Separation of Comprehensive Geometrical Errors of a 3-DOF Parallel Manipulator Based on Jacobian Matrix and Its Sensitivity Analysis with Monte-Carlo Method

Parallel kinematic machines （PKMs） have the advantages of a compact structure,high stiffness,a low moving inertia,and a high load/weight ratio.PKMs have been intensively studied since the 1980s,and are still attracting much attention.Compared with extensive researches focus on their type/dimensional synthesis,kinematic/dynamic analyses,the error modeling and separation issues in PKMs are not studied adequately,which is one of the most important obstacles in its commercial applications widely.Taking a 3-PRS parallel manipulator as an example,this paper presents a separation method of source errors for 3-DOF parallel manipulator into the compensable and non-compensable errors effectively.The kinematic analysis of 3-PRS parallel manipulator leads to its six-dimension Jacobian matrix,which can be mapped into the Jacobian matrix of actuations and constraints,and then the compensable and non-compensable errors can be separated accordingly.The compensable errors can be compensated by the kinematic calibration,while the non-compensable errors may be adjusted by the manufacturing and assembling process.Followed by the influence of the latter,i.e.,the non-compensable errors,on the pose error of the moving platform through the sensitivity analysis with the aid of the Monte-Carlo method,meanwhile,the configurations of the manipulator are sought as the pose errors of the moving platform approaching their maximum.The compensable and non-compensable errors in limited-DOF parallel manipulators can be separated effectively by means of the Jacobian matrix of actuations and constraints,providing designers with an informative guideline to taking proper measures for enhancing the pose accuracy via component tolerancing and/or kinematic calibration,which can lay the foundation for the error distinguishment and compensation.

Motion Error Compensation of Multi-legged Walking Robots

Existing errors in the structure and kinematic parameters of multi-legged walking robots,the motion trajectory of robot will diverge from the ideal sports requirements in movement.Since the existing error compensation is usually used for control compensation of manipulator arm,the error compensation of multi-legged robots has seldom been explored.In order to reduce the kinematic error of robots,a motion error compensation method based on the feedforward for multi-legged mobile robots is proposed to improve motion precision of a mobile robot.The locus error of a robot body is measured,when robot moves along a given track.Error of driven joint variables is obtained by error calculation model in terms of the locus error of robot body.Error value is used to compensate driven joint variables and modify control model of robot,which can drive the robots following control model modified.The model of the relation between robot＇s locus errors and kinematic variables errors is set up to achieve the kinematic error compensation.On the basis of the inverse kinematics of a multi-legged walking robot,the relation between error of the motion trajectory and driven joint variables of robots is discussed.Moreover,the equation set is obtained,which expresses relation among error of driven joint variables,structure parameters and error of robot＇s locus.Take MiniQuad as an example,when the robot MiniQuad moves following beeline tread,motion error compensation is studied.The actual locus errors of the robot body are measured before and after compensation in the test.According to the test,variations of the actual coordinate value of the robot centroid in x-direction and z-direction are reduced more than one time.The kinematic errors of robot body are reduced effectively by the use of the motion error compensation method based on the feedforward.

A Method for Identification and Compensation of Machining Errors of Digital Gear Tooth Surfaces

In order to generate the digital gear tooth surfaces(DGTS)with high efficiency and high precision,a method for identification and compensation of machining errors is demonstrated in this paper.Machining errors are analyzed directly from the real tooth surfaces.The topography data of the part are off-line measured in the post-process.A comparison is made between two models:CAD model of DGTS and virtual model of the physical measured surface.And a matching rule is given to determine these two surfaces in an appropriate fashion.The developed error estimation model creates a point-to-point map of the real surface to the theoretical surface in the normal direction.A“pre-calibration error compensation”strategy is presented.Through processing the results of the first trail cutting,the total compensation error is predicted and an imaginary digital tooth surface is reconstructed. The machining errors in the final manufactured surfaces are minimized by generating this imaginary surface.An example of ma- chining 2-D DGTS verifies the developed method.The research is of important theoretical and practical value to manufacture the DGTS and other digital conjugate surfaces.

Systematic error analysis and compensation for high accuracy star centroid estimation of star tracker

Subpixel centroid estimation is the most important star image location method of star tracker. This paper presents a theoretical analysis of the systematic error of subpixel centroid estimation algorithm utilizing frequency domain analysis under the con-sideration of sampling frequency limitation and sampling window limitation. Explicit expression of systematic error of cen-troid estimation is obtained, and the dependence of systematic error on Gaussian width of star image, actual star centroid loca-tion and the number of sampling pixels is derived. A systematic error compensation algorithm for star centroid estimation is proposed based on the result of theoretical analysis. Simulation results show that after compensation, the residual systematic errors of 3-pixel-and 5-pixel-windows’ centroid estimation are less than 2×10-3 pixels and 2×10-4 pixels respectively.

