形态分量分析在转子早期碰摩故障诊断中的应用

提出了一种基于形态分量分析的转子早期碰摩故障诊断方法,该方法用形态分量分析从转子早期碰摩故障信号中提取出冲击成分。形态分量分析根据信号中各组成成分的形态差异,构建不同的稀疏表示字典对各组成成分进行分离。当转子系统中出现早期碰摩时,其振动信号往往由以转频及其谐波为主要成分的周期成分、包含转子早期碰摩故障信息的冲击成分及随机噪声构成。周期成分表现为信号中的平滑部分,而冲击成分则表现为信号中的细节部分,因此,可根据周期成分与冲击成分的形态差异,用形态分量分析实现二者的分离。对形态分量分析的阈值方法进行了改进,提出了基于半软阈值的形态分量分析,仿真结果表明,基于半软阈值的形态分量分析要优于基于硬阈值的形态分量分析。对某转子早期碰摩故障信号进行了分析,结果表明,基于半软阈值的形态分量分析能有效地提取转子早期碰摩故障信号中的冲击成分,进而诊断转子早期碰摩故障。     

基于混沌弱信号检测的轧机故障诊断研究

为检测强噪声背景下轧机的转子和齿轮故障,给出了一种Duffing方程检测微弱信号的算法.设计加入待检信号后的混沌振子方程,检测出转子发生早期碰摩以及齿轮偏心和单齿缺陷故障.故障诊断实验可以证明利用Duffing振子的间歇混沌现象对强噪声背景中轧机故障的微弱特征信号进行检测的有效性,与相关函数法比较,证明此方法的优越性.     

可调品质因子小波变换在转子早期碰摩故障诊断中应用

针对高速旋转机械转子发生早期动静碰摩故障时主要为转子工频成份及转子与支撑间碰摩所致瞬态冲击信号成份,据可调品质因子小波变换对信号品质因子定义为转子工频成份为高品质因子信号、转子动静碰摩所致瞬态冲击信号为低品质因子信号,分别构建高、低品质因子小波变换基函数实现转子早期动静碰摩信号工频成份与瞬态冲击成份有效分离,对碰摩故障进行模式识别。通过仿真信号及转子碰摩实验信号验证可调品质因子小波变换在转子早期碰摩故障诊断中的有效性。     

基于MCSSD的转子碰摩故障早期检测

提出了基于多尺度线调频基信号稀疏分解(Multi-scale Chirplet Sparse Signal Decomposition,简称MCSSD)的转子碰摩故障早期检测方法,该方法用MCSSD方法对转子碰摩故障振动信号进行单次分解,从原信号中分离出具有最大幅值的工频(或倍频)信号分量。由于MCSSD方法是采用线性直线逐段自适应逼近分析信号的各分量频率,分解得到的信号分量与真实信号分量具有很好的频率匹配特性,不会产生频率混叠现象,因此,与小波分解与EMD分解相比,MCSSD能更有效地从转子早期碰摩故障振动信号分离出最具最大幅值的工频(或倍频)信号分量。将该信号分量从原信号中去除,对残余信号分量做频谱分析,即可有效诊断转子早期碰摩故障。应用实例证明了该方法的有效性和优越性。     

转子复合碰摩故障特征提取实验研究

对旋转机械中的一些典型碰摩故障及复合碰摩故障进行了试验模拟,对故障发生过程中的加速度信号进行了采集.在此基础上,对转子故障加速度信号的三维谱特性进行了分析,提取和总结出由故障造成的加速度信号突变和对应的谱特征.分析结果表明采用加速度信号对转子的碰摩故障进行诊断是有效的.加速度信号三维谱图可以丰富旋转机械碰摩故障诊断系统知识库中的特征信息,对于更准确地诊断转子中的碰摩故障具有重要的意义.     

