非线性油膜支承裂纹转子振动特性分析

 以具有无限长轴承和无限短轴承支承的横向裂纹转子为研究对象,分析在非线性油膜力与横向裂纹联合作用时,Jeffcott转子的动力特性,并将其与刚性支承情况进行比较。结果表明轴承油膜力的存在对裂纹转子的振动影响较大,一般将降低转子的振动,这样势必增加转子裂纹故障诊断的难度。所以,在进行裂纹转子的故障诊断时,必须考虑到支承条件的影响,建立合理的动力学模型。     

给定通流部分形状时轴流压气机级性能优化

用一维理论对轴流压气机的初步设计作了进一步研究，导出了轴流压气机基元级的特性关系。建立了在给定通流部分形状时最优化设计的数学模型。得到了解析关系。并通过研究给出了数值算例。所得解析关系具有一定的普适性，并可进一步拓展用于多级轴流压气机优化中。     

基础横向振动对电磁轴承转子系统动力特性影响的实验研究

从实验上研究了电磁轴承基础的横向振动对电磁轴承转子系统动力特性的影响。结果表明电磁轴承的控制器对电磁轴承基础横向振动的抑制能力是非常有限的,在控制器的设计过程中必须考虑基础振动的影响,否则较大的基础振动会使电磁轴承系统不能稳定地工作,甚至失去支撑转子的能力。     

滚动轴承振动与噪声关系的灰色研究

以灰色系统理论为基础,通过实验,研究6201和6203轴承振动与噪声的关系。振动用加速度有效值描述,噪声以声压级表示。实验数据处理结果表明,轴承振动与噪声的关系不明显,并具有很大的不确定性。因此,不宜用轴承的振动代替轴承的噪声,应单独研究轴承的噪声问题,制订轴承噪声标准和相应的工艺标准。      

涡轴发动机组合压气机转子轴向预紧力计算方法

采用PATRAN软件建立了涡轴发动机组合压气机转子轴向预紧力的三维循环对称有限元计算模型,用MSC/MARC分析软件进行了计算分析,确定了转子中心拉杆和小拉杆的轴向预紧力,并在组合压气机转子的相关试验中对计算结果进行了验证。本文的研究为同类转子的轴向预紧力计算进行了有益的探索。      

基于神经网络的滚动轴承故障包络信号的自动识别方法

介绍了一种基于神经网络的滚动轴承故障包络信号的自动识别方法。将从包络信号的时域和频域信息中提取的反映滚动轴承故障的特征信息作为BP神经网络的输入,用BP算法对该网络进行训练。利用BP神经网络的智能性来实现滚动轴承故障的智能诊断。     

三支承磁悬浮轴承转子系统性能的实验分析

在一般磁悬浮轴承转子系统的基础上增加辅助磁悬浮支承组件,构成磁轴承与辅助磁悬浮支承组合三点支承转子系统。通过试验模态分析和系统高速旋转实验研究了不同控制参数下,组合支承柔性转子系统的动态性能,并与二支承系统进行了比较。实验结果表明,辅助磁悬浮支承对系统性能有较大影响,提高了系统在各阶模态振动时的阻尼,使系统顺利越过二阶弯曲临界转速在16000rpm以上稳定运行。     

某型发动机轴流叶轮疲劳寿命分析

为准确了解某型发动机的关键零部件——轴流叶轮的使用寿命,进而提高其可靠性,分析了该轴流叶轮的痧劳寿命,并通过疲劳寿命试验进行了验证．研究结果为轴流叶轮的定寿和延寿提供了重要依据。     

The Origin of Mercury’s Internal Magnetic Field

Mariner 10 measurements proved the existence of a large-scale internal magnetic field on Mercury. The observed field amplitude, however, is too weak to be compatible with typical convective planetary dynamos. The Lorentz force based on an extrapolation of Mariner 10 data to the dynamo region is 10⁻⁴ times smaller than the Coriolis force. This is at odds with the idea that planetary dynamos are thought to work in the so-called magnetostrophic regime, where Coriolis force and Lorentz force should be of comparable magnitude. Recent convective dynamo simulations reviewed here seem to resolve this caveat. We show that the available convective power indeed suffices to drive a magnetostrophic dynamo even when the heat flow though Mercury’s core–mantle boundary is subadiabatic, as suggested by thermal evolution models. Two possible causes are analyzed that could explain why the observations do not reflect a stronger internal field. First, toroidal magnetic fields can be strong but are confined to the conductive core, and second, the observations do not resolve potentially strong small-scale contributions. We review different dynamo simulations that promote either or both effects by (1) strongly driving convection, (2) assuming a particularly small inner core, or (3) assuming a very large inner core. These models still fall somewhat short of explaining the low amplitude of Mariner 10 observations, but the incorporation of an additional effect helps to reach this goal: The subadiabatic heat flow through Mercury’s core–mantle boundary may cause the outer part of the core to be stably stratified, which would largely exclude convective motions in this region. The magnetic field, which is small scale, strong, and very time dependent in the lower convective part of the core, must diffuse through the stagnant layer. Here, the electromagnetic skin effect filters out the more rapidly varying high-order contributions and mainly leaves behind the weaker and slower varying dipole and quadrupole components (Christensen in Nature 444:1056–1058, 2006). Messenger and BepiColombo data will allow us to discriminate between the various models in terms of the magnetic fields spatial structure, its degree of axisymmetry, and its secular variation.     

基于EMD熵特征融合的滚动轴承故障诊断方法

研究了滚动轴承故障诊断单一故障信号的局限性和故障特征的非线性,从信息融合的理论出发,利用非线性动力学参数熵作为特征,提出了基于经验模态分解(EMD)熵特征融合的方法来解决滚动轴承故障诊断问题.首先将原始信号进行EMD,利用EMD的自适应多分辨率的特点计算EMD得到的固有模态函数(IMF)信号的多种熵值,然后采用核主元分析(KPCA)对提取的状态特征进行信息融合,从而得到互补的特征,最后将提取的融合特征通过支持向量机(SVM)进行故障诊断.滚动轴承故障诊断实验表明:该方法结合了EMD、信息熵理论和KPCA强大的非线性处理能力的特点,可以进行滚动轴承故障诊断.