基于EMD样本熵-LLTSA的故障特征提取方法

针对振动信号的非线性、非平稳性以及微弱故障特征难以提取的问题,提出了一种基于经验模态分解(EMD)、样本熵和流形学习的故障特征提取方法.该方法将EMD、样本熵和流形学习相结合.首先,利用EMD的自适应多分辨率的特点计算分解得到的IMF(固有模态函数)信号的样本熵,初步提取滚动轴承状态特征值;然后利用流形学习方法对初步的提取的滚动轴承状态特征进行进一步的提取;最后利用支持向量机(SVM)对该特征提取方法进行分类评估,并将该方法运用在滚动轴承故障诊断实验中,实验证明该特征提取方法与基于小波包样本熵的故障诊断方法相比具有很好的聚类性能,且对于SVM的分类结果可达100%,在降低了特征数据的复杂度的同时,增强了故障模式识别的分类性能,具有一定的优越性.     

基于排列组合熵的转子振动信号故障诊断SVM方法研究

针对发动机转子的多种故障模式,提出了基于排列组合熵的SVM故障诊断方法。利用转子实验台,模拟了转子正常、转子不平衡、转子不对中、动静碰磨和基座松动5种典型振动模式,并使用振动传感器采集多路振动数据。计算振动数据的排列组合熵并将其作为故障特征向量,对特征向量样本集进行多级SVM分类诊断,并运用小波包能量特征提取方法提取信号特征。实例计算与结果对比表明,本文方法的正确率要高于基于小波包能量提取特征的SVM分类诊断方法,在提取转子振动信号的特征向量及在小样本下的故障分类诊断等方面,具有可行性和有效性。     

用小波和神经网络相结合的方法识别人体表面肌电信号

以MALTAB语言作为系统设计工具，将小波分析与神经网络相结合分析人体表面肌电信号。对SEMG信号的识别分为3个步骤：数据预处理，特征的提取，设计分类器分类。首先利用小波分析进行消噪，提取特征；然后采用BP神经网路进行分类、识别；最后通过对分类结果的分析与比较，证明小波与神经网络相结合是一种有效的表面肌电信号的模式识别方法。     

Bayesian分类方法在微小型飞行器视觉导航中的应用

在微小型飞行器的视觉导航中,图像分割的基本工作是将天地两部分分割开.这是形成整个视觉导航系统闭环控制的基础.而欲实现天地分割,则以特征线的提取为前提.本文分别从自底向上和自顶向下两种思路出发,利用广义Hough变换和基于多尺度最小方差的方法,进行了全局特征线的提取.然后,采用Bayesian分类的方法,实现了对微小型飞行器视觉导航至关重要的天地分割.通过具有典型意义的仿真实验,比较了两种方法所获得的结果,揭示了两种方法应用于微小型飞行器视觉导航的优点和缺点.     

基于粗糙核Fisher鉴别分析的特征提取及其在发动机故障诊断中的应用

将粗糙集理论的属性约简与核Fisher鉴别分析方法结合起来,提出一种基于粗糙核Fisher鉴别分析的故障特征提取方法.首先采用粗糙集理论的属性约简删除与分类无关或关系不大的特征,降低输入特征维数,排除干扰特征的影响,减小了特征提取计算量;再采用核Fisher鉴别分析方法进一步提取非线性特征;最后将该方法应用于航空发动机滑油系统故障特征提取及故障识别中.结果表明:该方法获取的特征在提高分类正确率的同时,还有效地降低了输入特征维数,提高了分类效率,并且对分类器具有较强的适应性和鲁棒性.      

基于分形的BP网络水下目标识别

主要讨论目标回波的分形特征和基于分形的识别方法,并用实际潜艇的回波数据进行了分形特征识别研究。在分析回波信号的时间域波形的基础上,应用随机分形理论,给出基于分形 Brown 运动的回波信号分形特征矢量提取的理论和方法;提取了回波信号的分形特征矢量;进而给出了基于 BP 网络的分类计算方法。计算结果表明,提出的提取水声回波信号目标特征矢量的方法与分类方法切实可行。     

一种基于红外图像的目标自动识别算法

红外成像制导具有在各种复杂战术环境下自主搜索、捕获、识别和跟踪目标的能力,代表了当代红外制导技术的发展趋势。提出了一种红外图像预处理、跟踪、分类的自动目标识别算法,利用小波变换、形态学方法对红外图像进行预处理,提取不同频带的惯性不变矩作为特征量,利用神经网络进行分类识别,结果表明该算法具有很高的识别率,对于精确制导武器的目标识别研究具有一定的参考价值。     

