利用机器视觉系统对磨削过程进行状态监测

V. Gopan, S. Ragavanantham, S. Sampathkumar
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引用次数: 4

摘要

本研究旨在开发一种非接触式方法来测量砂轮载荷和砂轮磨损,从而确定最佳修整间隔。本文借助机器视觉系统,提出了一种系统的车轮载荷测量方法。砂轮的图像是用数码相机拍摄的。这些图像已被传输到计算机,并被处理以确定加载的百分比。利用MATLAB的图像工具箱进行图像处理。全局阈值分割技术用于区分车轮的负载区域与背景的其余部分。对砂轮在静态和动态条件下的图像进行了采集和分析。实验结果表明,利用机器视觉系统对砂轮加载进行在线监测是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Condition monitoring of grinding process through machine vision system
This study aims at developing a non-contact method for measuring the grinding wheel loading and wheel wear and thereby determining the optimum dressing intervals. With the aid of a machine vision system, this paper presents a systematic process for measuring the wheel loading. The images of the grinding wheel have been taken using a digital camera. These images have been transferred to the computer and are processed for determining the percentage of loading. The image toolbox of MATLAB has been used for image processing. Global thresholding technique has been used to differentiate the loaded region of the wheel from rest of the background. Images of the grinding wheel in static as well as dynamic condition are taken and are analyzed. Experimental results are presented which show the ability of using machine vision system in the online monitoring of the grinding wheel loading.
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