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转子铜排鱼尾槽尺寸的视觉检测评定算法

李尚君 吴龙 叶松涛 严思杰

李尚君, 吴龙, 叶松涛, 严思杰. 转子铜排鱼尾槽尺寸的视觉检测评定算法[J]. 机械科学与技术, 2017, 36(8): 1149-1154. doi: 10.13433/j.cnki.1003-8728.2017.0801
引用本文: 李尚君, 吴龙, 叶松涛, 严思杰. 转子铜排鱼尾槽尺寸的视觉检测评定算法[J]. 机械科学与技术, 2017, 36(8): 1149-1154. doi: 10.13433/j.cnki.1003-8728.2017.0801
Li Shangjun, Wu Long, Ye Songtao, Yan Sijie. Machine Vision Measurement Algorithm for Turbo Generator's Coil Strip[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(8): 1149-1154. doi: 10.13433/j.cnki.1003-8728.2017.0801
Citation: Li Shangjun, Wu Long, Ye Songtao, Yan Sijie. Machine Vision Measurement Algorithm for Turbo Generator's Coil Strip[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(8): 1149-1154. doi: 10.13433/j.cnki.1003-8728.2017.0801

转子铜排鱼尾槽尺寸的视觉检测评定算法

doi: 10.13433/j.cnki.1003-8728.2017.0801
基金项目: 

江苏省重点研发计划项目(BE2015005-1)与国家自然科学基金项目(51375196)资助

详细信息
    作者简介:

    李尚君(1991-),硕士研究生,研究方向为机械电子工程,shangjunlee@hust.edu.cn

    通讯作者:

    严思杰(联系要),教授,博士,sjyan@hust.edu.cn

Machine Vision Measurement Algorithm for Turbo Generator's Coil Strip

  • 摘要: 汽轮发电机转子铜排完成鱼尾槽铣削后需要进行严格的检测。由于传统的人工检测方法不可避免地带来错检或漏检,导致检测正确率(检正率)低下,本文中采用机器视觉系统对转子铜排两端鱼尾槽进行尺寸检测。首先,利用基于拉普拉斯变换改进的Otsu阈值分割方法,实现了目标边缘轮廓的精确定位;其次,结合使用移动最小二乘法(MLS)实现了亚像素轮廓的提取;最后,使用鱼尾槽样件对上述提出的算法进行了检测验证。实验结果表明,本文提出的方法可以满足铜排鱼尾槽在线检测要求,与传统方法相比,检测重复测量精度更高,重复测量精度平均提高50%以上。
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出版历程
  • 收稿日期:  2016-05-19
  • 刊出日期:  2017-08-05

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