基于信号共振稀疏分解与重分配小波尺度谱的转子碰摩故障诊断方法

提出了基于信号共振稀疏分解与重分配小波尺度谱的转子碰摩故障诊断方法。与常规的基于频带划分的信号分解方法不同,信号共振稀疏分解方法根据信号中各成分品质因子的不同,将信号分解成高共振分量和低共振分量。当转子出现碰摩故障时,振动信号往往由以转频及谐波为主要成分的周期信号、包含转子故障信息的瞬态冲击信号以及噪声组成。周期信号为窄带信号,具有高的品质因子,可分解为高共振分量;而瞬态冲击信号为宽带信号,具有低的品质因子,可分解为低共振分量。本文方法先利用信号共振稀疏分解方法从转子碰摩信号中提取冲击成分,再对提取的冲击成分进行重分配小波尺度谱分析,最后根据尺度图中冲击成分的周期诊断转子碰摩故障。算法仿真和应用实例验证了该方法诊断转子碰摩故障的有效性。     

基于加速度信号全谱分析的转子碰摩故障特征提取实验研究

转子在运行过程中的振动加速度信号包含了转子运行状态大量信号，瞬态过程中故障加速度信号特征的提取及其识别对于旋转机械故障诊断是十分重要的。旋转机械振动的全谱分析是一种使一些典型故障尤萁是碰摩故障能被很清楚检测出来的有效方法，本文在对旋转机械转子中的一些典型碰摩故障进行了模拟试验，以及对故障发生过程中的加速度信号进行采集的基础上，对转子故障加速度信号的全谱特性进行了分析，提取和总结出由故障造成的加速度信号突变和对应的谱特征。分析结果表明：采用转子振动加速度信号对转子的碰摩故障进行诊断是有效的。加速度信号全谱图可以丰富旋转机械碰摩故障诊断系统知识库中的特征信息，对于更准确地诊断转子中的碰摩故障具有重要意义。     

基于定子振动的转子碰摩故障诊断方法研究

转子碰摩会引发转子和定子的振动,但由于转子系统的很多常见故障(如不对中、不平衡等)与碰摩故障的转子振动特征多有重复之处,在很大程度上限制了故障的有效诊断.于是以定子振动信号为诊断源,研究了碰摩故障的诊断技术.首先分析了定子振动的机理,认为碰摩时定子受到冲击力作用,会引发定子固有频率振动,提出可采用共振解调法进行碰摩故障的诊断.利用IFFT方法进行了定子固有振动信号的分离,再进行希尔伯特变换,得到其包络信号,并对其进行谱分析,从而完成分析诊断过程.最后进行了单点碰摩和局部碰摩的故障模拟实验,结果表明定子高频固有振动包络信号可以揭示碰摩故障的发生,结合角度定位信号,可以对转子碰摩故障进行定位.     

基于声信号三维谱分析的转子复合碰摩故障特征提取

转子在运行过程中的声音包含了大量的转子运行状态信号,变速过程中故障声信号特征的提取及其识别对于旋转机械故障诊断是极其必要的,目前基于声信号三维谱分析的转子故障特征提取还不多,在对转子旋转机械中的一些典型产生的碰摩故障及复合碰摩故障进行了试验模拟,对故障发生过程中的声信号进行采集的基础上,对转子故障声信号的三维谱特性进行了分析。提取和总结出由故障造成的声信号突变和对应的声谱特征。分析结果表明:采用声信号对转子的碰摩故障进行诊断是有效的。声信号三维谱图丰富旋转机械碰摩故障诊断系统知识库中的特征信息,可以用于更准确地诊断转子中的碰摩故障。     

转子全周碰摩与局部碰摩的识别方法研究

摘 要：超临界汽轮发电机组的结构和工况复杂,容易引起转、静子间的碰摩。根据碰摩诱发因素的不同,可将其分为全周碰摩与局部碰摩。由于两种碰摩故障的时、频特征相似,传统的时、频域分析方法很难准确提取它们的故障特征。本文针对这一不足,提出一种基于经验模式分解-奇异值分解（EMD-SVD）与支持向量机（SVM）的碰摩故障识别方法,用于对转子全周碰摩与局部碰摩故障进行识别。首先,通过EMD获取碰摩信号的固有模式函数（IMF）;然后,提取表征信号主要能量的前四阶IMF组成特征矩阵并进行SVD分解,得到关于原信号的一组特征值;最后,将特征值输入SVM,对原信号进行分类识别。转子试验台全周碰摩与局部碰摩试验结果表明,本方法对转子全周碰摩与局部碰摩故障的分类准确率高,其中以径向基函数作为核函数的SVM分类准确率达到96.0%。     

