Fault Recognition of Rolling Bearings Based on Parameter Optimized Multi-Scale Permutation Entropy and Gath-Geva

To extract fault features of rolling bearing vibration signals precisely, a fault diagnosis method based on parameter optimized multi-scale permutation entropy (MPE) and Gath-Geva (GG) clustering is proposed. The method can select the important parameters of MPE method adaptively, overcome the disadvantages of fixed MPE parameters and greatly improve the accuracy of fault identification. Firstly, aiming at the problem of parameter determination and considering the interaction among parameters comprehensively of MPE, taking skewness of MPE as fitness function, the time series length and embedding dimension were optimized respectively by particle swarm optimization (PSO) algorithm. Then the fault features of rolling bearing were extracted by parameter optimized MPE and the standard clustering centers is obtained with GG clustering. Finally, the samples are clustered with the Euclid nearness degree to obtain recognition rate. The validity of the parameter optimization is proved by calculating the partition coefficient and average fuzzy entropy. Compared with unoptimized MPE, the propose method has a higher fault recognition rate.     

Parameter fitting for piano sound synthesis by physical modeling

A difficult issue in the synthesis of piano tones by physical models is to choose the values of the parameters governing the hammer-string model. In fact, these parameters are hard to estimate from static measurements, causing the synthesis sounds to be unrealistic. An original approach that estimates the parameters of a piano model, from the measurement of the string vibration, by minimizing a perceptual criterion is proposed. The minimization process that was used is a combination of a gradient method and a simulated annealing algorithm, in order to avoid convergence problems in case of multiple local minima. The criterion, based on the tristimulus concept, takes into account the spectral energy density in three bands, each allowing particular parameters to be estimated. The optimization process has been run on signals measured on an experimental setup. The parameters thus estimated provided a better sound quality than the one obtained using a global energetic criterion. Both the sound's attack and its brightness were better preserved. This quality gain was obtained for parameter values very close to the initial ones, showing that only slight deviations are necessary to make synthetic sounds closer to the real ones.     

The influence of fractality on the time evolution of the diffusion process

In the literature, the deviations from standard behaviors of the solutions of the kinetic equation and the analogous diffusion equation are put forward by investigations which are carried out in the frame of fractional mathematics and nonextensive physics. On the other hand, the physical origins of the order of derivative namely α in fractional mathematics and the entropy index q in nonextensive physics are a topic of interest in scientific media. In this study, the solutions of the diffusion equation which have been obtained in the framework of fractional mathematics and nonextensive physics are revised. The diffusion equation is solved by the cumulative diminuation/growth method which has been developed by two of the present authors and physical nature of the parameters α and q are enlightened in connection with fractality of space and the memory effect. It has been emphasized that the mathematical basis of deviations from standard behavior in the distribution functions could be established by fractional mathematics where as the physical mechanism could be revealed using the cumulative diminuation/growth method.     

Elastic scattering and the K matrix: (II). Phase shifts,resonances and few-level approximations

The K-matrix expansions given in part I are applied to the scattering by a square-well potential. Their convergence proves very satisfactory from a physical point of view since few-level approximations allow very good approximations to the phase shifts and cross sections. It also appears that all the complex poles of K_l and the real ones with positive residue should undoubtedly be associated with physical resonances. As for the real ones with negative residue, i.e. the echo poles, they are obviously unrelated to resonances, but they provide a very good parametrization of the background part of the scattering. The time delay is given a major role in the argument. The possibility of having double poles is also discussed and sum rules are given for the energies and residues of the poles.     

A new interpretation of percolation conductivity results with large critical regimes

A two parameter equation which has the same mathematical form as the percolation equation is presented. One parameter is the critical volume (area) fraction of the insulator. The other, the exponent, is a combination of an effective demagnetization coefficient for the insulating dispersion and the critical fraction. The equation reduces to dilute effective media theory and to Bruggeman's symmetric and asymmetric media theories as limiting cases. The equation is shown to fit experimental data with standard deviations of less than 0.01, over the entire conducting range.     

