse Representation based Classification,SRC)在计算机视觉和模式识别领域取得了巨大成功,高光谱图像解译也逐渐引入稀疏表示方法。针对基于SRC的高光谱图像分类算法随机抽取训练样本构成字典较难捕获相似类别的相对差异性信息问题,提出采用Fisher字典学习方法增强相似类训练样本的可区分性。此外,考虑到高光谱图像具有较强空间相关性的特点,设计一种简单有效的投票策略进行类别判决。大量实验表明:基于Fisher字典学习的联合投票分类方法能够较好地改善高光谱分类精度。     

基于半监督学习的一种图像检索方法

为了提高图像检索的质量, 提出了一种基于半监督学习的图像检索方法。该方法提取图像的颜色、形状、纹理特征, 计算得到已知类别样本的中心图像, 检索过程中利用中心图像自适应调整相关度计算函数, 然后根据与查询图像相关度的大小对图像进行检索和排序。实验结果表明：该方法较已有的基于内容的图像检索方法有更高的查准率, 同时, 由查准率—查全率曲线可知该方法能够达到很好的检索质量。     

Two-dimensional correlation relaxometry studies of cement pastes performed using a new one-sided NMR magnet

We present preliminary results of the first NMR T₁-T₂ two-dimensional relaxation correlation experiments performed using a one-sided NMR system in cement based materials. Two-dimensional correlation relaxometry has itself only recently been demonstrated in cement paste where it proved to be a particularly sensitive probe of pore-water dynamics providing direct information on exchange of water between the gel and capillary pore networks. Further to this we have observed differences in the structural development of a selection of cement pastes throughout the early stages of hydration and verified the theoretical frequency dependence of the ratio T₁ / T₂. When coupled with instrumentation developments in one-sided NMR magnets the way is opened to detailed, spatially resolved studies of the development of hydration and porosity in the surface layers (top 50 mm) of cementitious materials. A new magnet, suitable for such applications, is discussed.     

基于特征融合的加权SVM音频隐写分析算法

针对隐写分析中特征维数过高的问题,提出一种特征加权支持向量机音频隐写分析算法.利用特征相关性对原始特征进行优化选择,利用增益比率法计算特征权重,提出了改进特征加权支持向量机.与常用的C-SVM进行的对比实验表明,该方法能够有效提高检测率,降低时间复杂度.     

A minimum variance distortionless response filter based on the bifrequency spectrum for single-channel noise reduction

This paper deals with the problem of single-channel noise reduction in the short-time Fourier transform (STFT) domain. Many algorithms have been developed to solve this important problem, most of which generally assume that the STFT coefficients in different frequency bands are uncorrelated, so the noise reduction is achieved by applying a gain function to the STFT of the noisy speech in each frequency band. However, this assumption is not accurate and the STFT coefficients of speech signals between neighboring frequency bands are correlated in practice due to the use of small lengths of the fast Fourier transform (FFT) and overlap add/save techniques in implementation. This paper formulates the noise reduction problem by taking into account the interband correlation using the so-called bifrequency spectrum. Based on this formulation, a single-channel minimum variance distortionless response (MVDR) filter is derived, which is shown to be able to significantly improve the signal-to-noise ratio (SNR) and meanwhile maintain the desired speech not much distorted. Simulations are presented to justify the claimed merits of the developed MVDR filter.     

A correlation for the estimation of critical micellization concentrations and temperatures of polyols in aqueous solutions

An empirical correlation is presented for the estimation of critical micellization concentrations (CMC) and critical micellization temperatures (CMT) for poly(ethylene oxide)-block-poly(propylene oxide)-block-poly(ethylene oxide) copolymers in aqueous solutions. The CMC and CMT are expressed as a function of the polyol molecular weight, composition, and temperature (for CMC determination) or concentration (in the case of CMT). The correlation was developed from experimental CMT data for a set of 12 polyols that covered a wide range of molecular weights (2900–14600) and poly(ethylene oxide) contents (30–80 wt%) and is based on a simple expression for the standard free energy of micellization. Such a correlation should be useful to practitioners of the field as it allows easy prediction of CMC and CMT for a wide range of polyols with a minimal number of input parameters.