支持协同工作的人机界面模型

一、前言 人们越来越明显地认识到人机界面在系统开发中的重要作用。它是用户与软件交流的直接语言。有人作过统计,软件开发的70%工作量在于人机界面的设计和改善。人机界面的质量高低会对学习时间、运行速度、出错率和用户满意度等方面产生极大的影响。一个使用方便的系统具有明显的竞争优势。当一个对话式系统设计得很好时,人机界面仿佛消失,使用户能集中精力他们的工作、开发和愉悦之中。系统使用方便的主要原因必定是具有一个良好的人机界面。从某种程度上讲,一个软件开发的成功与否,主要取决于该软件的用户界面开发得是否成功

超精密飞切机床结合面虚拟材料法建模及模态优化

在超精密飞切加工中,机床自身的动态特性是引起加工表面微波纹的主导因素。为探究超精密金刚石飞切机床的动态特性及其对加工表面微波纹的影响机理,将虚拟材料法的结合面建模方法引入整机动力学模型中。进一步地,利用有限元分析软件进行整机的模态分析及优化。结果表明:相较于传统的弹簧-阻尼模型,该模型具有更高的综合精度。同时模态分析表明,机床固有频率为268 Hz的第五阶模态对加工尤为敏感,而通过适当增加结合面的结合刚度,可优化机床模态进而消除波纹提高表面质量。科学挑战计划(JCKY2016212A506-0504

Surface texture analysis for ultra-precision flycutting machining based on the dynamic characteristics of machine tools

采用超精密飞切加工技术可获得软脆性平面光学元件的最终表面,而元件表面微观形貌的加工可控性对于光学元件使用性能有直接影响。首先运用多尺度小波分解方法,对飞切机床的加工表面波纹进行了特征提取,得到了工件表面波纹的频率组成及占比;然后通过对机床主轴系统的有限元分析,结合冲击振动测试,找到了与工件表面波纹对应的模态;最后通过对机床的在线振动测试及加工实验进一步明确了飞切加工表面微波纹的成因。结果表明:表面波纹在17 mm左右的空间周期上存在最大的分量,显著影响光学元件的精度和使用效果,该波纹由主轴系统在间断切削的冲击响应所引起,可以通过改变主轴结构实现波纹频率和幅值的控制。Ultra-precision flycutting is widely used to machine soft and brittle plane optical elements,and the controllability of micro surface texture affects the performance of the element directly. The multi-scale wavelet decomposition was used to detect the wave feature of the optical element machined by flycutting machine tool,and the frequency and percent of the waves were achieved. The relevant modals of those waves were found by the finite element analysis and the response test of the spindle system. Particularly,online vibration test and machining experiments were conducted to verify the factor bringing about the micro surface texture on the element. The results show that the micro surface texture at a space period of 17 mm is the most prominent and will make worse observably the accuracy and application of the element,which is caused by the response of the spindle system during the machining process. In addition,modifying the structure of spindle system can make a difference on the amplitude and frequency of the wave.国家级基金(2013ZX04006011-102-001

Formation and solving for the micro-waves of fly-cut surface introduced by spindle error

为分析超精密飞切机床加工表面微波纹的形成机理,研究了主轴回转误差信息提取与表面形貌仿真技术,获取微波纹误差来源并研究解决方案。首先,在超精密飞切机床主轴上搭载五通道在线电容位移检测系统,并对采集到的信号进行误差分析提取。然后,建立飞切加工表面微观形貌三维仿真模型,仿真分析主轴误差引入的加工表面微波纹,并与表面检测结果比对确定误差来源。最后,通过调整主轴电机控制系统抑制该误差。三维仿真和实测结果相吻合,证实超精密飞切机床主轴转速波动导致的回转误差造成了工件表面1 Hz左右的规律性条纹,对主轴转速控制系统进行数字化改造后,基本消除了该因素导致的表面微波纹,表面粗糙度从5 nm以上抑制到2 nm左右,PV值优于10 nm。超精密飞切机床主轴转速波动会对飞切加工表面微观形貌以及表面粗糙度产生显著影响,需至少控制在0.5 r/min以内。In order to find out the formation mechanism of micro-waves on the fly-cut surface,the spindle motion error was sampled and a 3D topography simulation model was compiled. Firstly,a nano-class testing and evaluation system was established on the fly cutting machine,the displacement data was sampled and the spindle motion error was analyzed.Then a 3D surface profile topography simulation model was established to analyze the micro-waves caused by the spindle motion error. The simulated surface was compared with the measured surface to find out the error sources. Finally,the characteristics of spindle were improved by adjusting the control system of the spindle motor. The simulated 3D surface profile topography was similar to that of the measured profile,which verified that the macro-waves was caused by the undulate of the spindle speed. When the spindle characteristics was improved,the macro-waves caused by the spindle motion error almost disappeared,and the surface roughness reduced from more than 5 nm to 2 nm. It is thus concluded that the undulate of ultra-precision fly cutting machine spindle speed causes macro-waves on the work-piece surface,and the undulate spindle speed must less than 0. 5 r / min.基金项目:高档数控机床与基础制造装备《强激光光学元件超精密制造关键装备研制》(2013ZX04006011-102-001

On-line measurement and evaluation of spindle error motion in ultra precision machine tool

为了实现对超精密机床主轴回转误差的在线测试与评价,建立了纳米级在线测试与评价系统。对该系统所采用的测试仪器、干扰抑制、数据处理与指标评价方法进行研究。首先,在某台超精密切削机床上搭建了由5个电容传感器组成的5通道测试模块。接着,以多通道高速数据采集模块实现多通道位移数据模拟量的高速采集。然后,对采集的信号进行必要的干扰信号分离。最后,将5通道位移数据转换为易于理解的轴向误差和径向误差数据,并按照同步误差和异步误差进行分离。测试结果表明:该机床主轴工作转速下的径向同步误差为405 nM,径向异步误差为66 nM;轴向同步误差为59 nM,轴向异步误差为54 nM。能够实现超精密机床主轴回转误差的纳米级在线测试,对于超精密光学加工表面的误差溯源和机床主轴性能分析具有重要意义。In order to realize the on-line measurement and analysis of spindle error motion in ultra precision machine,a nano-class testing and evaluation system is established and its measurement instruments,interference control,data processing,evaluation methods and etc.are investigated.Firstly,a five-channel module consisted of five capacitance sensors is established on an ultra precision cutting machine.All the five channels of the displacement sensors are sampled via a high speed data acquisition system simultaneously.Secondly,the separation of interference signals from displacement sensors has been carried out.Finally,the displacement signals are transformed into radial error and axial error,and are separated as synchronous and asynchronous error.Experimental results indicate that the synchronous error and the asynchronous error in radial direction are 405 nm and 66 nm respectively,and the synchronous error and the asynchronous error in axial direction are 59 nm and 54 nm respectively.It can meet the system demands of nano-class,on-line measurement of ultra precision spindle.Thus,it is of great importance for the optical work piece's surface error tracing,and the spindle's performance analyzing.高档数控机床与基础制造装备“强激光光学元件超精密制造关键装备研制”(2013ZX04006011-102-001

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors