Scaling analysis of phase fluctuations in experimental three-phase flows

The characterization of complex patterns arising from three-phase (e.g., oil-gas-water) flows is an important problem with significant engineering and industrial applications. Based solely on measured conductance fluctuation signals from experimental three-phase flows, we propose a method to characterize and distinguish three commonly observed flow patterns. Using the phase characterization method, we first calculate the instantaneous phase from the signals. Then, through performing a scaling analysis, detrended fluctuation analysis (DFA), we extract scaling behaviors associated with the phase fluctuations and find that the DFA scaling exponent is sensitive to the transition among different flow patterns, which can be used to characterize nonlinear dynamics of the three-phase flow. From a novel perspective, we investigate the three-phase flow in terms of phase characterization and scaling analysis. The results indicate that our method can provide new insights into the exploration of complex mechanism in flow pattern transition. The effectiveness of the method is demonstrated and its broader applicability is articulated.     

Multifractal analysis of the UV/VIS spectra of malignant ascites: Confirmation of the diagnostic validity of a clinically evaluated spectral analysis

Multifractal (MF) approach was applied for the analysis of ultraviolet/visible (UV/VIS) spectra as an independent confirmation of the diagnostic efficacy of UV/VIS spectral analysis of intraperitoneal fluids, ascites, taken from patients with a known clinical diagnosis. Recently, it was reported that from UV/VIS spectra differentiation of malignant from benign ascites is possible. Here, it was shown that by using MF analysis of UV/VIS spectra, the objective classification of UV/VIS spectra is possible. The applicability of UV/VIS analysis and MF classification of spectra were evaluated on N=68 cases, of which M=64 and B=4 were clinically confirmed as malignant and benign, respectively. The overall diagnostic efficacy was 89.71% when using on-line analysis of UV/VIS spectra (61 out of 68 samples were positively recognized: 58 malignant and 3 benign), and even 95.59% by using off-line MF classsification (65 out of 68 samples were classified correctly: 63 malignant and 2 benign). It can be inferred that UV/VIS spectral analysis of ascites, combined with MF analysis, could be suggested as a successful and safe screening method in the evaluation of intraperitoneal fluids.     

基于方差一致的随机信号功率谱密度修正

由于分析频率间隔与频率分辨率的不同以及窗函数的使用,通常的功率谱密度数值计算可能会损失时域信号的方差信息,分析频率和信号长度选取不同时,得到的功率谱密度幅值不能够保证唯一性。为使得到的功率谱密度能够保持原始时域信号的方差信息,基于时域信号方差和功率谱密度的积分值的一致性,对功率谱密度进行了修正,得到的功率谱密度能够保持时域信号的方差信息,适用于更一般的分析频率要求。     

Studies of spectral properties of short genes using the wavelet subspace Hilbert–Huang transform (WSHHT)

This paper presents a new algorithm for the analysis of spectral properties of short genes using the wavelet transform and the Hilbert–Huang transform (HHT). A wavelet subspace algorithm combined with the empirical mode decomposition (EMD) is introduced to create subdivided intrinsic mode functions (IMFs) and a cross-correlation analysis is applied to remove pseudo-spectral components. Experiments are carried out on DNA sequences with the double-base (DB) curve representation and the results show that the signal-to-noise ratio of buried signals can be enhanced using the proposed method, yielding significant patterns that are rarely observed with conventional methods. The wavelet subspace Hilbert–Huang transform (WSHHT) algorithm is able to correctly identify spectral patterns of very short genes (below 70 bp) in DNA sequences.     

Characterization of micro-lenses based on single interferogram analysis using Hilbert transformation

Measurement of the shape, surface quality, and optical performance of micro-lenses, as well as, the uniformity of the parameters across the wafer is an important issue. In this paper we describe a reflection/transmission microscopic interferometer for characterization of micro-lens array. A Hilbert transform (HT) based method is applied to enhance the fringe contrast and to recover the phase from a single fringe pattern with closed fringes. The reflection mode of operation reveals the geometrical properties of the array whereas transmission mode of operation provides information regarding the focal properties of the micro-lenses. Experimental results on a square-packed fused silica micro-lens array are presented.     

