坐标测量机动态测量不确定度评定研究

目前人们对三坐标测量机动态测鼍小确定度仍采用静态测量理论来评定,与其实际使用情况不符,带来一定的评定误差.本文分析了触发模式下三坐标测量机测头的主要动态误差源,通过改变测量速度和逼近距离对测头(Renishaw MH20i)动态误差的影响进行了实验测试,采用Monte Carlo方法对三坐标测量机测头动态测量不确定度进行评定,与使州传统的测量小确定度A类和B类评定结果相比较,本方法不受直接测量量相关性的限制,受问题条件限制小,评定更符合实际情况.     

复杂机电系统耦合与解耦设计--现代机电系统设计理论的探讨

针对现代大型复杂机电系统的性能与运行状态多物理过程和多参数全局耦合结果的实,提出了对复杂机电系统进行全局耦合分析及合并行设计的基本思想,探讨了全局耦合分析与设计的基本理论框架,以其研究复杂机电系统功能,奇异工况的生成机制,实现,复杂机电系统的全局耦合最优设计。     

产品拆解混合图模型构建与能量评估方法

基于拆解过程存在不确定特性的本质,结合定义的能量可拆解度概念,构建了产品拆解能量分析的理论模型。基于图论思想和面向对象技术,在定义拆解混合图基本元素的基础上,以压缩盘结构装配体为例构建拆解混合图,并生成该产品完全拆解序列及目标拆解序列。同时应用设计的Monte Carlo求解算法,对其进行完全能量可拆解度和目标能量可拆解度计算的举例分析,为实现产品拆解过程的量化评估提供了一定的理论基础。实例仿真结果表明,所提模型和方法可以有效地实现产品拆解过程的随机评估。     

An MCMC algorithm based on GUM Supplement 1 for uncertainty evaluation

This paper describes a simple Markov chain Monte Carlo algorithm for evaluating measurement uncertainty according to Bayesian principles. The algorithm has two phases, the first coinciding with the Monte Carlo method described in GUM Supplement 1 (GUMS1), the second a simple Metropolis–Hastings algorithm. The second phase can be regarded as a post-processing add-on to the GUMS1 calculation and can be used whenever a GUMS1 approach is adopted. The algorithm allows users freedom to choose their preferred prior distribution for the measurand, rather than that implicitly assigned in the GUMS1 approach, thereby avoiding some of the problems that can arise when applying GUMS1 to certain types of measurement model. The post-processing can be implemented in a few lines of software, so that many of the practical difficulties in implementing Bayesian approaches to measurement uncertainty evaluation are largely removed.     

Comparison of GUM and Monte Carlo methods for evaluating measurement uncertainty of perspiration measurement systems

Measurement uncertainty is an important parameter to express measurement results including means and reliability. The uncertainty analysis of the biomedical measurement system needs to be established. A perspiration measurement system composed of several sensors was developed. We aim to estimate the measurement uncertainty of this system with several uncertainty sources, including airflow rate, air density, and inlet and outlet absolute humidity. Measurement uncertainty was evaluated and compared by the Guide to the expression of the uncertainty in measurement (GUM) method and Monte Carlo simulation. The standard uncertainty for the perspiration measurement system was 6.81 × 10⁻⁶ kg/s and the uncertainty percentage <10%. The major source of the uncertainty was airflow rate, and inlet and outlet absolute humidity. The Monte Carlo simulation could be executed easily with available spreadsheet software programs of the Microsoft Excel. GUM and Monte Carlo simulation did not differ in measurement uncertainty with precision to two decimal places. However, the sensitivity coefficient derived by GUM provided useful information to improve measurement performance, which was not evaluated with the Monte Carlo simulation method.     

Measurement uncertainty evaluation of conicity error inspected on CMM

The cone is widely used in mechanical design for rotation, centering and fixing. Whether the conicity error can be measured and evaluated accurately will directly influence its assembly accuracy and working performance. According to the new generation geometrical product specification(GPS), the error and its measurement uncertainty should be evaluated together. The mathematical model of the minimum zone conicity error is established and an improved immune evolutionary algorithm(IIEA) is proposed to search for the conicity error. In the IIEA, initial antibodies are firstly generated by using quasi-random sequences and two kinds of affinities are calculated. Then, each antibody clone is generated and they are self-adaptively mutated so as to maintain diversity. Similar antibody is suppressed and new random antibody is generated. Because the mathematical model of conicity error is strongly nonlinear and the input quantities are not independent, it is difficult to use Guide to the expression of uncertainty in the measurement(GUM) method to evaluate measurement uncertainty. Adaptive Monte Carlo method(AMCM) is proposed to estimate measurement uncertainty in which the number of Monte Carlo trials is selected adaptively and the quality of the numerical results is directly controlled. The cone parts was machined on lathe CK6140 and measured on Miracle NC 454 Coordinate Measuring Machine(CMM). The experiment results confirm that the proposed method not only can search for the approximate solution of the minimum zone conicity error(MZCE) rapidly and precisely, but also can evaluate measurement uncertainty and give control variables with an expected numerical tolerance. The conicity errors computed by the proposed method are 20%-40% less than those computed by NC454 CMM software and the evaluation accuracy improves significantly.     

