数控机床线性轴角度偏差的重要性

主要介绍线性轴角度偏差与直线度潜在关系。     

角度块角度偏差测量值的不确定度评定

本文介绍了角度块的测量原理,对工作角为90°(1,2,3,4)和30°20'的二等角度块角度偏差进行比对分析,对测量结果进行不确定度评定,验证了校准能力。     

铺层角度偏差对曲面复合材料结构固化变形的影响分析

本文阐述了铺层角度偏差对某变厚度曲面结构复合材料固化变形的影响。对铺层角度偏差的来源进行了归纳,采用考虑热膨胀和固化收缩的固化变形计算模型,对该变厚度的复合材料曲面层合板结构的固化变形进行了计算,计算结果与试验结果较为吻合,表明了计算模型的准确性。采用均匀试验设计方法,得到了该曲面结构铺层角度偏差在5°以内变化时的实验方案,对实验设计的计算结果进行了回归分析,结果显示,对于该曲面复合材料结构,总体上铺层角度偏差对固化变形的影响不大,相对的,-45°的铺层偏差对固化变形的影响较大,90°的铺层偏差对固化变形的影响较小。     

设计与制造中的统计几何公差建模及应用

几何与尺寸公差(形位公差GD&T)广泛用于机械工程设计与制造中重要几何特征的偏差控制.相对较成熟和简单的尺度公差建模与分析,几何公差统计建模与分析更具挑战性,是当前CAD技术中尚未但亟待解决的课题之一.现提出采用统计几何模态模型(SMA)方法解决这一问题.SMA可识别刻划与解释测量数据中的几何特征信号模式及其变化,从而服务于制造中的(公差)质量检验、诊断及变化模式的统计建模.在设计中SMA可进行模态重组综合,从而再现或仿真几何特征偏差的随机变化进行统计几何公差分析.     

三坐标测量机测量形位公差问题分析

本文介绍了利用三坐标测量机测量形位公差时容易出现的问题及其解决办法。     

几何公差中最大实体要求的分析探讨及应用

根据《产品几何技术规范(GPS)几何公差最大实体要求、最小实体要求和可逆要求》标准要求规定,阐述最大实体要求的概念、应用最大实体要求时,形状公差与尺寸的补偿情况和相互关系;测量和控制最大实体要求下极限尺寸的方法。     

二级角度块角度偏差测量结果不确定度评定

一、测量原理使用最大允许示值误差为±2″的测角仪,依据JJG70-2004《角度块》检定规程规定的方法对工作角为50°的二等角度块角度偏差进行连续测量,得到测量结果分别为-21″、-24″、-19″、-18″、-17″、-23″、-19″、-20″、-21″、-18″。取该组数据的平均值为输入测量的最佳估计值-20″,测量结果为49°59′40″。     

角度测量及误差分析

在经济建设、国防建设和科学技术各部门都离不开角度计量问题。诸如切削刀具的测量 ,零件有关角度的测量 ,仪器或机床导轨的检验和装调 ,以及天文研究 ,大地测量 ,水利、交通建设 ,导弹和卫星的发射等 ,都跟角度计量有密切联系。角度测量分为直接测量和间接测量两种。一、直接测量全组合互比法一般用来检定高精度的圆分度器件 ,如用多面棱体检定多齿分度台、测角仪、光学分度头等的分度误差。它是根据多面棱体和被检仪器的度盘都具有圆周封闭的特点 ,用多面棱体的各工作角与被检仪器的同一分度间距相比较 ,利用封闭原理消除多面棱体各角值误…     

车身尺寸公差及定位系统在汽车设计中的应用

理解车身各种尺寸公差的定义及要求,来布置车身上的定位点参考系统,既（RPS）,从而满足整车在设计、开发、制造以及检验的过程中的定位要求,达到定位点统一的原则,避免因定位点的改变而产生误差,最终达到提升整车质量的目的。     