Research on coning compensation algorithms for SINS of angular rate input

To compensate the coning error of Strap-down Inertial Navigation Systems (SINS) under high dynamic angular motion, many rotation vector algorithms have been developed using angle increments information. However, most SINS use angular rate gyros. Aimed at this problem, 18 algorithms are derived based on analysis of the conventional algorithms, and corresponding coning error expressions are given. At last simulation is made which indicates that the new algorithms have much higher precision.

A Comparison of Two Linear Discriminant Analysis Methods That Use Block Monotone Missing Training Data

We revisit a comparison of two discriminant analysis procedures, namely the linear combination classifier of Chung and Han (2000) and the maximum likelihood estimation substitution classifier for the problem of classifying unlabeled multivariate normal observations with equal covariance matrices into one of two classes. Both classes have matching block monotone missing training data. Here, we demonstrate that for intra-class covariance structures with at least small correlation among the variables with missing data and the variables without block missing data, the maximum likelihood estimation substitution classifier outperforms the Chung and Han (2000) classifier regardless of the percent of missing observations. Specifically, we examine the differences in the estimated expected error rates for these classifiers using a Monte Carlo simulation, and we compare the two classifiers using two real data sets with monotone missing data via parametric bootstrap simulations. Our results contradict the conclusions of Chung and Han (2000) that their linear combination classifier is superior to the MLE classifier for block monotone missing multivariate normal data.

基于高频正交方波注入法的永磁同步电机控制研究

针对传统高频注入法解调过程复杂和观测精度受非理想因素时延影响的不足,提出一种基于高频正交方波注入法的零低速位置估计方法。首先,考虑估计旋转轴系注入的低可靠性,选择将高频信号注入静止轴系,采用简单代数运算提取出高频响应电流,通过解调正向虚拟高频响应电流初步估计转子位置;然后,针对主要非理想因素进行影响分析,在此基础上,通过解调负向虚拟高频响应电流提取出相位滞后角,完成补偿;最后,为避免启动阶段位置收敛错误,通过获取电感变化趋势判断出磁极极性。实验结果表明,所提算法在各类工况均能稳定收敛,且最大平均误差不超过1°,说明了算法的抗扰性以及准确性。

机器视觉技术在大坝表面变形监测中的适用性研究

针对大坝表面变形自动化监测中GNSS系统垂直位移监测精度低、费用昂贵和静力水准仪布设难度大、维修成本高等问题,利用机器视觉技术对大坝表面变形进行监测。室内试验结果表明,相机与标靶距离在100 m范围内,机器视觉的测量精度可达到亚毫米级,且水平和垂直变形位移精度相近。由误差分析可知,标靶与相机的距离与测量精度有明显的相关性,而环境因素是影响远距离监测精度的重要因素,并利用大坝视准线原理优化了机器视觉监测系统。最后以浙江省大力塘水库为试点,对大坝表面变形进行实时监测,结果表明,机器视觉技术完全可满足实际工程需求,且优化后的机器视觉测量技术可明显提高监测数据的精度和稳定性。

基于双目视觉的6D位姿测量误差补偿方法

针对双目视觉设备测量误差较大且单点测量误差在视野范围内分布不一致,导致测量6D位姿精度和稳定性较差的问题,提出了一种测量误差补偿方法。为了解决传统回归模型在小样本多输入多输出情况下拟合效果较差的问题,采用基于多输出最小二乘支持向量回归(MLSSVR)的算法,实现了单点测量误差准确预测,并采用遗传算法对模型超参数进行全局寻优;为了实现跟踪坐标系的位姿测量误差补偿,结合位姿测量原理,将线性问题转化为最优估计问题,通过最小化坐标变换误差函数,将多个单点预测误差转化为多点耦合误差,从而实现了6D位姿测量误差补偿。实验结果表明,所提方法将跟踪坐标系的平均位置测量误差在3个方面上分别降低了63.4%、45.2%和75.0%,平均姿态测量误差分别降低50%、48.4%和53.1%;与其它现有补偿方法相比,所提方法能显著提高双目视觉设备的测量精度,并保证不同观测角度下的测量误差补偿有效性。

机器视觉系统中光源位移误差分析与优化

为了采集多类型工况的图像,扩大神经网络的学习样本。改变光源的高度能显著影响图像的差异,为此对影响光源位移准确度的步进电机和驱动结构进行误差分析并提出对应的优化补偿方法。经由对四台步进电机所需负载分析研究,建立负载模型,优化负载驱动电路。针对传动结构中轴心定位误差以及丝杆应力的干扰分别设计优化方案并完成对整体方案的验证。实验表明优化方法能有效地减小装置误差,四组传动丝杆的定位精度分别提升了88.896%、98.336%、45.081%、31.479%,优化效果明显,为图像采集提供位移精度保证。

