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Quantification of the Morphological Signature of Roping Based on Multiscale Analysis and Autocorrelation Function Description

机译:基于多尺度分析和自相关函数描述的绳索形态特征的量化

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摘要

Roping or ridging is a visual defect affecting the surface of ferritic stainless steels, assessed using visual inspection of the surfaces. The aim of this study was to quantify the morphological signature of roping to link roughness results with five levels of roping identified with visual inspection. First, the multiscale analysis of roughness showed that the texture aspect ratio S computed with a low-pass filter of 32 µm gave a clear separation between the acceptable levels of roping and the non-acceptable levels (rejected sheets). To obtain a gradation description of roping instead of a binary description, a methodology based on the use of the autocorrelation function was created. It consisted of several steps: a low-pass filtering of the autocorrelation function at 150 µm, the segmentation of the autocorrelation into four stabilized portions, and finally, the computation of isotropy and the root-mean-square roughness S on the obtained quarters of function. The use of the isotropy combined with the root-mean-square roughness S led to a clear separation of the five levels of roping: the acceptable levels of roping corresponded to strong isotropy (values larger than 10%) coupled with low root-mean-square roughness S . Both methodologies can be used to quantitatively describe surface morphology of roping in order to improve our understanding of the roping phenomenon.
机译:绳索或骑行是影响铁素体不锈钢表面的视觉缺陷,使用目视检查表面进行评估。本研究的目的是量化绳索的形态学签名,以将粗糙度与目视检查确定的五种绳索相结合。首先,粗糙度的多尺度分析表明,使用32μm的低通滤波器计算的纹理纵横比S在可接受的绳索和不可接受的水平(被拒绝的纸张)之间进行了清晰的分离。为了获得绳索的渐变描述而不是二进制描述,创建了一种基于自相关函数的使用方法。它由几个步骤组成:在150μm处的自相关函数的低通滤波,将自相关的分割成四个稳定部分,最后,在所获得的宿舍上计算各向同性和根均方粗糙度S.功能。使用各向同性联合与根平均方粗糙度S的结合导致了五级绳索的清晰分离:可接受的绳索水平对应于具有低根性的强大的各向同性(大于10%的值),相应方形粗糙度。两种方法都可用于定量描述绳索的表面形态,以改善我们对绳索现象的理解。

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