基于灰色关联度和Teager能量算子的轴承早期故障诊断

滚动轴承的健康状态直接影响着旋转设备的运行状态,为了及早获取滚动轴承状态异常的信息,提出了基于灰色关联度和Teager能量算子(TEO)的滚动轴承早期故障的诊断方法。对滚动轴承运转的振动数据进行等长度分组,计算各组数据与轴承状态良好的第一组数据之间的灰色关联度,根据灰色关联度值的变化趋势,确定早期故障发生的时间段,截取该时段的振动数据进行Teager能量包络谱分析,确定故障类型。分别采用峭度系数、波形因子和均方根等指标与TEO相结合的方法对相同的轴承振动信号进行了分析和故障诊断,将各种方法的早期故障诊断结果与所提方法比较,结果验证了"灰色关联度+TEO"方法在轴承早期故障诊断中的可行性及有效性。     

Oximetry of retinal capillaries by multicomponent analysis

Retinal oximetry of capillaries was performed for early detection of retinal vascular abnormalities, which are caused predominantly by complications of systemic circulatory diseases. As the conventional method for determining absorbance is not applicable to capillaries, multicomponent analysis was used to estimate the absorbance spectra of the retinal blood vessels. In this analysis, the capillary spectrum was classified as intermediate between those of the retinal arteries and veins, enabling relative estimation of oxygen saturation in the capillaries. This method could be useful for early recognition of disturbances in the peripheral circulation. Furthermore, a spectroscopic ophthalmoscope system based on the proposed method was developed to examine the human retina. A clinical trial of this system demonstrated that oximetry of the retinal capillaries may be an improvement over the present diagnosis for patients of malignant hypertension.     

Method of early failure detection for elastic diaphragms based on frequency analysis of the acoustic signal

A method of in-service early failure detection based on frequency analysis of the acoustic signal obtained from elastic diaphragms in air-driven pumps is described. A fully digital system for frequency analysis based on a personal computer was developed with a view to practical implementation of this method. The validity of the method was demonstrated by experiments performed under realistic in-plant conditions.     

基于RF和ANFIS算法的直驱风电机组故障预警

针对风电机组运行工况复杂和单一状态参数不能较好实现故障早期预警的特点,提出随机森林算法(RF)和自适应模糊神经网络算法(ANFIS)相结合的故障预警方法。该方法充分考虑机组运行数据高维非线性特点,应用随机森林算法,建立有功功率与运行参数的数据驱动模型,计算各运行参数影响有功功率的相关度;构建自适应网络模糊推理系统模型,以训练误差最大值作为故障预警阈值,实时监测发电机运行状态。将该方法应用于某1.5 MW直驱机组发电机故障预警分析,结果表明,该方法能够提前预警发电机健康状态,避免严重事故发生,对风电场开展预防性维护、维修具有重要的指导意义。     

Residual stresses of types II and III and their estimation

Residual stresses (RS) are induced in metallic materials by a variety of working and fabrication processes. They are generally classified into three categories (types I, II and III) depending upon their range of influence. Separation of type I and II stresses often requires stress measurements on thin specimens. Type III stresses are related closely to grain fragmentation and micro-strains associated with plastic deformation. Perhaps the oldest and the most rigorous method of estimating these stresses is still the Warren-Averbach analysis developed during the late forties/early fifties. Other techniques involving integral breadths and variance of the profiles have also been developed. In all these methods developed during the early stages, prior to seventies, a major requirement was well-separated non-overlapping profiles. The late sixties and early seventies saw a dramatic increase in computational capabilities with the advent of powerful electronic computers. This led to the introduction of curve-fitting procedures into the field of X-ray diffraction. The most remarkable achievement of this period is the development of the Rietveld Method. Although this method was initially developed to tackle the neutron diffraction profiles, which are as a rule nearly symmetric and Gaussian in nature, the method saw rapid developments during the eighties. At present, techniques based on concepts developed by Rietveld could be applied to essentially asymmetric and non-Gaussian multiple spectral components of X-ray diffraction profiles. Pattern decomposition techniques which separate composite powder diffraction profiles into individual profiles are now available. In combination with single line profile analysis techniques, this provides a powerful tool in the hands of researchers. A typical example of such a single line profile analysis is given.     

