基于二次EEMD的转子故障信号时频分析方法研究

HHT时频分析被广泛应用于机械故障诊断中,但其模态混叠成为应用时的瓶颈。针对此问题提出了利用二次集合经验模态分解分解(ensemble empirical mode decomposition,EEMD)来消除模态混叠的时频分析方法。该方法首先用EEMD将原信号分解成若干个本征模函数(intrinsic mode function,IMF),然后选取相关系数较大的分量重构原信号,再利用EEMD对其进行二次处理,便可获得去除模态混叠的时频分布。通过对仿真与实验转子信号分析,该方法可以有效抑制经验模式分解(empirical mode decomposition,EMD)的模态混叠现象,相比一次EEMD,二次EEMD去除模态混叠更明显,能有效应用于旋转机械故障诊断中。     

基于最大相关波形延拓改进的EEMD方法

针对经验模态分解(empirical mode decomposition,EMD)中出现的端点效应和模态混叠现象问题,提出了利用最大相关波形延拓改进聚合经验模态分解(ensemble empirical mode decomposition,EEMD)方法.利用最大相关波形法对原始信号的两端进行延拓,实现延拓数据在原信号边界处的平滑过渡,减小端点处包络线的拟合误差.针对EEMD中参数无法自动获取的问题,采用自适应EEMD对新信号进行分解,提高信号的分解精度.通过仿真分析和转子不平衡故障诊断实例研究表明,改进的EEMD方法不仅能够明显减少虚假模态分量、有效抑制模态混叠现象,而且较好地改善了端点效应引起的分解失真问题.同时与基于极值点对称延拓改进方法及基于镜像延拓改进方法相比,所提方法具有较高的分解精度.     

基于EEMD和伪信号技术的涡街信号处理方法

针对深海水平流涡街信号的微弱性、低频性,易被噪声淹没难以提取的特点,文章提出一种基于整体经验模态分解(ensemble empirical mode decomposition,EEMD)和伪信号技术的消噪方法。通过分析经过EEMD分解及希尔伯特变换(Hilbert transform,HT)后信号的时频特性,确定组成信号的主要两阶固有模态参数(intrinsic mode functions,IMF),结合双伪信号技术进一步处理后识别信号频率。模拟实验与仿真结果对比表明,该方法能有效提高信号的抗干扰能力,精确估计涡街信号频率。     

EEMD滤波的转子轴心轨迹提纯方法

针对轴心轨迹提纯问题,研究了集合经验模式分解(Ensemble empirical mode decomposition ,EEMD)抑制模态混叠的特性及其滤波特性,提出了基于EEMD滤波的转子轴心轨迹提纯方法。应用EEMD将信号分解成一系列的固有模式函数(Intrinsic mode function,IMF)分量,再根据先验知识选择相应的IMF分量重构信号,组合成提纯轴心轨迹。对小型转子试验台转子轴心轨迹的成功提纯验证了该方法的有效性,与谐波窗和EMD轴心轨迹提纯方法的对比结果表明了该方法的优势,为转子系统故障诊断提供了一种新的手段。     

基于EMD改进算法的欠定混合盲分离

为改善拟合效果,针对经验模态分解(empirical mode decomposition,EMD)算法存在的端点效应,提出一种改进的EMD算法——端点极值延拓方法.利用改进的EMD算法对观测信号进行分解,将分解分量连同之前的观测信号构成新的观测信号,从而将欠定情况转化为超定情况,最后利用独立成分分析(independent component analysis,ICA)算法得到源信号的估计.通过仿真实验对比,证明了本文算法的有效性.     

信息熵与经验模态分解集成的转子故障信号量化特征提取

针对转子振动信号的非线性、非平稳性造成的故障状态难以定量准确描述问题,提出一种基于信息熵和经验模态分解(empirical mode decomposition,EMD)的转子振动信号量化特征提取方法.该方法通过对比转子故障信号EMD分解后各内禀模态分量(intrinsic mode function,IMF)的能量状态及其与原始信号间的相关性程度,在确定出包含主要故障信息的分量基础上,分别对其进行时域、频域及时频域内4种信息熵熵值的计算,从而建立起一种信息熵熵带特征量.实验信号的分析结果表明,该方法能够较好地实现对转子系统故障信号的量化特征提取,所提取出的特征集合具有能够使典型故障特征量之间存在显著差异的性能.     

IFD与KELM结合的滚动轴承故障诊断方法

针对滚动轴承振动信号非线性、非平稳的特点,提出基于迭代滤波分解(iterative filtering decomposition, IFD)提取各分量特征,结合核极限学习机(kernel extreme learning machine, KELM)的故障诊断方法.通过对原始信号进行IFD分解,得到一组本征模态函数(intrinsic mode functions, IMF).计算包含主要故障信息在内的IMF分量能量与排列熵组成的故障特征向量,将特征向量作为KELM输入识别轴承的故障类型.实验分析结果表明,以IFD作为预处理器的特征融合方法比经验模态分解(empirical mode decomposition, EMD)为预处理器的特征融合方法有更高的故障识别率,并且该方法在少量样本情况下仍能有效识别故障类型.     

