基于独立成分分析(ICA)处理两相流信号

为了提高固体速度测量精度，提供一种基于独立成分分析（ICA）处理两相流信号的基本方法。首先介绍独立成分分析（ICA）的基本原理，然后介绍使用空间滤波和小波变换获得固体速度的方法。最后给出仿真实验结果证明该方法可行。     

独立成分分析在两相流速度测量中的应用

文中提出一种基于独立成分分析和相关法测量两相流速度的方法。首先介绍独立成分分析的基本原理，然后利用独立成分分析分别分离出上游和下游传感器的两相流混合信号，并据此画出对应两相流信号的相关函数曲线，得到不同速度信号的渡越时间。最后给出仿真宴验的处理结果。     

Classification System of Raman Spectra using Cluster Analysis to Diagnose Coronary Artery Lesions

Abstract

The traditional methods employed to detect atherosclerotic lesions allow for the identification of lesions; however, they do not provide specific characterization of the lesion's biochemistry. Currently, Raman spectroscopy techniques are widely used as a characterization method for unknown substances, which makes this technique very important for detecting atherosclerotic lesions. The spectral interpretation is based on the analysis of frequency peaks present in the signal; however, spectra obtained from the same substance can show peaks slightly different and these differences make difficult the creation of an automatic method for spectral signal analysis. This paper presents a signal analysis method based on a clustering technique that allows for the classification of spectra as well as the inference of a diagnosis about the arterial wall condition. The objective is to develop a computational tool that is able to create clusters of spectra according to the arterial wall state and, after data collection, to allow for the classification of a specific spectrum into its correct cluster.     

独立分量分析在机械振动信号分离中的应用

针对机械运转时工作环境复杂,监控采集的信号多为混合信号的情况,研究了如何从混合信号中分离出相对应的各振动源信号.采用独立分量分析的分离方法,通过对极大似然估计的目标函数进行简化,基于无需选择学习率的快速不动点迭代的优化方法,选用可同时估计亚高斯和超高斯独立成分的非线性函数估计概率密度,推导出了该算法.最后,对工程中几种特殊情况下的混合信号进行仿真和实验室实测的分离试验.结果表明,算法简单易行,具有快速稳定收敛的性质.     

基于小波变换和ICA的滚动轴承早期故障诊断

滚动轴承早期故障诊断的关键在于如何从低信噪比混合信号中检测出显著的轴承故障特征频率。提出以连续小波变换(CWT)和独立分量分析(ICA)相结合的方法来诊断单通道信号的滚动轴承早期故障,提出按频谱等间隔选取伪中心频率的小波分解尺度,并对ICA处理后的信号进行包络频谱分析以确定故障类型。最后,利用实际的滚动轴承实验数据对该方法进行了验证。     

Extraction of Respiratory Activity from Photoplethysmographic Signals Based on an Independent Component Analysis Technique: Preliminary Report

Abstract

A new method is reported for monitoring respiratory activity using photoplethysmography (PPG) without the need of prior knowledge of the respiratory rate range. Two channels of transmission mode PPG signals were collected from the subject's index finger and analyzed using an independent component analysis (ICA) algorithm. The respiratory activity was separated from the heart‐related pulsation in PPG after the ICA analysis. The results demonstrated that the ICA analysis could successfully extract normal and simulated apnoea respiratory activities. The algorithm was applied for both simulated signals and those collected from 10 young normal adults. The reported technique may be potentially used for the simultaneous monitoring of the pulse rate and respiratory activity based on the hardware of current pulse oximetry devices. The structure and implementation of this preliminary respiratory activity monitoring system were presented. Possible further improvements for the system performance were also discussed.     

独立分量分析在货车轴承故障诊断中的应用

提出基于独立分量分析的故障诊断方法,数值试验结果表明,基于独立分量分析的故障诊断方法能有效地诊断滚动轴承的外圈、内圈和滚动体的故障,而且比传统的共振解调法的性能更好。     

Micro‐Raman Spectroscopy Study of Human Pterygium and Conjunctival Melanocytic Nevi

Pterygium, a common ophthalmic disease that is caused by fibrovascular growth of conjunctiva and conjunctival melanocytic nevi that is another conjunctival disease, are detected by Raman spectroscopy in the present study. We find that there is an obvious increase in the intensity at the peak of 1,583 cm^?1 that is assigned to C=C unsaturated fatty acids stretch of lipids in the pterygium tissue, and 1,639 cm^?1 also increased which belongs to amide I. Also, PCA (Principal Component Analysis) was used to classify the normal conjunctiva from the pterygium tissue. For the conjunctival melanocytic nevi, the intensity of Raman spectrum region between 1,550 cm^?1 and 1,650 cm^?1 that belong to protein has increased, which indicates that the content of protein in conjunctival melanocytic nevi is more richer than the normal ones. SCANNING 34: 395–398, 2012. © 2012 Wiley Periodicals, Inc.     