目标极点提取的改进算法

针对强电磁脉冲孔耦合瞬态响应的极点参数提取问题,将传统的矩阵束算法进行改进。通过对含有噪声的瞬态响应数据进行互相关处理,能有效提高低信噪比时极点的提取精度。再将数据经离散化后构造Hankle矩阵,结合奇异值分解,求解其广义特征值,即可提取信号的极点参数信息。最后通过仿真分析以及对波形的重构,验证改进算法具有抗噪能力强、拟合度高的特点。     

A novel variable resolution global spectral method on the sphere

A variable resolution global spectral method is created on the sphere using High resolution Tropical Belt Transformation (HTBT). HTBT belongs to a class of map called reparametrisation maps. HTBT parametrisation of the sphere generates a clustering of points in the entire tropical belt; the density of the grid point distribution decreases smoothly in the domain outside the tropics. This variable resolution method creates finer resolution in the tropics and coarser resolution at the poles. The use of FFT procedure and Gaussian quadrature for the spectral computations retains the numerical efficiency available with the standard global spectral method. Accuracy of the method for meteorological computations are demonstrated by solving Helmholtz equation and non-divergent barotropic vorticity equation on the sphere.     

Optimized fuzzy C-means clustering algorithm for the interpretation of the near-infrared spectra of rocks

The rock near-infrared spectrum contains information of its composition and structure. The interpretation of rock near-infrared spectrum is one of the important approaches in the qualitative and quantitative analyses of the alteration minerals in rock. The rock near-infrared spectra are classified using optimized fuzzy C-means clustering algorithm, and the main mineral composition is obtained for different rock samples through the analysis of cluster centers. The minimum Spectral Correlation Coefficient is used as the objective function to classify the simulation data. In this study, the classification method was first tested for parameter setting using simulation data, which was the mixture of several standard mineral spectra quantified in terms of reflectivity in the near-infrared band. Classification accuracies under different fuzzy index values are compared. When the fuzzy index value is 1.5, the classification accuracy of the simulation samples is 83%. The initial values of different cluster centers were shown to affect the classification result. In the practical application, the initial values of cluster centers need to be rationally chosen based on the knowledge of mineral spectroscopy. This method is applied in the clustering analysis of the rock near-infrared spectra, which were also quantified in terms of reflectivity in the near-infrared band. These actual rock near-infrared spectra were measured by a spectrometer, while the classification results were compared with X-ray diffraction analysis to show the effectiveness of our algorithm. Our study has shown that, with the optimized fuzzy C-means clustering algorithm, the interpretation of rock near-infrared spectra can help us obtain information of the mineral composition and structure more effectively in terms of accuracy and speed. This method is suitable for the rapid processing of massive rock near-infrared spectra and may become an important technology in geological survey and geological prospecting.     

A subspace time-domain algorithm for automated NMR spectral normalization

Recently, two methods have been proposed for quantitatively comparing NMR spectra of control and treated samples, in order to examine the possible occurring variations in cell metabolism and/or structure in response to numerous physical, chemical, and biological agents. These methods are the maximum superposition normalization algorithm (MaSNAl) and the minimum rank normalization algorithm (MiRaNAl). In this paper a new subspace-based time-domain normalization algorithm, denoted by SuTdNAl (subspace time-domain normalization algorithm), is presented. By the determination of the intersection of the column spaces of two Hankel matrices, the common signal poles and further on the components having proportionally varying amplitudes are detected. The method has the advantage that it is computationally less intensive than the MaSNAl and the MiRaNAl. Furthermore, no approximate estimate of the normalization factor is required. The algorithm was tested by Monte Carlo simulations on a set of simulation signals. It was shown that the SuTdNAl has a statistical performance similar to that of the MiRaNAl, which itself is an improvement over the MaSNAl. Furthermore, two samples of known contents are compared with the MiRaNAl, the SuTdNAl, and an older method using a standard. Finally, the SuTdNAl is tested on a realistic simulation example derived from an in vitro measurement on cells.     

