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首页>《中国测试》期刊>本期导读>面向机箱标准件装配质量局部特征的智能检测技术

面向机箱标准件装配质量局部特征的智能检测技术

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作者:何彬媛1, 黄坚1, 刘桂雄1, 林镇秋2

作者单位:1. 华南理工大学机械与汽车工程学院, 广东 广州 510640;
2. 广州市华颉电子科技有限公司, 广东 广州 510663


关键词:标准件装配质量;检测模板;局部特征检测;智能检测


摘要:

标准件装配质量包含零件类型、位置偏差、姿态偏差等多个指标,还具有部位多、类型复杂的特点,该文提出基于装配局部特征的检测模板结合机器视觉的产品装配质量智能检测方案。首先,分析鉴别产品质量需从类型、位置、角度方面进行检测,还须结合装配公差要求,研究标准件局部特征检测方法;其次,通过标准件局部特征检测对装配部件进行快速准确定位、利用数学模型进行鉴别,结合SURF算法确定主方向及特征点,实现标准件装配质量的快速智能检测;最后,构建机箱标准件装配质量检测装置,对多个不同型号ADLINK嵌入式机箱进行试验。结果表明:与全局检测相比,使用标准件装配质量的局部特征智能检测技术,检测时间可缩短86.31%,实现零漏检,识别正确率达100%。


Intelligent detection technology for local characteristics of chassis standard component assembly quality
HE Binyuan1, HUANG Jian1, LIU Guixiong1, LIN Zhenqiu2
1. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China;
2. Guangzhou Hua Jie Electronic Technology Co., Ltd., Guangzhou 510663, China
Abstract: The assembly quality of standard components includes many types of parts, position deviation, attitude deviation, etc. It also has many features and complex types. The intelligent detection scheme of product assembly quality based on the detection template of assembly local features combined with machine vision is proposed. Firstly, the analysis and identification of product quality should be tested in terms of type, position and angle. It is also necessary to study the local feature detection method of standard components in combination with assembly tolerance requirements. Secondly, the assembly parts can be quickly and accurately positioned and utilized by the local feature detection of standard components. The model is identified, combined with the SURF algorithm to determine the main direction and feature points, to achieve rapid intelligent detection of standard component assembly quality. Finally, the chassis standard component assembly quality inspection device is constructed, and several different models of ADLINK embedded chassis are tested. The results show that compared with the global detection, the detection time can be shortened by 86.31% and the recognition accuracy rate is 100% using the local feature intelligent detection technology of the standard component assembly quality, and every standard component is detected.
Keywords: standard component assembly quality;detection template;partial image detection;intelligent detection
2019, 45(3):18-23  收稿日期: 2018-08-22;收到修改稿日期: 2018-09-29
基金项目: 广州市科技计划项目(2018020300006)
作者简介: 何彬媛(1995-),女,广西贺州市人,硕士研究生,专业方向为精密检测与仪器仪表
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