基于独立分量分析的潜艇振源贡献量定量计算方法

振动噪声控制对于潜艇具有重要意义。常用的振动噪声分析方法仅分析了噪声的来源,而未对振动噪声源对总振动噪声的贡献量进行定量计算。介绍盲源分离基本模型,以及基于独立分量分析理论和聚类评价方法提高盲分离性能的改进固定点算法,并基于该算法和先验信息理论提出一种定量计算振源贡献量的新方法。通过仿真试验分析基于两种不同分离准则算法的分离性能以及振源贡献量计算结果。将该方法应用于某型号潜艇缩比模型振源贡献量的定量计算中,对比分析表明该方法具有很高的计算精度。研究结论可为振动噪声的主动控制提供可靠的依据。     

Constrained independent component analysis and its application to machine fault diagnosis

For machine fault diagnosis the signals from working machine are always numerous, even uncountable, but there contains only a little useful information. Hence how to find out the useful signal from numerous signals, including noises, that is, how to only extract the desired fault signal is very attractive. This paper shows that the constrained independent component analysis (cICA) can solely extract desired faulty signal using some prior mechanical information. The methods of creating reference of cICA for machine diagnostics are discussed, and the effectiveness of the method is successfully verified by simulations and experiments.     

复合ICA-SVM机械状态模式分类

提出了一种新颖的、基于独立分量分析(ICA)的复合神经网络，用于不同机械状态模式的特征提取。利用支持向量机(SVM)进行最终分类。与通常的基于经验风险最小化(ERM)原理的神经网络方法相比，基于结构风险最小化(SRM)原理的支持向量机分类方法具有更好的推广能力。而借助多个独立分量分析网络，隐藏于多通道振动观测信号中的不变特征得到有效提取，从而实现了支持向量机分类器在分类能力和推广性两者间的合理平衡。     

基于FFT-MCC分析的ICA(BSS)盲不确定性消除

为了消除ICA（BSS）估计的幅值、相位及排序等盲不确定性，提出一种基于快速傅里叶变换与最大相关准则分析的ICA（BSS）估计源自适应校正方法。借助对原始传感观测及估计源的频谱分析，近似获得各本底源信号在观测信号中所占的比重——初始放大权值；基于最大相关准则优化调整ICA（BSS）估计源的相位，并对初始放大权值进行微调，从而消除ICA（BSS）估计的盲不确定性，实现源波形的恢复及其混合参数的估计。仿真试验结果证明了该方法的有效性，也表明它在复杂系统源识别或重建方面具有较大的应用潜力。     

Quantification of anhydrous ethanol and detection of adulterants in commercial Brazilian gasoline by Raman spectroscopy

Raman spectroscopy can be used to evaluate the quality of fuels in a remote, rapid, and nondestructive manner without the need for reagents. In this study, Raman was used to quantify anhydrous ethanol in commercial gasoline and to detect peaks due to compounds commonly used for the adulteration of commercial gasoline. Samples of commercial gasoline were collected from fuel stations in the region of Santos, SP, Brazil. Samples of naphtha from the refinery, pure ethanol, and ethanol diluted in distilled water at concentrations close to the range used in the gasoline were also obtained and characterized. Raman spectra were collected using a dispersive Raman spectrometer (830?nm, 2?cm^?1 resolution in the 400–1800?cm^?1 spectral range). As expected, the spectra of commercial gasoline showed pronounced peaks of naphtha and ethanol. By using the peak intensities of the ethanol diluted in water, the ethanol concentration was found to be in the range of 27%?±?1% in most of the samples; some samples presented ethanol concentrations as high as 28.8%, suggesting adulteration. Some samples presented peaks at 766, 798, and 995?cm^?1 with higher intensities, suggesting the presence of an adulterant with organic characteristics, such as solvents with aromatic rings. Raman spectroscopy has been shown to be effective in determining the adulteration of commercial gasoline, which may contribute to rapid quality control of fuels at the point of sale.     

Novel combined instrumentation for laser-induced breakdown spectroscopy and Raman spectroscopy for the in situ atomic and molecular analysis of minerals

Abstract

An instrument combining laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy was developed for the in situ atomic and molecular composition analysis of minerals. The apparatus consists of an optical system, a sample chamber, a spectrometer for Raman and another for LIBS, as well as a control system equipped with laboratory-written software. Gypsum, calcite, prehnite, pearl, lazurite, and several mixtures of NaBr and CaCO₃ were selected as samples for evaluation of the performance of the instrument. Sulfate, carbonate, silicate, and crystalline water were identified and different structures of CaCO₃ were clearly distinguished by the use of a Gaussian fit. The limit of detection for CaCO₃ in a NaBr mixture was 5.7?mg/g by Raman. LIBS was employed to determine calcium, magnesium, iron, sodium, aluminum, and carbon with the newly developed system. The limits of detection obtained for Ca, Na, and C were 90.2?μg/g, 84.6?μg/g, and 2.5?mg/g, respectively. The experimental results from commercial Raman spectroscopy instruments were used to verify and support the measurements from this novel instrument.     