基于特征增维和近邻成分分析的民航发动机故障分类方法

为提高航空发动机故障诊断准确度,提出了一种从快速存取记录器（QAR）数据中提取最合适故障特征的方法。对原始 QAR数据进行缺失值填补和巡航点提取操作,选择部分发动机性能参数差值作为初始特征值;再采用特征增维方法挖掘隐藏特征 信息,进而采用近邻成分分析算法进行特征筛选优化,将所提方法与朴素贝叶斯等4种分类算法相结合,对某航空公司CFM56-7B 发动机的QAR数据进行试验验证。结果表明：从QAR数据中提取最合适故障特征的方法能有效地提高发动机故障分类算法的准 确率,且适用于不同的诊断算法,准确率优于80%。     

基于量子粒子群和流形学习的分类方法及其在发动机故障诊断中的应用

针对测量参数存在的非线性、参数间的耦合性以及噪声干扰,将量子粒子群算法引入到流形学习的参数选择中,结合径向基神经网络,提出了一种故障诊断方法。邻域个数和约简维数是流形学习中的关键问题。结果表明:该方法首先利用量子粒子群算法优选邻域个数、约简维数和径向基函数的参数,再利用等距特征映射(ISOMAP)对原始参数进行非线性降维,提取其低维流形特征,从而进行故障分类。结果表明:该方法能够有效地对发动机各种复合故障进行分类,精度达到97.33%,量子粒子群优于基本粒子群优化的分类结果;其分类精度明显优于主元分析(PCA)、核主元分析(KPCA)方法,且有很强的抗噪能力。     

基于小波变换和不变矩的车标识别方法

形状特征是目标识别的重要参数,小波变换的低频部分代表物体的总体形状特征,而图像中的噪声主要分布于高频部分。根据这一特征,利用小波变换消除噪声提取目标形状,进而利用特征不变矩距离进行分类,实现目标识别,将该方法应用在实测车标图像的识别中,结果表明识别效果较好。     

The effect of inlet conditions on the flow and heat transfer in multiple rotating cavity with axial throughflow

This paper discusses experimental results from two different build configurations of a heated multiple rotating cavity test rig.Measurements of heat transfer from the discs and tangential velocities are presented.The test rig is a 70% full scale version of a high pressure compressor stack of an axial gas turbine engine.Of particular interest are the internal cylindrical cavities formed by adjacent discs and the interaction of these with a central axial throughflow of cooling air.Tests were carried out for a range of non-dimensional parameters representative of high pressure compressor internal air system flows(Re up to 5×106 and Rez up to 2×105).Two different builds have been tested.The most significant difference between these two build configurations is the size of the annular gap between the(non-rotating) drive shaft and the bores of the discs.The heat transfer data were obtained from thermocouple measurements of surface temperature and a conduction solution method.The velocity measurements were made using a two component,LDA system.The heat transfer results from the discs show differences between the two builds.This is attributed to the wider annular gap allowing more of the throughflow to penetrate into the cavity.There are also significant differences between the radial distributions of tangential velocity in the two builds of the test rig.For the narrow annular gap,there is an increase of non-dimensional tangential velocity V/Ωr with radial location to solid body rotation V/Ωr=1.For the wider annular gap,the non-dimensional velocities show a decrease with radial location to solid body rotation.      

Research on Auto-detection for Remainder Particles of Aerospace Relay Based on Wavelet Analysis

Aerospace relay is one kind of electronic components which is used widely in national defense system and aerospace system. The existence of remainder particles induces the reliability declining, which has become a severe problem in the development of aerospace relay. Traditional particle impact noise detection (PIND) method for remainder detection is ineffective for small particles, due to its low precision and involvement of subjective factors. An auto-detection method for PIND output signals is proposed in this paper, which is based on direct wavelet de-noising (DWD), cross-correlation analysis (CCA) and homo-filtering (HF), the method enhances the affectiv-ity of PIND test about the small particles. In the end, some practical PIND output signals are analysed, and the validity of this new method is proved.     

Preparation of Highly Dispersed Antimony-doped Tin Oxide Nano-powder via Ion-exchange Hydrolysis of SnCl4 and SbCl3 and Azeotropic Drying

Antimony-doped tin hydroxide colloid precipitates have been synthesized by hydrolysis of SnCl4 and SbCl3 using: (1) an ion-exchange hydrolysis to remove chlorine ions, and (2) isoamyl acetate as an azeotropic solvent to obviate water. The obtained dried powder is of high dispersivity without any need for further grinding. The size and dispersivity of the final particles are investigated with the aid of TG-DTA, BET, XRD and TEM. After having calcined, the antimony-doped tin oxide nanopowder possesses a tetragonal rutile structure with high dispersivity, uniform particles and low hard agglomeration.     

Effects of Mo on the Microstructure and Hydrogen Sorption Properties of Ti-Mo Getters

The effects of Mo on the microstructure evolution, porosity and hydrogen sorption properties of Ti-Mo getters are investigated in this work. The results show that the addition of Mo prolongs the densification process of Ti-Mo getters and results in a significant amount of sintered pores. With the Mo content increasing, the porosity of getters firstly increases reaching the maximum value as it at- tains about 7.5wt.%, and then drops. At the room temperature, the hydrogen sorption property of getters increases progressively with the Mo content increasing, but the tendency is not very clear before its content lies below 2.5wt.%. When the Mo content achieves about 7.5wt.%, the hydrogen sorption property proves to be the best. The discussion is made about the above mentioned phenomena inclusive of hydrogen sorption properties of getters under different activation conditions (from 500-750 ℃).     

