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Evaluation of surface roughness based on sampling array for rotary ultrasonic machining of carbon fiber reinforced polymer composites

机译:基于采样阵列的表面粗糙度评价碳纤维增强聚合物复合材料旋转超声波加工

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This paper focuses on the evaluation of surface roughness of carbon fiber reinforced polymer (CFRP) composites after rotary ultrasonic machining. The carried out research involved a novel evaluation method based on sampling array, in which N x N samples are averagely distributed over machined surface. Surface topography of each sample was measured by a white light interferometer and quantitatively characterized by arithmetical mean height (S-a). Frequency histogram of S-a in sampling array was fitted with Gaussian function. The mean value and standard deviation of Gaussian function were applied to evaluate surface quality of machined surface. The conducted research shows that the critical sampling number is 13 x 13 and the relative error has found to be less than 1%. Moreover, the spatial distribution of S-a across the surface has been analyzed innovatively and found that small value of S-a takes a large proportion while large one presents strip spatial distribution along feed direction. Fracture mechanism of reinforcement fibers accounts for this phenomenon. This research work provides a foundation for surface quality evaluation of composites and has applications for precision manufacturing industry. (C) 2019 Elsevier Ltd. All rights reserved.
机译:本文侧重于旋转超声加工后碳纤维增强聚合物(CFRP)复合材料表面粗糙度的评价。进行的研究涉及一种基于采样阵列的新型评估方法,其中N×N样品平均分布在加工表面上。通过白色光干涉仪测量每个样品的表面形貌,并通过算术平均高度(S-A)定量表征。采样阵列中S-A的频率直方图配有高斯功能。高斯函数的平均值和标准偏差应用于评估机加工表面的表面质量。进行的研究表明,临界采样数为13×13,相对误差发现小于1%。此外,创新地分析了整个表面的S-A的空间分布,发现S-A的少量比例大,而大大呈现沿馈送方向的条带空间分布。增强纤维的骨折机理占这种现象的折衷。本研究工作为表面质量评估提供了复合材料的基础,并具有精密制造业的应用。 (c)2019年elestvier有限公司保留所有权利。

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