基于小波分析的FastICA联合降噪方法在滚动轴承故障诊断中的应用研究

采用小波分析方法进行振动信号降噪存在选取参数依靠经验的问题,采用独立分量分析（ICA）方法进行振动信号降噪存在欠定问题,为了避免小波降噪以及ICA方法单独使用的缺点,提出了将小波降噪分析和基于负熵的FastICA独立分量分析相结合来处理滚动轴承含噪振动信号的方法。首先对原始信号进行小波降噪处理,然后将处理后的信号与原始信号组成FastICA的输入矩阵,进行FastICA降噪处理,最后利用滚动轴承振动信号对该方法进行有效性验证。实验分析表明：该方法增大了振动信号的峭度值,达到了滚动轴承振动信号降噪的目的。     

LMD-ICA联合降噪方法在滚动轴承故障诊断中的应用

针对经典独立分量分析（ICA）只能应用于观测源数不少于信号源数的超定盲源分离问题,提出局部均值分解和ICA相结合的欠定盲源分离新方法。该方法将采集的单通道振动信号进行局部均值分解,基于互相关准则对分解的分量进行重组,构建虚拟噪声通道;将虚拟噪声通道与振动信号作为盲源分离的信号输入,采用基于负熵的FastICA算法实现信号源和噪声的分离,从而达到降噪目的。将该方法应用于滚动轴承故障信号,频谱分析结果表明,该方法处理后的信号中噪声得到一定程度滤除,频谱中毛刺更少,故障特征频率更加明显,有利于故障特征的提取,实验分析证明了该方法的有效性。     

基于形态分量分析与能量算子解调的齿轮箱复合故障诊断方法

针对齿轮箱复合故障的故障特征分离,提出了一种基于形态分量分析与能量算子解调的齿轮箱复合故障诊断方法。该方法先根据振动信号中各组成成分形态的差异,采用形态分量分析方法构建不同形态的稀疏表示字典进行故障成分分离,将齿轮箱复合故障信号分解为包含齿轮故障信息的谐振分量、包含轴承故障信息的冲击分量和噪声分量,然后分别对谐振分量和冲击分量进行能量算子解调分析,最后根据各解调谱诊断齿轮和轴承故障。算法仿真和应用实例表明该方法能有效地分离齿轮箱复合故障振动信号中齿轮与轴承的故障特征。     

基于GC-MS和LC-MS的人参冰酒成分分析

为研究人参冰酒的活性成分,采用气相色谱-三重四极杆质谱(GC-QQQ-MS/MS)法,通过DB-Heavy WAX色谱柱(30 m×0.25 mm×0.25 μm)分离,以分流比1∶20,程序升温的方法对人参冰酒中挥发性成分进行分析。采用超高效液相色谱-四极杆静电场轨道阱高分辨质谱(UPLC-Q-Orbitrap-HRMS)法,通过 Sigma HPLC Column C18色谱柱(5 cm×3.0 mm×2.7 μm),以乙腈-0.1%甲酸水溶液为流动相,流速0.2 mL/min,梯度洗脱的方法分析人参冰酒中多酚和皂苷类成分。根据高分辨质谱提供的准分子离子峰和碎片离子信息,得到化合物的相对分子质量和结构信息,结合化合物的保留时间和相关文献,共鉴定出28种挥发性成分、28种皂苷类成分和24种多酚类成分。本研究有助于明确人参冰酒的有效成分,可为人参冰酒的鉴别及质量评价提供数据支持。     

基于形态分量分析和包络谱的轴承故障诊断

滚动轴承出现局部损伤时,其振动信号往往由包含轴承自身振动的谐振分量、包含轴承故障信息的冲击分量及随机噪声分量构成。提出了基于形态分量分析和包络谱的滚动轴承故障诊断方法。该方法根据轴承振动信号中各组成成分的形态差异,利用改进的形态分量分析对滚动轴承故障振动信号中的谐振分量、冲击分量和噪声分量进行分离,然后对冲击分量进行Hilbert包络解调分析,根据包络谱诊断滚动轴承故障。算法仿真和应用实例表明,该方法能有效提取滚动轴承故障特征。     

语义背景下基于形式概念分析的产品族组件规划与类型识别研究

提出了语义背景下产品族规划阶段基于形式概念分析的组件规划与类型识别新方法,采用网络本体语言建立产品族语义信息模型,进而获取产品族语义形式背景,应用Hasse图描述组件形态分布,并在此基础上用Galois格理论进行组件类型识别。研究表明,基于形式概念分析的组件类型识别和组件规划方法不仅具备传统Pareto方法所具有的零部件通用性评价功能和使用频率统计功能,还能从整体上动态地规划组件在产品族中的布局,最后以某冰箱产品族规划实例进行了验证。