浅析孔基本偏差换算的两个规则及应用

本文针对教材中关于孔基本偏差的换算方法及换算的前提条件阐述的不够详细等问题着重介绍了孔基本偏差换算的两个规则和应用及其应用时须注意的问题。     

光学薄膜的误差灵敏度和允差分析

实际生产出的薄膜的光学特性和理论计算得到的光学特性常常存在差别,这些差别的来源有多种,诸如理论模型假设时忽略的一些因素;薄膜久置引起的薄膜结构改变或吸潮、污染;制造过程中的制造误差(光学监控系统引起的薄膜厚度和折射率的误差)等.针对各种误差的来源有相应的改善方法.本文就光学监控系统引起的薄膜厚度和折射率的误差进行分析,同时提出膜系的允差分析,以尽量减小由于监控设备引起的误差,最后介绍了实际生产的计算机优化监控程序.     

Representation of geometric variations using matrix transforms for statistical tolerance analysis in assemblies

The goal of this article is to develop a tolerance representation for assemblies compatible with tolerance analysis based on a closed-form algorithm used in robotic applications. A methodology is described that represents standard Y14.5M-1982 tolerances using homogeneous 4×4 matrix transforms. Transforms represent both the nominal relations between parts and the variations caused by geometric deviations allowed by the tolerances. The analysis calculates a statistical estimate of the location of theNth part in an assembly starting from the first part or a fixture. Except forform tolerances, most types of tolerance specifications are compatible with the proposed representation. This approach is well suited to integration with CAD systems and feature-based design. Since assembly apparatus errors can be calculated using the same methodology, one can predict the relative position and angle errors between two parts about to be mated. This permits useful evaluation of assembly equipment errors, comparison of different product tolerance assignments, and calculations of assembly process capability.     

铺层取向误差对CFRP可折叠管件半片变形影响的数值分析与试验研究

以单层厚度为0.04mm的碳纤维/树脂(T300/5228,CFRP)超薄单向预浸料,采用真空袋-固化炉成型方法制备了一系列不同铺层复合材料"Ω"型可折叠管件半片,并采用ANSYS软件进行了有限元分析,通过实验和数值模拟方法研究了铺层方式及取向误差对变形的影响,制备的四种铺层方式制件实验测量其变形趋势与相应模拟分析结果一致,得到了铺层取向误差对变形影响较小的铺层方式。研究发现:±45°铺层比0°铺层的铺层取向误差对变形影响更大,增加90°铺层可以在一定程度上控制因铺层取向误差导致的可折叠管件半片的变形。研究结果表明通过铺层设计可以在一定程度上实现对CFRP可折叠管件半片变形的控制。     

采煤机大倾角爬坡试验行走曲线的设计与运动分析

为了解决采煤机在煤层倾角大于20°的工作面采煤工作时经常出现牵引力不足,制动效果不好,采煤机在停机和开机时溜坡下滑等问题,太重煤机有限公司自主设计、建造了大功率采煤机爬坡试验设施用于大功率大倾角采煤机爬坡试验基地。本文主针对采煤机爬坡试验行走曲线和采煤机制动器失效后的运动分析及试验安全防范方面的问题进行了一些论证和探讨。     

Serial production lines with geometric machines and finite production runs: performance analysis and system-theoretic properties

A production run is typically referred to as a group of identical goods that is produced by a particular manufacturing process. In many discrete manufacturing practices, the manufacturing activity is carried out by deploying a series of production runs of different products according to customer orders. If the volume of a production run is relatively small and process changeovers are necessary, the production system operates partially (or entirely) in the transient regime, especially at the beginning and near the end of a production run. In this case, the traditional steady-state analysis approach may become inapplicable. In this paper, we consider finite production run-based manufacturing in serial lines with machines obeying the geometric reliability model and buffers having finite capacity. Exact Markovian analysis is first used to derive the closed-form formulae to calculate the transient performance of the production line during a production run as well as the distribution, mean, and standard deviation of its completion time in one- and two-machine lines. For multi-machine lines, an aggregation-based approach is proposed to approximate the system performance measures with high accuracy and computational efficiency. In addition, system-theoretic properties of production run completion time with respect to machine and buffer parameters are discussed.     

