可用于虚轴和普通刀具刃磨机床的数控系统

介绍了一种开放式数控系统.该系统可用在虚轴刀具刃磨机床和普通刀具刃磨机床.给出了该控制系统的硬件和软件结构,并给出了实例:在虚轴刀具刃磨机和普通刀具刃磨机磨出螺旋面钻头的实例.      

X-ray observations of black-hole accretion disks

Our current theoretical and observational understandings of the accretion disks around Galactic black-holes are reviewed. Historically, a simple phenomenological accretion disk model has been used to interpret X-ray observations. Although such a phenomenological interpretation is still useful, high quality X-ray data from contemporary instruments allow us to test more realistic accretion disk models. In a simple and ideal case, the standard optically thick accretion disk model is successful to explain observations, such that the inner disk radius is constant at three times the Schwarzschild radius over large luminosity variations. However, when disk luminosity is close to or exceeds the Eddington luminosity, the standard disk model breaks, and we have to consider the “slim disk” solution in which radial energy advection is dominant. Recent observations of Ultra-luminous X-ray sources (ULXs), which may not be explained by the standard disk model, strongly suggest the slim disk solution. We compare theoretical X-ray spectra from the slim disk with observed X-ray spectra of ULXs. We have found that the slim disk model is successful to explain ULX spectra, in terms of the massive stellar black-holes with several tens of solar mass and the super-Eddington mass accretion rates. In order to explain the large luminosities (>10⁴⁰ ergs s⁻¹) of ULXs, “intermediate black-holes” (>100M) are not required. Slim disks around massive stellar black-holes of up to several tens of solar mass would naturally explain the observed properties of ULXs.     

考虑动态不确定因素的深空探测器任务规划

针对现有的任务规划方法在响应深空动态不确定因素的扰动情况时存在的不确定因素识别度低、响应策略单一等问题,文章提出了一种考虑动态不确定因素的深空探测器任务规划算法。首先,对不确定扰动按从轻到重四个等级进行划分,并采用模糊神经网络评估不确定扰动属于哪种扰动级别,根据评估结果选择对应的扰动响应策略;然后,采用基于分层任务网络规划（HierarchicalTaskNetwork,HTN）的局部任务修复方法,对受到扰动的子系统对应的复合任务重新进行任务分解,完成对初始规划方案的调整修复。仿真结果表明所提出的算法可以有效地对深空动态不确定因素进行评估和响应,从而提高了任务规划的可靠性和灵活性。     

追踪及凝视状态下地气光对空间目标成像影响

为了分析不同探测方式下地气光辐射对空间目标成像特性的影响,利用卫星仿真工具包(satellite tool kit,STK)设计了一个以地球同步轨道(geosynchronous orbit,GEO)卫星与中轨道(medium orbit,MEO)卫星上搭载的可见光成像器为探测平台,以高椭圆轨道(highly elli...     

SAMI2 model results for the quiet time low latitude ionosphere over India

Efficacy of SAMI2 model for the Indian low latitude region around 75°E longitudes has been tested for different levels of solar flux. With a slight modification of the plasma drift velocity the SAMI2 model has been successful in reproducing quiet time ionospheric low latitude features like Equatorial Ionization Anomaly. We have also showed the formation of electron hole in the topside equatorial ionosphere in the Indian sector. Simulation results show the formation of electron hole in the altitude range 800–2500?km over the magnetic equator. Indian zone results reveal marked differences with regard to the time of occurrence, seasonal appearances and strength of the electron hole vis-a-vis those reported for the American equatorial region.     

Testing the no-hair theorem with observations of black holes in the electromagnetic spectrum

According to the no-hair theorem, astrophysical black holes are uniquely described by their mass and spin. In this paper, we review a new framework for testing the no-hair hypothesis with observations in the electromagnetic spectrum. The approach is formulated in terms of a Kerr-like spacetime containing a quadrupole moment that is independent of both mass and spin. If the no-hair theorem is correct, then any deviation from the Kerr metric quadrupole has to be zero. We show how upcoming VLBI imaging observations of Sgr A∗ as well as spectroscopic observations of iron lines from accreting black holes with IXO may lead to the first astrophysical test of the no-hair theorem.     

基于深度学习的航空发动机故障融合诊断

通过对航空发动机故障诊断,能够正确判断各部件工作状态,快速确定维修方案,保证飞行安全。在结合深度信念网络和决策融合算法的基础上,提出了基于深度学习的航空发动机故障融合诊断模型。该模型通过分析发动机的大量性能参数,先利用深度学习模型提取出性能参数中的隐藏特征,得出故障分类置信度;其后对多次故障分类结果进行决策融合,从而得出更准确的诊断结果。将普惠JT9D发动机故障系数用于数据仿真,通过算例验证本文算法的有效性;算例计算结果表明:多次实验结果经数据融合提高了可信度,该模型具有较高的故障分类诊断准确性和抗干扰能力。      

基于EMD与LS-SVM的刀具磨损识别方法

针对刀具磨损声发射信号的非平稳特征和BP神经网络学习算法收敛速度慢、易陷入局部极小值等问题,提出了基于经验模态分解和最小二乘支持向量机的刀具磨损状态识别方法.首先对声发射信号进行经验模态分解,将其分解为若干个固有模态函数之和,然后分别对每一个固有模态函数进行自回归建模,最后提取每一个自回归模型的系数组成特征向量,特征向量被分为两组,一组用于对最小二乘支持向量机训练,另一组用于识别刀具磨损状态.试验结果表明:该方法能很好地识别刀具磨损状态,与BP神经网络相比具有更高的识别率.      

深空探测返回舱着陆冲击动力学分析

为分析深空探测返回舱着陆冲击动力学问题,首先建立包括返回舱及着陆土壤在内的全柔体着陆冲击动力学分析模型,并利用"神舟号"载人飞船着陆冲击试验数据对土壤模型进行修正;然后利用非线性动力分析软件LS-DYNA对深空探测返回舱着陆冲击过程进行仿真分析。通过典型着陆工况计算,得到了返回舱着陆过程中姿态变化、应力分布、关键点加速度响应曲线及冲击能量分配等。仿真结果可为深空探测返回舱结构优化设计、着陆姿态选择及地面试验等研究提供参考。     

适合多种机床结构的数控系统5坐标变换库

研究了适合多种结构布局形式的统一坐标变换方法,开发出数控系统5坐标变换函数库,并作为坐标变换控制模块集成到数控系统中.分析了5坐标数控机床运动学模型,归纳出12种5坐标数控机床结构布局,并推导了对应的坐标变换数学算法.通过结构分析和数学变换将12种算法扩展归纳到3类基础算法,并基于3类基础算法开发出适合多种机床结构布局的5坐标变换库.利用机床三维仿真系统验证了5坐标变换库的可行性,并将该坐标变换库集成到北京航空航天大学开发的CH-2010开放式数控系统中.