基于EEMD-HHT边际谱的轴承故障诊断

提出一种基于聚合经验模态分解 (ensemble empirical mode decomposition,EEMD)和Hilbert-Huang变换（HHT）边际谱的滚动轴承故障诊断方法。首先采用EEMD方法将轴承振动信号分解成若干个模态混叠得到较好抑制的固有模态函数（IMFs）,然后对各IMF进行Hilbert变换,求出轴承振动信号的总HHT边际谱,最后根据该边际谱的幅值特性,确定滚动轴承的故障特征。本文方法提供了一种滚动轴承故障诊断的有效工具。     

基于EEMD和FastICA的单通道背景声舱音盲源分离

针对单通道信号盲源分离(blind source separation, BSS)模型的极端欠定问题,提出利用总体经验模态分解(ensemble empirical mode decomposition,EEMD)将单通道混合信号分解成多个瞬时频率本征模态函数(intrinsic mode function,IMF)分量的形式,构建新的观测矩阵,再通过快速独立分量分析(fast independent component analysis,FastICA)实现信号的盲源分离。仿真实验和实验室研究表明:该方法能够抑制宽频和瞬态干扰,有效地将淹没于噪声中的目标信号提取出来。实测数据分析表明该方法可以在飞机发动机噪声干扰下有效地提取背景声舱音信号,证明该方法在舱音信号处理中的有效性。     

EMD去噪法在FMCW雷达信号处理中的应用

针对调频连续波(frequency modulated continuous wave,FMCW)雷达信号在传播过程中会受到各种噪声影响的情况,提出了一种新型的基于自相关函数能量特性的经验模态分解(empirical mode decomposition,EMD)降噪算法。该算法首先对差频信号进行EMD分解,得到包含原信号不同尺度信息的本征模态函数(intrinsic mode function,IMF)分量;其次对每一IMF分量进行无偏自相关运算,并计算其能量;第三,根据IMF分量的自相关函数能量变化曲线,确定出有用信号贡献率最大的IMF分量;最后进行EMD重构。实验结果表明:该方法在各种信噪比条件下,能够准确判断出有用信号主导的IMF分量,对差频信号具有良好的去噪效果,同时该方法具有自适应性,不受主观因素的影响,适合应用在FMCW雷达系统中。     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

海南岛地体及其毗邻陆缘晚中生代—新生代古地磁研究和构造演化

本文叙述了对海南岛及其毗邻大陆边缘白垩纪到第四纪地层岩石进行古地磁研究的全部工作过程。通过分析岩石中剩余磁矢量的磁偏角及磁倾角的变化,提出海南岛白垩纪以来经历的构造演化模式如下:早期伴随顺时针旋转而向南迁移,后期伴随逆时针转动并向北运移。联系该地区及邻区的地质、地球物理资料,对海南岛上述的构造地体运动提出以下认识:北部湾内早期有一拉张作用,主要是该作用使湾内地壳显著伸长减薄,形成北部湾盆地。从而导致了海南岛的早期构造运动,而海南岛后期的构造运动则主要是受南海海底扩张的影响。海南地体运动规律的阐明对于了解北部湾油气盆地的形成演化有重要的理论和实际意义。     

Exciton Seebeck in Molecular Systems

Various applications relevant to the exciton dynamics,such as the organic solar cell,the large-area organic light-emitting diodes and the thermoelectricity,are operating under temperature gradient.The potential abnormal behavior of the exicton dynamics driven by the temperature difference may affect the efficiency and performance of the corresponding devices.In the above situations,the exciton dynamics under temperature difference is mixed with     

Achieving Unusual States of Matter Under High Pressure

The elongation method,originally proposed by Imamura was further developed for many years in our group.As a method towards O(N)with high efficiency and high accuracy for any dimensional systems.This treatment designed for one-dimensional(ID)polymers is now available for three-dimensional(3D)systems,but geometry optimization is now possible only for 1D-systems.As an approach toward post-Hartree-Fock,it was also extended to     

《Chinese Science Bulletin》SUBJECT INDEX TO VOLUME 59(2014)

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An on-line scaling method for improving scalability of a database cluster

The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.     

An improved R-tree based on childnode''s probability

R-Tree is a good structure for spatial searching. But in this indexing structure,either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display the geometric objects users concern about swiftly onto the display window. This process includes two operations:retrieve data from database and then draw them onto screen. Accordingly, to improve the efficiency, we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree, the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper introduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets: One is that every node and geometric object in the generalization is assigned with a importance value which denote the importance of them, and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks, and vertexes are total ordered by their importance value. With the help of the generalized R-tree, one can easily retrieve data at different detail levels.Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

Integrating GIS Web services based on mediating architecture

The geographic information service is enabled by the advancements in general Web service technology and the focused efforts of the OGC in defining XML-based Web GIS service. Based on these models, this paper addresses the issue of services chaining,the process of combining or pipelining results from several interoperable GIS Web Services to create a customized solution. This paper presents a mediated chaining architecture in which a specific service takes responsibility for performing the process that describes a service chain. We designed the Spatial Information Process Language (SIPL) for dynamic modeling and describing the service chain, also a prototype of the Spatial Information Process Execution Engine (SIPEE) is implemented for executing processes written in SIPL. Discussion of measures to improve the functionality and performance of such system will be included.