基于二叉树的LS-WSVM早期火灾多类分类研究

针对早期火灾信息特点,提出了一种基于二叉树的最小二乘小波支持向量机（Least squareswavelet support vector machine,LS-WSVM）多类分类方法.该方法首先把主成份分析用于早期火灾信息的特征提取.然后,把二叉树结构和LS-WSVM相结合,提出了基于二叉树的LS-WSVM多类分类模型,不仅避免了盲目分类和不可分情况,而且提高了分类速度和泛化能力.最后,用该模型对特征信息进行处理,从而实现了对早期火灾的多类识别.早期火灾分类实验结果表明,该方法比采用径向基核函数的最小二乘支持向量机多类分类方法具有更好的识别效果和更快的分类速度.     

Automated segmentation of retinal blood vessels and identification of proliferative diabetic retinopathy

Proliferative diabetic retinopathy can lead to blindness. However, early recognition allows appropriate, timely intervention. Fluorescein-labeled retinal blood vessels of 27 digital images were automatically segmented using the Gabor wavelet transform and classified using traditional features such as area, perimeter, and an additional five morphological features based on the derivatives-of-Gaussian wavelet-derived data. Discriminant analysis indicated that traditional features do not detect early proliferative retinopathy. The best single feature for discrimination was the wavelet curvature with an area under the curve (AUC) of 0.76. Linear discriminant analysis with a selection of six features achieved an AUC of 0.90 (0.73-0.97, 95% confidence interval). The wavelet method was able to segment retinal blood vessels and classify the images according to the presence or absence of proliferative retinopathy.     

声信号的主分量分析应用于滚动轴承故障诊断

利用声信号来进行故障诊断具有"采集比较容易,非接触式测取,设备简单,速度快,无须事先粘贴传感器,不影响设备正常工作,易于实现早期预报和在线监测,疳可在不易测量振动信号的场合得到广泛应用"等优点.由于外界噪声的影响,有效信息的提取较为困难.采用主分量分析对传声器测取的声信号进行了预处理;在此基础上应用基于Morlet小波变换的包络分析和频谱分析来提取故障特征向量,并以滚动轴承为例进行实验.结果表明,这是诊断滚动轴承早期故障的一种可选方法.     

EARLY-STAGE EVOLUTION OF PARTICLE SIZE DISTRIBUTION DUE TO GRAVITATIONAL COAGULATION

Evolution of the particle size distribution of an aerosol undergoing gravitational coagulation in early time stages was numerically investigated. The moment method was also applied in initiating a simple approach to the changes of particle size distribution parameters. Finally, an analytical solution was developed approximating the collision kernel into a form suitable for the analysis. The results underwent analysis by comparison. The derived analytical solution was found to be in good agreement with the numerical moment method. However, the results of the moment method do not exactly coincide with the results of the direct numerical integration because the particle size distribution does not attain the log-normal size distribution form.     

基于龄期度法对早龄期混凝土结构温度应力的分析

为合理确定早龄期混凝土的性能,考虑养护温度对混凝土力学性能的发展过程及终值的影响,引入了龄期度法,并以某高层大体积混凝土基础底板的温度场和应力场的有限元计算为例,讨论了应用龄期度法对早龄期混凝土结构温度应力计算问题。在有限元分析中应用龄期度法,要求每个单元都具有不同的材料属性,并且每个单元的材料属性都要随荷载步改变,计算中满足了上述两个要求,并通过计算说明了该基础底板实测内外温差超过规范规定的温差限值而未出现裂缝的原因。