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What data is the surface roughness mainly evaluated by?

Abstract: 表面粗糙度的评估主要依赖于几个关键数据指标。高度特征参数包括等值线算术平均值偏差(Ra),它是轮廓偏差的算术平均值,能准确反映表面粗糙度;剖面最大高度则表示剖面峰值线与谷值底线之间的距离。间距特征参数如轮廓细胞的平均宽度(Rsm)衡量微观粗糙度的间距,表面纹理也会因Rsm值不同而异。形状特征参数Rmr反映轮廓支撑长度与采样长度的比率,等值线支撑长度表示截面长度的总和。这些指标共同帮助评估和理解表面的粗糙程度及其对性能的影响。

Height characteristic parameter

Contour Arithmetic Mean Deviation: The arithmetic mean of the absolute value of the contour deviation within the sampling length (lr). In actual measurement, the more measurement points, the more accurate Ra will be.

Profile maximum height: the distance between the peak line of the profile and the bottom line of the valley.

Ra is preferably within the common range of the amplitude parameter.

Spacing Feature Parameters

Surface roughness is mainly based on what data evaluation?  Picture 1

Average width of outline cells. The average value of the microroughness spacing of the profile within the sample length. The microroughness spacing refers to the length of the profile peaks and adjacent profile valleys on the centerline. In the case of the same Ra value, the Rsm value is not necessarily the same, so the reflection texture will also be different. Surfaces that pay attention to texture usually pay attention to two indicators, Ra and Rsm,

The Rmr shape feature parameter is represented by the contour support length ratio, that is, the ratio of the contour support length to the sampling length.

The contour support length is the sum of the section lengths obtained by intersecting the contour with a line parallel to the midline and at a distance c from the peak line of the contour within the sampling length.

Surface roughness is mainly based on what data evaluation?  Picture 2

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