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Measurement of Micro Burr and Slot Widths through Image Processing: Comparison of Manual and Automated Measurements in Micro-Milling

机译:通过图像处理测量微毛刺和槽宽度:微铣削手动和自动测量的比较

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摘要

In this study, the burr and slot widths formed after the micro-milling process of Inconel 718 alloy were investigated using a rapid and accurate image processing method. The measurements were obtained using a user-defined subroutine for image processing. To determine the accuracy of the developed imaging process technique, the automated measurement results were compared against results measured using a manual measurement method. For the cutting experiments, Inconel 718 alloy was machined using several cutting tools with different geometry, such as the helix angle, axial rake angle, and number of cutting edges. The images of the burr and slots were captured using a scanning electron microscope (SEM). The captured images were processed with computer vision software, which was written in C++ programming language and open-sourced computer library (Open CV). According to the results, it was determined that there is a good correlation between automated and manual measurements of slot and burr widths. The accuracy of the proposed method is above 91%, 98%, and 99% for up milling, down milling, and slot measurements, respectively. The conducted study offers a user-friendly, fast, and accurate solution using computer vision (CV) technology by requiring only one SEM image as input to characterize slot and burr formation.
机译:在该研究中,使用快速准确的图像处理方法研究了Inconel 718合金的微铣削过程之后形成的毛刺和槽宽。使用用于图像处理的用户定义的子程序获得测量。为了确定显影成像过程技术的准确性,将自动测量结果与使用手动测量方法测量的结果进行比较。对于切割实验,使用具有不同几何形状的多个切割工具,例如螺旋角,轴向前角度和切削刃数量的螺旋角度。使用扫描电子显微镜(SEM)捕获毛刺和槽的图像。捕获的图像是用计算机视觉软件处理的,该软件是用C ++编程语言和开放式计算机库(打开CV)编写的。根据结果​​,确定槽和毛刺宽度的自动和手动测量之间存在良好的相关性。所提出的方法的准确性分别高于91%,98%和99%,分别用于铣削,下铣和槽测量。的进行的研究提供了用户友好的,速度快,并且使用计算机视觉(CV)技术,通过仅需要一个SEM图像作为输入来表征槽和毛刺的形成准确的解决方案。

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