Generalized expressions of second and third order for the evaluation of standard measurement uncertainty

The Guide to the Expression of Uncertainty in Measurement (GUM) requires the use of a first-order Taylor series expansion for propagating uncertainties. However, when the measurement function is strongly non-linear the use of this linear approximation may be inadequate and therefore higher order terms from the Taylor series cannot be neglected. The present paper aims to derive generalized expressions of second and third order for the evaluation of the estimate of a measurand and its associated standard uncertainty. A case study is given to illustrate an application of the proposed methods and the results obtained with the GUM method are compared to the corresponding ones when applying the method proposed in GUM Supplement 1.     

Monte carlo method for the uncertainty evaluation of spatial straightness error based on new generation geometrical product specification

Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product specification(GPS) requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on "The Guide to the Expression of Uncertainty in Measurement(GUM)". In order to compute spatial straightness error(SSE) accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization(QPSO) is proposed to solve the minimum zone SSE and Monte Carlo Method(MCM) is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function(PDF) for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine(CMM) is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.     

复杂机械系统方案创新设计阶段符号方案的自动化生成

基于机构组合创新思想进行复杂机械系统方案设计的自动化方法研究。在实践上,开发了机构组合创新应用软件。阐明了采用该软件进行复杂机械系统方案设计的工作流程,给出了应用实例。同时,从系统的角度出发,对概念设计阶段符号方案的自动化生成进行了较为深入的研究。     

基于复杂网络的产品服务系统评价

产品服务系统具有的高阶次、多回路、非线性和不确定性等特点,使得分析和评价产品服务系统十分困难.针对这一问题,定义了服务、服务型制造网络和产品服务链等概念,并从不同视角描述产品服务系统.运用复杂网络的理论,从成本、质量、工时、可靠性、稳定性和鲁棒性多个维度剖析产品服务系统微观构成和服务间耦合机理,并以此构建了产品服务系统评价体系.该体系的建立为服务组织的检测、监控和优化提供了理论支撑.通过实例验证了评价体系的有效性和实用性.     

产品形态创新设计及其评价体系研究现状与趋势

产品形态创新评价是通过对产品形态创新的相关属性进行综合的、指标化的评判,对产品的形态创新结果进行客观、公平和合理的评价。评价结果将被应用于设计方案优选和指导设计改进。文中对产品形态设计及其相关技术、产品形态创新评价体系研究的现状进行了综述,对产品形态创新评价体系的理论基础、评价模型与指标体系进行了深入讨论,提出了产品形态创新设计评价体系研究的主要内容。     

Adaptive Monte Carlo and GUM methods for the evaluation of measurement uncertainty of cylindricity error

Measurement uncertainty is one of the most important concepts in geometrical product specification (GPS). The “Guide to the expression of uncertainty in measurement (GUM)” is the internationally accepted master document for the evaluation of uncertainty. The GUM method (GUMM) requires the use of a first-order Taylor series expansion for propagating uncertainties. However, when the mathematical model of measurand is strongly non-linear the use of this linear approximation may be inadequate. Supplement 1 to GUM (GUM S1) has recently been proposed based on the basis of probability density functions (PDFs) using the Monte Carlo method (MCM). In order to solve the problem that the number of Monte Carlo trials needs to be selected priori, adaptive Monte Carlo method (AMCM) described in GUM S1 is recommended to control over the quality of the numerical results provided by MCM.The measurement and evaluation of cylindricity errors are essential to ensure proper assembly and good performance. In this paper, the mathematical model of cylindricity error based on the minimum zone condition is established and a quasi particle swarm optimization algorithm (QPSO) is proposed for searching the cylindricity error. Because the model is non-linear, it is necessary to verify whether GUMM is valid for the evaluation of measurement uncertainty of cylindricity error. Then, AMCM and GUMM are developed to estimate the uncertainty. The procedure of AMCM scheme and the validation of GUMM using AMCM are given in detail. Practical example is illustrated and the result shows that GUMM is not completely valid for high-precision evaluation of the measurement uncertainty of cylindricity error if only the first-order terms in the Taylor series approximation are taken into account. Compared with conventional methods, not only the proposed QPSO method can search the minimum zone cylindricity error precisely and rapidly, but also the Monte Carlo simulation is adaptive and AMCM can provide control variables (i.e. expected value, standard uncertainty and lower and higher coverage interval endpoints) with an expected numerical tolerance. The methods can be extended to the evaluation of measurement uncertainty of other form errors such as roundness and sphericity errors.     

