| 基于计算机视觉的钢轨扣件螺母缺失检测系统 |
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| 引用本文： | 王凌,张冰,陈锡爱. 基于计算机视觉的钢轨扣件螺母缺失检测系统[J]. 计算机工程与设计, 2011, 32(12): 4147-4150 |
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| 作者姓名： | 王凌 张冰 陈锡爱 |
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| 作者单位： | 中国计量学院机电工程学院,浙江杭州,310018 |
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| 基金项目： | 浙江省自然科学基金项目，浙江省教育厅基金项目 |
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| 摘 要： | 针对传统方法己经不能满足线路检修的需要,设计了一种基于计算机视觉的钢轨扣件螺母缺失检测系统,建立了钢轨扣件螺母缺失检测系统的系统框架,提出了一种基于特定区域像素点扫描统计的扣件定位算法,使用了主元分析法算法来提取扣件螺母特征向量,并利用最小距离分类器对扣件进行分类。实验结果表明,该系统能有效地自动识别钢轨扣件螺母是否缺失,能在一定程度上代替扣件系统螺母的人工巡检。
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| 关 键 词： | 计算机视觉 钢轨扣件 螺母缺失检测 主元分析法 最小距离分类器 像素点扫描 |
Inspection system for loss of rail fastening nut based on computer vision |
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| WANG Ling,ZHANG Bing,CHEN Xi-ai. Inspection system for loss of rail fastening nut based on computer vision[J]. Computer Engineering and Design, 2011, 32(12): 4147-4150 |
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| Authors: | WANG Ling ZHANG Bing CHEN Xi-ai |
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| Affiliation: | WANG Ling,ZHANG Bing,CHEN Xi-ai(College of Mechatronics Engineering,China Jiliang University,Hangzhou 310018,China) |
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| Abstract: | As the traditional visual inspection of bare eyes can no longer meet the railway maintenance requirements,this paper focuses on the computer-vision-based system for detecting rail fastening automatically.A framework of this system is developed,and an algorithm of positioning the rail fastening based on the scanning pixels and statistics of specific areas is proposed.The principal components analysis algorithm is used to obtain the eigenvectors of the fastening nut and the minimum distance classifier is used... |
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| Keywords: | computer vision rail fastening nut missing detection PCA minimum distance classifier scanning pixels |
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