基于主分量分析的声信号特征提取及识别研究

主分量分析(PCA)是统计学中分析数据的一种有效方法。研究了基于这种算法对四种战场目标的声信号进行特征提取,获得了低维的特征类器对声目标进行分类,分类结果准确率较高,均获得满意的实验效果     

一种基于核主成分分析和组合分类器的虹膜识别方法

提出了一种新的虹膜特征提取与识别方法,该方法利用核主成分分析(KPCA)在高维空间具有较强的特征选择能力来提取虹膜图像的纹理特征。采用了一种距离度量和支持向量机相结合的两级分类方法,前级采用欧式距离来度量图像间的相似性,若符合条件,给出分类结果,否则拒绝,并转入后一级分类器——支持向量机分类,以减少进入支持向量机的样本数目,该组合分类方法充分利用了支持向量机识别率高和距离度量速度快的优点。实验结果表明,该方法提高了虹膜识别率,是一种有效的虹膜识别方法。     

Evaluation and analysis of cutting speed,wire wear ratio,and dimensional deviation of wire electric discharge machining of super alloy Udimet-L605 using support vector machine and grey relational analysis

The current study investigates the behavior of wire electric discharge machining (WEDM) of the super alloy Udimet-L605 by employing sophisticated machine learning approaches.The experimental work was designed on the basis of the Taguchi orthogonal L27 array,considering six explanatory variables and evaluating their influences on the cutting speed,wire wear ratio (WWR),and dimensional deviation (DD).A support vector machine (SVM) algorithm using a normalized poly-kernel and a radial-basis flow kernel is recommended for modeling the wire electric discharge machining process.The grey relational analysis (GRA) approach was utilized to obtain the optimal combination of process variables simultaneously, providing the desirable outcome for the cutting speed, WWR,and DD.Scanning electron microscope and energy dispersive X-ray analyses of the samples were performed for the confirmation of the results.An SVM based on the radial-basis kernel model dominated the normalized polykernel model.The optimal combination of process variables for a mutually desirable outcome for the cutting speed,WWR,and DD was determined as T_on1,T_off2,I_P1, WT3,SV1,and WF3.The pulse-on time is the significant variable influencing the cutting speed,WWR,and DD.The largest percentage of copper (8.66%) was observed at the highest cutting speed setting of the machine compared to 7.05% of copper at the low cutting speed setting of the machine.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-017-0192-7     

基于时频切片分析的故障诊断方法及应用

为了提取设备的故障特征,提出了基于时频切片分析的故障特征提取方法。首先采用基于频率切片小波变换分解振动信号,得到信号在全频带的时频分布。在此基础上根据其时频能量分布,选择时间频率切片区间进行细化分析,通过时频分割和信号重构得到选定区间的时频特征,实现了故障特征的分离。这种方法能够有效地获取正确的故障特征信息,在某炼油厂齿轮箱摩擦故障诊断中取得了较好的效果。     

Brain tumor severity analysis using modified multi‐texton histogram and hybrid kernel SVM

Magnetic resonance image (MRI) segmentation refers to a process of assigning labels to set of pixels or multiple regions. It plays a major role in the field of biomedical applications as it is widely used by the radiologists to segment the medical images input into meaningful regions. In recent years, various brain tumor detection techniques are presented in the literature. In this article, we have developed an approach to brain tumor detection and severity analysis is done using the various measures. The proposed approach comprises of preprocessing, segmentation, feature extraction, and classification. In preprocessing steps, we need to perform skull stripping and then, anisotropic filtering is applied to make image suitable for extracting features. In feature extraction, we have modified the multi‐texton histogram (MTH) technique to improve the feature extraction. In the classification stage, the hybrid kernel is designed and applied to training of support vector machine to perform automatic detection of tumor region in MRI images. For comparison analysis, our proposed approach is compared with the existing works using K‐cross fold validation method. From the results, we can conclude that the modified multi‐texton histogram with non‐linear kernels has shown the accuracy of 86% but the MTH with non‐linear kernels shows the accuracy of 83.8%.