计及检修的电网可靠性评估的马尔可夫方法

针对电力系统状态检修和可靠性评估问题,对采用状态检修的电力系统可靠性评估进行了研究,提出了一种计及状态检修的电网可靠性评估方法。将影响电力系统可靠性的因素归纳为3个方面:外力破坏、设备老化、设备检修。将电力系统设备状态的变化视为无后效性的马尔可夫过程,将设备状态划分为5个等级,考虑外力破坏、设备老化、设备检修三方面的影响,分别建立无检修和有检修情况下设备的状态转移模型。在此基础上,采用蒙特卡洛仿真算法对系统进行了可靠性评估,计算常用的系统可靠性指标之一即期望缺供电量。研究结果表明,设备质量和其工作环境对系统可靠性具有明显影响,这样应首先考虑通过改善设备质量和工作环境来提升系统可靠性。     

Application of Monte Carlo simulation for estimation of uncertainty of four-point roundness measurements of rolls

Large-scale rotors in the paper and steel industry are called rolls. Rolls are reground at regular intervals and roundness measurements are made throughout the machining process. Measurement systems for roundness and diameter variation of large rolls (diameter <2000 mm) are available on the market, and generally use two to four sensors and a roundness measurement algorithm. These methods are intended to separate roundness of the rotor from its movement. The hybrid four-point method has improved accuracy, even for harmonic component amplitudes. For reliable measurement results, every measurement should be traceable with an estimation of measurement uncertainty. In this paper, the Monte-Carlo method is used for uncertainty evaluation of the harmonic components of the measured roundness profile under typical industrial conditions. According to the evaluation, the standard uncertainties for the harmonic amplitudes with the hybrid method are below 0.5 μm for the even harmonics and from 1.5 μm to 2.5 μm for the odd harmonics, when the standard uncertainty for the four probes is 0.3 μm each. The standard uncertainty for roundness deviation is 3.3 μm.     

采用灰色系统理论的家电产品设计综合评价

在对家电产品设计综合评价进行分析的基础上,分析家电产品设计综合评价模块,构建家电产品方案设计综合评价的指标系统,最后运用灰色关联分析法对家电产品设计进行综合评价。实例表明,该方法能够很好地评价家电产品的设计水平。     

电子汽车衡测量结果的不确定度评定

本文介绍了电子汽车衡不确定度的来源、测量结果评定的方法及不确定度的报告与表示,通过分析计算完整地对测量结果的质量有了一个定量的描述。     

两种不确定度评定方法在金属锑价态分析中的应用

主要研究利用液相色谱-原子荧光联用技术对水中不同价态的金属锑进行检测,并用GUM方法和Top-Down技术的控制图法分别对其测量不确定度进行评定。实验结果发现GUM方法步骤较为繁琐,对分析不确定度的来源分析容易造成遗漏或重复,对于某些不确定度来源可能难以定量。控制图法基于实验室质控工作数据,在确保数据具有正态性和独立性的前提下,评定不确定度能有效反应实验室长期质控状态,在水质检测领域的不确定度评定中更为适用。     

基于绿色特征的方案设计快速生命周期评价方法

为解决常规生命周期评价方法由于固有的周期长、数据需求量大等缺点而难以适用于产品的方案设计阶段问题,提出一种基于绿色特征的快速生命周期评价方法;建立了绿色特征模型筛选设计方案中的绿色信息。采用模糊集合理论中的直觉模糊数对定性特征值进行了研究;采用Monte Carlo法处理定量特征,并将其标准差作为不确定性因子进行不确定性分析。选择合适的生命周期影响评价方法进行生命周期影响评价,得到生命周期评价结果,以完成产品设计方案的环境影响评价,从而支持产品的绿色设计。通过某公司变速箱前箱体实例对所提快速生命周期评价理论进行了验证。     

基于不确定性的复杂产品开发迭代过程优化设计

产品开发通常涉及需求、约束、资源等众多不确定因素,因此采用数字设计结构矩阵中概率数值表示任务之间不相等的关联关系,并基于数字设计结构矩阵的过程分析,计算不同过程序列的执行时间,求得最小时间的过程排布.同时采用仿真算法,获得过程执行最大到最小时间段内执行时间的概率分布.以某导弹系统性能分析过程为例,说明了复杂产品开发过程建模和过程执行顺序优化的可行性.