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Design of optimal measurement strategies for geometric tolerances control on coordinate measuring machines

机译:坐标测量机几何公差控制的最优测量策略设计

摘要

This study is concerned with a vast industrial problem: the inspection of physical components and subsystems for checking their conformance to dimensional and geometric tolerance specifications. Although a number of non contact optical devices are being currently developed for such a task, Coordinate Measuring Machines (CMM) are still universally adopted thanks to their superiority in terms of accuracy in the measurement of point coordinates. However, their unsurpassed metrological quality for this basic operation is counterbalanced by a fundamental problem that is plaguing practitioners in the sector of industrial metrology. The problem is usually referred to as methods divergence and can be stated as follows. On one hand, the machines probe the part surface point-wise and economic constraints force the point sample to be small. On the other end, geometric errors, as defined by tolerance standards, depend heavily on extreme values of the form deviations over the related surface so that a full-field inspection is virtually required. For example, straightness error is the minimum distance between two parallel lines enclosing the actual feature. Thus extreme points are more important than the others in determining the straightness error. This problem, translated in statistical terms, means using a small sample of form deviations to make inference on a quantity dependent on extreme values of the population, thereby unlikely to be in the sample. Thus sample-based evaluation of geometric errors is naturally prone to be substantially biased and uncertain, especially when the surfaces exhibit systematic form deviations. In spite of this, common practice in industry is to probe very few points according to very simple sampling strategy (uniform, random, stratified). The software packages sold with the machines contain algorithms of computational geometry which are selected by purely economic criteria (easy to implement, fast to compute) regardless of their implications on measurement quality. Moreover, user awareness of the importance of evaluating measurement uncertainty in the inspection of geometric tolerances is exceedingly limited. This is no wonder if we consider that the ISO committees have been working for several years on different four methods for uncertainty evaluation in CMM measurement tasks (ISO 15530 family) and still now only one standard has been officially delivered (ISO 15530-3, march 2004). Uncertainty calculation using calibrated objects).
机译:这项研究涉及一个巨大的工业问题:检查物理组件和子系统,以检查它们是否符合尺寸和几何公差规格。尽管目前正在为此任务开发许多非接触式光学设备,但是由于它们在点坐标的测量精度方面的优势,坐标测量机(CMM)仍然被普遍采用。然而,其基本操作无法克服的计量质量被一个困扰工业计量领域从业人员的基本问题所抵消。该问题通常称为方法分歧,可以陈述如下。一方面,机器会逐点探测零件表面,而经济限制会迫使点样变小。另一方面,由公差标准定义的几何误差在很大程度上取决于相关表面上形状偏差的极值,因此实际上需要进行全视场检查。例如,直线度误差是包围实际特征的两条平行线之间的最小距离。因此,在确定直线度误差时,极限点比其他点更重要。用统计术语翻译这个问题意味着要使用少量形式偏差样本来推断依赖于种群极值的数量,因此不太可能出现在样本中。因此,基于样本的几何误差评估自然容易产生明显的偏差和不确定性,尤其是当表面表现出系统的形式偏差时。尽管如此,工业上的惯例是根据非常简单的采样策略(均匀,随机,分层)探查很少的点。与机器一起出售的软件包包含计算几何算法,这些算法是根据纯粹的经济标准(易于实现,计算速度快)选择的,无论它们对测量质量的影响如何。此外,用户对于在检查几何公差中评估测量不确定度的重要性的认识受到极大限制。难怪我们是否认为ISO委员会已经针对CMM测量任务(ISO 15530系列)中不确定性评估的四种不同方法开展了多年的工作,而现在仍仅正式发布了一项标准(ISO 15530-3,3月) 2004)。使用校准对象进行不确定度计算)。

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    Concas Fabio;

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