Systematic selection and evaluation of relevant surface roughness parameters for the characterisation of the innovative RPM-Synchronous Grinding process

表面粗糙度 凸轮轴 研磨 机械工程 材料科学 工作流程 表面光洁度 过程(计算) 计算机科学 复合材料 工程类 操作系统 数据库
作者
Katharina Newrkla,Thomas Spenger,Ulrike Cihak-Bayr
出处
期刊:Surface topography [IOP Publishing]
卷期号:9 (1): 015022-015022 被引量:2
标识
DOI:10.1088/2051-672x/abdfb9
摘要

Abstract The key to high performances and long lifetimes of machine components in lubricated contacts is often the surface topography. Its characteristics can be derived in numerous ways from 3D topography measurements, but these procedures do not follow any existing standards, resulting in limited comparability. In this work, we present a new, universally applicable workflow to reveal the most significant roughness parameters for a comprehensive description of differences in surface topographies. This workflow, based on principal component analysis (PCA), offers a standardization of parameter selection. It is applied to RPM-Synchronous Grinding (RSG), a novel grinding process that enables the production of non-circular geometries without an oscillating movement. To increase trust in this new technique, knowledge on how the process parameters affect the surface topography is required. Numerous statistical roughness parameters were derived from 3D confocal light microscopy as well as 2D tactile measurements on each ground workpiece. We apply the proposed workflow and find that, for the selected RSG parameter variations, R q is the most relevant roughness parameter to capture changes in the surface topography. The 100 % fused white aluminum oxide grinding wheel, opposite grinding direction, and a low specific material removal rate result in the smoothest surfaces. A high degree of usage of the grinding wheel leads to higher R q values, but there is a trend to reach a plateau value. The RSG machined workpieces are compared to conventionally ground and shortly run camshafts. The camshafts have R q values in the range of the rougher RSG machined surfaces, but there are significant differences in the parameters S sk , S ku , S v and V vv . Provided the number of workpieces is high enough for statstical analysis, we propose to apply our workflow for the selection of the most relevant roughness parameters to describe the differences between surfaces obtained by different machining parameters and processes.
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