转台负载工况下角位置误差补偿方法研究

负载会影响转台回转轴的运动状态,进一步影响转台角位置误差的大小。通过分析负载工况下转台角位置误差傅里叶阶次的变化情况,提出一种基于谐波补偿的误差补偿方法。首先,分析负载对转台回转轴的影响,建立回转轴误差运动与角位置误差之间的数学模型,并进行数值仿真;其次,通过负载变化影响回转轴误差运动的大小,获取转台不同负载下的自校准曲线,采用傅里叶法分析对负载变化敏感的傅里叶阶次;最后,选取对负载变化敏感的傅里叶阶次拟合谐波补偿函数对转台角位置误差进行补偿。误差补偿后转台在不同负载工况下的角位置误差最大为±0.25″,与补偿后空载工况下角位置误差相差±0.03″,有效减小了负载对转台角位置误差的影响。

基于神经网络的并联机床位姿误差分析与补偿研究

为了解决并联机床位姿误差补偿这一难题,以六自由度并联机床为研究对象,基于并联机床的运动学逆解建立了位姿误差模型,得到了并联机床驱动杆杆长误差和铰链点位置误差与并联机床动平台位姿误差的关系。铰链点位置误差可以通过调整杆长来弥补,由于驱动杆杆长误差难以测量,所以基于BP神经网络设计了一种改进的修正系统输入法对并联机床动平台的位姿误差进行补偿。仿真结果表明,经过补偿后的位姿误差明显小于补偿前的位姿误差,验证了并联机床位姿误差分析与补偿方法的可靠性。

基于PSD传感器的炸点三维坐标测量方法研究

针对野外炸点空间三维坐标测量的问题,提出了基于二维PSD位置传感器的炸点位置测量方法,构建了基于二维PSD位置传感器的炸点三维坐标测量系统;基于双目视觉原理建立了炸点空间三维坐标测量数学模型;研究了被动探测系统在野外远距离下的标定技术;通过系统误差分解传递,分析了各参数的误差;在Matlab中分别绘制了炸点位置坐标3个维度的误差分布图,并分析了测量系统误差随炸点实际位置变化的分布情况;根据误差分布图得到了在理论100 m测试距离下X坐标最大测量误差约为0.292~0.303 m,Y坐标最大测量误差约为0.251~0.371 m,Z坐标最大测量误差0.270~0.336 m;最后通过静爆实验对测量方法正确性、被动探测系统标定技术可行性和测量系统功能性进行了验证,结果表明测量系统响应速度快且功能正常,被动探测系统标定技术具备可行性且操作方便,可适用于野外炸点位置的快速测量。

精密卧式车床热误差溯源、建模与实时补偿

精密卧式车床的关键部件会在内外热源的综合影响下发生热变形,进而严重影响加工精度。数据驱动的热误差建模方法为解决此问题提供了有效手段,而厘清车床的关键热误差元素及其传导机理可进一步提高车床热误差的建模效率、精度和鲁棒性。文章针对车床X轴丝杠摩擦热、主轴发热、Z轴鞍座发热以及液压刀塔和拖板发热4个关键热误差元素开展了溯源测试,并根据溯源结果建立了热误差模型并开发了热误差实时补偿系统。车削验证实验结果表明,补偿后车床的加工误差在反复的加工和冷机过程中均稳定降低了75%以上,文章所提的热误差溯源和补偿方法有效提高了车床的加工精度和稳定性。

Systematic centroid error compensation for the simple Gaussian PSF in an electronic star map simulator

Simulated star maps serve as convenient inputs for the test of a star sensor, whose standardability mostly depends on the centroid precision of the simulated star image, so it is necessary to accomplish systematic error compensation for the simple Gaussian PSF（or SPSF, in which PSF denotes point spread function）. Firstly, the error mechanism of the SPSF is described, the reason of centroid deviations of the simulated star images based on SPSF lies in the unreasonable sampling positions（the centers of the covered pixels） of the Gaussian probability density function. Then in reference to the IPSF simulated star image spots regarded as ideal ones, and by means of normalization and numerical fitting, the pixel center offset function expressions are got, so the systematic centroid error compensation can be executed simply by substituting the pixel central position with the offset position in the SPSF. Finally, the centroid precision tests are conducted for the three big error cases of Gaussian radius r = 0.5, 0.6, 0.671 pixel, and the centroid accuracy with the compensated SPSF（when r = 0.5） is improved to 2.83 times that of the primitive SPSF, reaching a 0.008 pixel error, an equivalent level of the IPSF. Besides its simplicity, the compensated SPSF further increases both the shape similarity and the centroid precision of simulated star images, which helps to improve the image quality and the standardability of the outputs of an electronic star map simulator（ESS）.