EMD时频分析拉曼光谱和近红外光谱

用时频方法分析拉曼光谱和近红外光谱。经验模态分解光谱成为特征模态分量,模态分量比重计算显示拉曼光谱能量均匀分布于各个分量,而近红外光谱的低阶特征模态分量只承载了较少的原光谱有效信息。真实光谱和数值实验均显示,经验模态分解视拉曼光谱为调幅信号,具有高频能量吸附特性; 视近红外光谱为调频信号,在一阶特征模态分量中可以较好实现高频窄带解调。一阶特征模态分量希尔伯特变换显示,经验模态分解拉曼光谱时易出现模态混叠现象。进一步在时频域分析玉米叶片近红外光谱,经验模态分解后截掉低能量的一、二阶分量,用剩余特征模态分量重构光谱信号,均方根误差为1.001 1,相关系数为0.981 3,两个指标反映出重构精度较高; 分解趋势项表明在近红外光波段,吸光度随着波长的减小呈现递增趋势; 特征模态分量的希尔伯特变换显示,657 cm-1是碱胁迫光谱特有频率,可作为碱胁迫光谱特征频率来辨识。     

航空光谱相机反射镜部件的有限元分析

反射镜是光谱相机的关键元件,为保证在复杂环境下的成像质量,有必要对其进行研究分析以验证结构设计的可靠性。针对反射镜在工作中的面形变化及结构的动力学性能,应用有限元分析软件MSC.Nastran对反射镜部件进行了静力分析及随机振动分析。计算结果表明,装配时压紧力对反射镜面形变化影响明显,可根据计算结果指导装调;随机振动分析结果表明,反射镜部件结构设计可靠,符合结构破坏的3σ原则,能够满足成像对反射镜位置精度和面形精度的要求。     

基于EMD-AWPP和HOSA-SVM算法的分布式光纤振动入侵信号的特征提取与识别

针对传统的信号处理方法无法有效区分不同振动入侵信号,提出一种基于EMD-AWPP和HOSA-SVM算法的振动信息特征提取与识别方法,用于解决分布式光纤振动入侵检测系统的高精度信号识别问题。处理不同振动类型时,该方法首先利用基于经验模态分解的自适应小波包处理算法,不仅对信号的低频部分进行了分解,而且对高频部分即信号的细节部分也进行了更好的时频局部化处理,改善了信号特征提取精度,减少传感信号异常值的影响; 其次采用高阶谱分析中的双谱和双相干谱,精确提取包含不同振动入侵信号类型的特征矢量; 最后在BPNN参比模型的基础上,用粒子群算法优化SVM的识别参数,使识别模型具有更强的自适应和自学习能力,克服了神经网络易陷入局部最优的不足之处,实现不同振动入侵信号的特征矢量识别。分析结果表明,针对不同类型的入侵源识别,该方法可以有效剔除随机噪声的影响,提取传感信息的特征矢量,降低异常值的影响,算法的预测类别与输出类别几乎一致,振动识别的精确率达到95%以上,识别效果明显强于BPNN网络的检测算法,提高了信息分析的准确性。     

Denoising of chaotic signal using independent component analysis and empirical mode decomposition with circulate translating

In this paper, a new method to reduce noises within chaotic signals based on ICA(independent component analysis)and EMD(empirical mode decomposition) is proposed. The basic idea is decomposing chaotic signals and constructing multidimensional input vectors, firstly, on the base of EMD and its translation invariance. Secondly, it makes the independent component analysis on the input vectors, which means that a self adapting denoising is carried out for the intrinsic mode functions(IMFs) of chaotic signals. Finally, all IMFs compose the new denoised chaotic signal. Experiments on the Lorenz chaotic signal composed of different Gaussian noises and the monthly observed chaotic sequence on sunspots were put into practice. The results proved that the method proposed in this paper is effective in denoising of chaotic signals.Moreover, it can correct the center point in the phase space effectively, which makes it approach the real track of the chaotic attractor.     

Noise source identification of diesel engine based on variational mode decomposition and robust independent component analysis

Through separating and identifying the noise sources of diesel engine, each independent noise obtained can be used as reference for the noise reduction, condition monitoring and fault diagnosis. In the noise source identification of diesel engine, the combustion noise and the piston slap noise are found to be overlapped in time domain and frequency domain. So it is intricate to accurately separate them. Therefore, the noise source identification method which is based on variational mode decomposition (VMD), robust independent component analysis (RobustICA) and continuous wavelet transform (CWT) is proposed. In the test, a 6-cylinder diesel engine was tested in a semi-anechoic chamber. The lead wrapped method was adopted to wrap No. 1–5 cylinders so as to isolate the interference noises, only the No. 6 cylinder part was bared. The single channel noise signal of cylinder head was measured. Then the variational mode decomposition algorithm is utilized to decompose the noise signal into several variational mode components. The RobustICA algorithm is adopted to extract the independent components. Finally, the continuous wavelet transform and the prior knowledge of diesel engine are applied to further identify the separated results. The results show that by using the proposed method to separate and identify the radiation noise of the cylinder head of the diesel engine, the independent components obtained are respectively the combustion noise and the piston slap noise. Comparing with the EEMD-RobustICA-CWT method, each independent noises obtained through the proposed method are more accurate and pure with less other interference noises.