On-line detection of fatigue cracks using an automatic mode tracking technique

Experimental fatigue tests usually require large testing times. In addition to the resulting increased time-to-market, the large fatigue test time also implies that any structural health monitoring technique that is used should be automatic. When using the modal parameters as damage indicators, an important amount of user interaction is still needed to separate physical poles from computational ones. In this paper, an experimental framework will be developed to automatically track the health of the structure on-line with the performance of fatigue tests. The modal parameters are tracked using a combination of the maximum likelihood estimator and an auto-regressive model. Since confidence levels on the modal parameter are available it is possible to detect if damage is present. In addition, the quasi-static stiffness with computed confidence levels is also used as a damage indicator. The proposed techniques are demonstrated on a steel beam with a propagating fatigue crack.     

一种新的恒星光谱间距离度量方法：残差分布距离

距离度量是光谱巡天数据处理中的一个重要研究内容,其定义了一种不同光谱间的距离计算方法,以此为基础可进行光谱的分类、聚类、参数测量及离群数据挖掘等工作。距离度量方法的好坏在一定程度上影响了分类、聚类、参数测量及离群数据挖掘的效果及性能,同时随着大规模恒星光谱巡天项目的开展,如何针对恒星光谱定义更为有效的距离度量方法成为其数据处理中一个非常关键的问题。基于此问题,在充分考虑到恒星光谱的特点及其数据特征的基础上,提出一种新的恒星光谱间的距离度量方法：残差分布距离。该距离度量有别于传统计算恒星光谱间距离计算方法,利用该方法计算恒星光谱间的距离时,首先将两条光谱归一化到同一尺度下,然后计算对应波长处的残差,以残差谱分布的标准差作为距离度量。该距离度量方法可用于恒星分类、聚类以及恒星大气物理参数测量等应用中。本文以恒星光谱细分类为例来比较检验该距离度量方法,结果表明该方法定义的距离在分类时能更为有效的刻画不同类别光谱间的差距,可以很好的用于相关应用中。同时还研究了信噪比对该距离度量方法的影响：残差分布距离一定程度上受光谱信噪比影响,信噪比越小,对距离的影响越大;在信噪比大于10之后,残差分布距离对分类的影响很小。     

Clustering gene expression data analysis using an improved EM algorithm based on multivariate elliptical contoured mixture models

Clustering gene expression data is an important research topic in bioinformatics because knowing which genes act similarly can lead to the discovery of important biological information. Many clustering algorithms have been used in the field of gene clustering. The multivariate Gaussian mixture distribution function was frequently used as the component of the finite mixture model for clustering, however the clustering cannot be restricted to the normal distribution in the real dataset. In order to make the cluster algorithm strong adaptability, this paper proposes a new scheme for clustering gene expression data based on the multivariate elliptical contoured mixture models (MECMMs). To solve the problem of over-reliance on the initialization, we propose an improved expectation maximization (EM) algorithm by adding and deleting initial value for the classical EM algorithm, and the number of clusters can be treated as a known parameter and inferred with the QAIC criterion. The improved EM algorithm based on the MECMMs is tested and compared with some other clustering algorithms, the performance of our clustering algorithm has been extensively compared over several simulated and real gene expression datasets. Our results indicated that improved EM clustering algorithm is superior to the classical EM algorithm and the support vector machines (SVMs) algorithm, and can be widely used for gene clustering.     

Reverse Monte Carlo iterative algorithm for quantification of X-ray fluorescence analysis based on MCNP6 simulation code

Reverse Monte Carlo iterative algorithm has been developed for quantification of energy-dispersive X-ray fluorescence analysis in order to calculate the concentrations of the elementary composition in solid substances. The core of the simulation code was the MCNP6 that is a well-established and widely applied software package in the nuclear research and practice for simulation of nuclear systems or the full process of gamma- or X-ray spectrometry. The reverse Monte Carlo algorithm and the full analytical procedure was tested by quantitative XRF analysis of reference alloy samples. The atomic compositions of the reference samples were determined by reverse Monte Carlo technique and also fundamental parameter method and by spark emission atomic spectroscopy. The agreement between the results of these three analytical methods was found within the standard deviations of the major elements of the samples. The total duration of the reverse Monte Carlo numerical computation was minimized to a few minutes using the variance reduction procedures available in the MCNP6.     

