A Defect Detection System for Lamp Cup Rivet Based on Machine Vision

2019 IEEE 16th International Conference on Networking, Sensing and Control (ICNSC) Pub Date : 2019-05-01 DOI:10.1109/ICNSC.2019.8743260

Zhiwei He, Canjun Jiang, Yuxiang Yang, Mingyu Gao, Zhongfei Yu

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引用次数: 1

Abstract

In order to improve the production efficiency of traditional industries and reduce production costs. This study designed a set of automatic detection system for lamp cup rivet defects based on the production characteristics of glass lamp cups of machine vision, which greatly improved the detection efficiency. The system uses high-definition industrial cameras, industry personal computer and servo driver to build a hardware platform, using Gaussian Filter, Thresholding method, Contour Extraction, Contour Screening and Least squares to fit the image processing technology, so the inclination degree of the lamp cup rivet and the depth of the groove are detected and analyzed. This study found that the detection of a single lamp cup took about 1s, and the accuracy of it was high. This system has been tested in factory. After a large number of product tests, the system is stable and reliable with high detection efficiency. The system not only meets the requirements of modern production, but also offers a greatly liberates of labor force.

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基于机器视觉的灯杯铆钉缺陷检测系统

为了提高传统行业的生产效率，降低生产成本。本研究根据机器视觉玻璃灯杯的生产特点，设计了一套灯杯铆钉缺陷自动检测系统，大大提高了检测效率。该系统以高清工业摄像机、工业个人计算机和伺服驱动器为硬件平台，采用高斯滤波、阈值法、轮廓提取、轮廓筛选和最小二乘拟合等图像处理技术，对灯杯铆钉的倾斜度和凹槽深度进行检测和分析。本研究发现，单个灯杯的检测时间约为15秒，且准确率较高。该系统已在工厂进行了测试。经过大量的产品测试，系统稳定可靠，检测效率高。该制度不仅满足了现代化生产的要求，而且极大地解放了劳动力。

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2019 IEEE 16th International Conference on Networking, Sensing and Control (ICNSC)

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