接触式钢卷中心位置检测技术误差分析与补偿

热轧钢卷生产中,需要检测到钢卷的中心位置,以便于钢卷打捆、喷码等工序的正常进行,由于热轧钢卷的生产环境恶劣,通常采用接触式测量技术检测钢卷的中心位置。分析了钢卷中心位置检测装置中触头组件的冲击变形引起的检测误差,为减小冲击,将原始触头组件改进为缓冲式触头组件;分析了由于钢卷外表面形状引起的检测误差,通过BP神经网络拟合出了误差补偿的解析式;分析了由于带钢收尾位置差异引起的检测误差,通过采用2组检测装置相结合的方式来判断触头的位置。通过上述研究,提出了相应的补偿方案,可有效提高接触式钢卷中心位置检测技术的检测精度。

基于改进GWO-GRNN的管道焊缝三维重构测量

为提高双目相机不同位姿下焊缝的三维重构测量精度,提出一种基于立体视觉图像误差补偿的管道焊缝三维重构测量方法。采用改进灰狼算法(IGWO)优化广义回归神经网络(GRNN)补偿焊缝三维重构图像点的坐标误差。采用混沌映射、非线性收敛因子和最优记忆保存思想对GWO算法进行改进,通过8个标准测试函数进行仿真验证;利用优化后的GRNN模型对图像点坐标误差进行预测和补偿,计算三维坐标重构出焊缝点云,三维测量焊缝的焊宽、余高和长度。试验结果表明:该模型在双目相机不同的位姿状态下都能较准确地实现焊缝的三维重构,焊缝的三维测量相对误差在0.9%以内。

基于GA-BP优化模型的红外CO分析仪温度补偿研究

光谱分析法是煤矿气体定量分析的重要技术手段。然而,当前广泛采用的便携式红外气体分析仪在现场测试过程中受环境温度影响较大,为提高气体分析仪的分析精度和适用性,围绕红外气体分析仪恒温加热的必要性、合理加热温度范围、测试数据误差优化模型等问题,开展了理论分析和实验研究。首先,搭建了涵盖温度补偿前、恒温加热测试、温度补偿后以及不同测试环境温度条件的红外气体分析仪实验平台,提出了实验步骤以及相应的分析方法;其次,在环境温度为25~45℃时,测试的CO气体体积分数为800×10^(-6),通过多次测试发现加热温度为45℃时,CO气体分析仪精度最佳,测试值最接近气体体积分数真实值;同时,选用CO(体积分数为10×10^(-6)~500×10^(-6))标准气体进行了精度测试,计算CO气体绝对误差仅为0~9×10^(-6),优于标准规定的误差范围;最后,设置-15~45℃的变温环境,对加热后的CO气体分析仪进行了温度补偿验证,测试得出环境温度越低,待测气体体积分数越高,则分析仪检测误差越大,最大误差可达110×10^(-6)。基于此,建立了BP、GA-BP神经网络误差分析模型,将环境温度、测试体积分数和标准气体体积分数与优化模型进行融合。对比发现:采用GA-BP神经网络模型得到的MAE值相较于BP神经网络降低了12.9823×10^(-6),且MSE、RMSE计算结果也验证了GA-BP模型在气体分析中的稳定性和可行性。

双矢量定姿在煤矿掘进机姿态测量中的应用

针对现有巷道掘进机的姿态测量手段中普遍存在的高成本和误差累积等问题,文中提出了一种基于双矢量定姿原理的姿态测量算法。通过在巷道掘进环境中分别对重力矢量和光矢量进行构建与感知,利用惯性倾角测量和双目视觉测量技术,基于矢量元素分别在导航坐标系和掘进机载体坐标系中的数学表达,可实现掘进机载体坐标系相对于巷道导航坐标系的姿态解算。利用倾斜仪和双目相机组成的测量装置对指示激光和重力矢量进行测量,结合双矢量定姿算法即可完成掘进机机身的姿态解算。文中设计了静态重复性精度测量实验,结果表明该方法的姿态角重复性测量精度为0.0662°。利用蒙特卡洛方法对可能会引入的误差源进行仿真分析,结果表明误差对方位角、俯仰角以及滚转角的影响分别为0.7864°、0.4548°和0.4765°。

煤矿用钻机上卸杆机械手的精度问题研究

上卸杆机械手作为自动化煤矿用钻机的重要组成部分,对其精度问题展开研究,分析了该机械手的控制特点及误差产生原因;利用AMESim软件对其运动控制进行仿真,得到较好的PID控制参数;以其展开形态在自身结构及钻杆重力影响下,进行有限元仿真分析。根据仿真结果对机械手结构进行修改,对重力挠度进行补偿,以满足最终姿态下机械手中心与夹持器中心的位置精度要求。