超声速燃烧数值模拟中的湍流与化学反应相互作用模型

高精度数值模拟有助于理解超声速湍流燃烧中湍流与化学反应的相互作用,可为发动机燃烧室等工程应用设计提供可靠的预测模型。除直接数值模拟外,目前在湍流燃烧应用中使用的大涡模拟和雷诺平均Navier-Stokes模拟均需要借助模型模化发生在湍流小尺度上的流动与化学反应过程对湍流大尺度运动的影响。现有的湍流与化学反应相互作用模型大致可分为:火焰面类模型和概率密度函数类模型,2类模型在不同的应用中各自具有优势和局限性。此外,现有模型大都基于低马赫数燃烧,而超声速燃烧中通常会伴随快速混合、局部熄火和再着火以及激波等复杂过程,这为发展其中的湍流与化学反应相互作用模型提出了更多的挑战。     

适于低轨卫星IP网络的单核共享树组播算法(英文)

为了解决低轨卫星IP网络中现有典型源组播算法的信道资源浪费问题,本文提出了一套单核共享树组播算法,即核心群合并共享树(CCST)和加权核心群合并共享树(w-CCST)算法。CCST 算法包括动态近似中心(DAC)选核方法和核心群合并组播路径构建方法。DAC方法专为周期、规律运动的低轨卫星网络提出,不需要复杂的星上计算。在核心群合并方法中,以核节点作为初始核心群,通过核心群和剩余组成员的最短路径方法逐步扩展直至整棵组播树构建完成,从而使得组播树的树代价最小,大大提高了网络的带宽利用率和组播传输效率。w-CCST 算法中所提出的加权因子可以调整树代价和端到端传播时延之间的折衷程度,因此,可以通过调整加权因子来适度增大树代价、降低端到端传播时延以支持某些端到端时延要求苛刻的实时组播业务。最后,与低轨卫星 IP 网络中典型算法进行了性能比较,仿真结果说明,CCST 算法的平均树代价比其它算法显著降低,w-CCST 算法的平均端到端传播时延小于 CCST 算法。     

Jet Vectoring Control Using a Novel Synthetic Jet Actuator

A primary air jet vectoring control system with a novel synthetic jet actuator (SJA) is presented and simulated numerically. The results show that, in comparison with an existing traditional synthetic jet actuator, which is able to perform the duty of either “push” or “pull”, one novel synthetic jet actuator can fulfill both “push” and “pull” functions to vector the primary jet by shifting a slide block inside it. Therefore, because the new actuator possesses greater efficiency, it has potentiality to replace the existing one in various appli- cations, such as thrust vectoring and the reduction of thermal signature. Moreover, as the novel actuator can fulfill those functions that the existing one can not, it may well be expected to popularize it into more flow control systems.     

Nonlinear Adaptive Slewing Motion Control of Spacecraft Truss Driven by Synchronous V-gimbaled CMG Precession

The slewing motion control of a truss arm driven by a V-gimbaled control-moment-gyro (CMG) is a nonlinear control problem. The V-gimbaled CMG consists of a pair of gyros that must precess synchronously. The moment of inertia of the system, the angular momentum of the gyros and the external disturbances are not exactly known. With the help of feedback linearization and recursive Lyapunov design method, an adaptive nonlinear controller is designed to deal with the unknown items. Performance of the proposed controller is verified by simulation.     

An SOR Implicit Time-accurate Scheme in Calculating Unsteady Flows

A new time-accurate marching scheme for unsteady flow calculations is proposed in the present work. This method is the combination of classical Successive Over-Relaxation (SOR) iteration method and Jacobian matrix diagonally dominant splitting method of LUSGS. One advantage of this algorithm is the second-order accuracy because of no factorization error. Another advantage is the low computational cost because the Jacobian matrices and fluxes are only calculated once in each physical time step. And, the SOR algorithm has better convergence property than Gauss-Seidel. To investigate its accuracy and convergency, several unsteady flow computa- tional tests are carried out by using the proposed SOR algorithm. Roe’s FDS scheme is used to discritize the inviscid flux terms. Un- steady computational results of SOR are compared with the experiment results and those of Gauss-Seidel. Results reveal that the numerical results agree well with the experimental data and the second-order accuracy can be obtained as the Gauss-Seidel for unsteady flow computations. The impact of SOR factor is investigated for unsteady computations by using different SOR factors in this algorithm to simulate each computational test. Different numbers of inner iterations are needed to converge to the same criterion for different SOR factors and optimal choice of SOR factor can improve the computational efficiency greatly.