用于测量工业部件尺寸的计算计量学

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY

International Journal of Mathematical Engineering and Management Sciences Pub Date : 2023-10-01 DOI:10.33889/ijmems.2023.8.5.048

Lokendra Singh, Arpan Gupta

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引用次数: 0

摘要

针对工业中物体尺寸测量的问题，提出了一种基于Harris角点检测的计算机视觉新方法。拟议的研究为满足各种精确测量设备和熟练劳动力的需求提供了一种替代方案。为了测量物体的各个维度，所提出的算法根据像素强度的变化从背景中分离出角点。已经提出了一种算法来分析捕获的物体图像并执行测量和检查过程。本文的目的是利用计算机视觉检测算法，通过对零件的尺寸公差进行排序来控制零件的质量。根据使用智能手机相机（三星Galaxy F62）拍摄的图像，确定了各种物体的长度，如螺钉、螺栓和矩形铁片。提供了总共八种不同测量的证据，并证明该方法的精度相对于使用游标卡尺测量的尺寸高达99%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Computational Metrology for Measuring Industrial Component Dimensions

To target the problem of dimension measurement of objects in industry, a new computer vision method is proposed based upon Harris-corner detection. The proposed research delivers an alternative to the requirement of various precise measurement devices and skilled labour. In order to measure the various dimensions of an object, the proposed algorithm separates the corner points from the background based on variations in pixel intensity. An algorithm has been proposed to analyze captured object images and perform measurements and inspection processes. The aim of this paper is to utilize computer vision detection algorithms to control the quality of manufactured parts by sorting them on size tolerance. The length of various objects such as screws, bolts, and a rectangular iron piece was determined from the images captured using smartphone camera (Samsung Galaxy F62). The evidence for a total of eight different measurements is presented, and the accuracy of the method is proved up to 99 percent against the dimensions measured using the Vernier calliper.

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来源期刊

International Journal of Mathematical Engineering and Management Sciences Multiple-

CiteScore

3.80

自引率

6.20%

发文量

审稿时长

20 weeks

期刊介绍： IJMEMS is a peer reviewed international journal aiming on both the theoretical and practical aspects of mathematical, engineering and management sciences. The original, not-previously published, research manuscripts on topics such as the following (but not limited to) will be considered for publication: *Mathematical Sciences- applied mathematics and allied fields, operations research, mathematical statistics. *Engineering Sciences- computer science engineering, mechanical engineering, information technology engineering, civil engineering, aeronautical engineering, industrial engineering, systems engineering, reliability engineering, production engineering. *Management Sciences- engineering management, risk management, business models, supply chain management.