Prototype models for particle structure in gauge supersymmetry

Particle content in prototype models of gauge supersymmetry is examined. The properties of the prototype models which are in common with those of gauge supersymmetries are the initial non-diagonality of the quadratic part of the action, global supersymmetry invariance and the existence of a mass parameter in the quadratic part of the action. The analysis exhibits the particle content of prototype models to consist of normal poles and sets of complex conjugate poles on the physical sheet. Diagonalization of the hamiltonian can be carried out for such systems (in contrast to the prototype model of conformal supergravity where dipole ghosts arose). Essentially the pole structure observed in the prototype models of gauge supersymmetry is the supersymmetric analogue of the Lee-Wick phenomenon where the normal and the complex conjugate poles form global multiplets.     

基于变分模态分解与多尺度排列熵的生物组织变性识别

根据高强度聚焦超声(HIFU)治疗中超声散射回波信号的特点,本文利用变分模态分解(VMD)与多尺度排列熵(MPE)对生物组织变性识别进行了研究.首先对生物组织中的超声散射回波信号进行变分模态分解,根据各阶模态的功率谱信息熵值分离出噪声分量和有用分量;对分离出的有用信号进行重构并提取其多尺度排列熵;然后通过Gustafson-Kessel (GK)模糊聚类确定聚类中心,采用欧氏贴近度与择近原则对生物组织进行变性识别.将所提方法应用于HIFU治疗中超声散射回波信号实验数据,用遗传算法对多尺度排列熵的参数优化后,对293例未变性组织和变性组织的超声散射回波信号数据进行了多尺度排列熵分析,发现变性组织的超声散射回波信号的多尺度排列熵值要高于未变性组织;多尺度排列熵可以较好地识别生物组织是否变性.相对于EMD-MPE-GK模糊聚类以及VMD-小波熵(WE)-GK模糊聚类变性识别方法,本文所提方法中变性与未变性组织特征交叠区域数据点更少,聚类效果和分类性能更好;本实验环境下生物组织变性识别结果表明,该方法的识别率更高,高达93.81%.     

X射线探测器图像的恢复研究

图像退化是引起X射线探测器图像质量下降的主要原因。图像恢复,可以提高系统的分辨率和对比度灵敏度。通过对射线成像系统图像退化的分析,介绍了反滤波信号恢复方法,并提出了一种近似恢复算法,该算法将反滤波恢复近似为除法运算的恢复。给出了恢复前后的图像及标准差的对比,实验结果表明了该算法的有效性。     

X光图像中缺陷的自动提取方法研究

针对炭素制品X光图像的特点,对其缺陷的提取技术进行了研究,提出了基于迭代的阈值构造方法和基于数学形态学的边缘提取算法。为快速准确地提取缺陷,设计了目标边界提取算法和基于小波变换的图像增强算法,实现了原始图像中目标区域的增强及其背景的去除。在此基础上,为排除噪声干扰的影响,采用数学形态学和迭代阈值分割相结合的方法从目标区域中提取出缺陷区域,并在迭代阈值分割的基础上,利用基于数学形态学的边缘提取算法提取了缺陷的边缘。实验结果表明,该法很好地实现了缺陷区域及其边缘的自动提取,且受噪声影响很小,为进一步的缺陷特征参量的提取与选择奠定了良好的基础。     

光谱辐射照度标准灯的数据插值与曲线拟合方法研究

介绍了多种插值方法与曲线拟合方法,对光谱辐射照度标准灯在所需波长间隔上的照度值进行内插运算,包括这些方法的模型建立、参数计算及误差分析过程。得到了效果较好的插值方法及分段普朗克曲线拟合模型,其中拟合模型较好地体现了光谱辐射照度标准灯的灯丝发射率及灯壳的光谱透射比。最终结果的相对偏差接近国家级计量院提供标准灯的最佳不确定度0.2%。     

Non-decoupling,triviality and theϱ parameter

The dependence of the ? parameter on the mass of the Higgs scalar and the top quark is computed non-perturbatively using the 1/N _F expansion in the standard model. We find an explicit expression for the ? parameter thatrequires the presence of a physical cutoff. This should come as no surprise since the theory is presumably trivial. By taking this cutoff into account, we find that the ? parameter can take values only within a limited range and has finite ambiguities that are suppressed by inverse powers of the cutoff scale, the so called “scaling-violations”. We find that large deviations from the perturbative results are possible, but only when the cutoff effects are also large.