基于计算机视觉的皮革收缩温度中位移检测的研究
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摘要
在皮革工业中,皮革收缩温度这一重要指标的检测,对其加工工艺的制定有着重要的指导意义。本文针对皮革收缩温度测定仪中皮样收缩微小位移实时准确检测中用霍尔传感器存在的一些问题进行了研究;并基于计算机视觉技术,结合光学器件实现非接触式检测,完成微小位移量的高精度实时测量,检测精度达到0.01 mm,为高性价比皮革收缩温度检测仪的研制和生产提出了尝试。
In the leather industry,the detection of material performance parameters has an important guiding significance for the formulation of its processing technology.The shrinkage temperature of leather,an important index,is characterized by the small displacement produced at the beginning of shrinkage deformation during heating.The definition of starting shrinkage in the national standard is quantified as the corresponding moment of producing 0.15 mm micro-deformation(displacement).In this paper,the bottleneck of real-time and accurate detection of skin sample shrinkage micro-displacement in leather shrinkage temperature tester is effectively studied.Based on computer vision technology and optical devices,non-contact detection is realized,so that high-precision real-time measurement of micro-displacement can be completed.The detection accuracy reaches 0.01 mm,which is a high performance-price ratio.Technical support is provided for the development and production of leather shrinkage temperature detector.
In the leather industry,the detection of material performance parameters has an important guiding significance for the formulation of its processing technology.The shrinkage temperature of leather,an important index,is characterized by the small displacement produced at the beginning of shrinkage deformation during heating.The definition of starting shrinkage in the national standard is quantified as the corresponding moment of producing 0.15 mm micro-deformation(displacement).In this paper,the bottleneck of real-time and accurate detection of skin sample shrinkage micro-displacement in leather shrinkage temperature tester is effectively studied.Based on computer vision technology and optical devices,non-contact detection is realized,so that high-precision real-time measurement of micro-displacement can be completed.The detection accuracy reaches 0.01 mm,which is a high performance-price ratio.Technical support is provided for the development and production of leather shrinkage temperature detector.
引文
[1]Q B/T 1271-2012,毛皮-物理和机械试验-收缩温度的测定[S].北京:中国标准出版社,2012.
[2]赵妮娜.皮革收缩温度测量仪的研制[D].西安:陕西科技大学,2010.
[3]薛峰,郭萍.计算机视觉检测技术的发展及应用研究[J].通信电源技术,2016,33(6):133-134.
[4]刘曙光,刘明远,何钺.机器视觉及其应用[J].河北科技大学学报,2000,55(4):11-15,26.
[5]陈苏,陈国兴,韩晓健等.基于计算机视觉的位移测试方法研究与实现[J].振动与冲击,2015,34(18):71-76.
[6]宁铎,石秉恒,吕斌等.基于神经网络提高皮革收缩温度测量精度的研究[J].中国皮革,2013,42(21):29-33.
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[9]卢瑜,郝兴文,王永俊.Moravec和Harris角点检测方法比较研究[J].计算机技术与发展,2011,21(6):95-100.
[10]郭晨曦.基于Harris角点检测算法的图像拼接技术的研究与应用[D].西安:西安科技大学,2016.
[11]卢英,王慧琴,佟威等.基于Harris-张正友平面标定法的摄像机标定算法[J].西安建筑科技大学学报,2014,46(6):860-864.
[12]赵永志,彭国华.一种有效的图像二值化方法[J].科学技术与工程,2007,7(1):139-141,144.
[13]谢季峰.基于霍夫变换的划痕检测算法应用[J].电脑知识与技术,2012,8(20):4957-4958,4961.
[14]李礁.基于色彩矩阵优化的自适应阈值算法[J].信息系统工程,2011(8):43-44.
[15]曹兵,李文博,张云波.基于改进Harris角点算法的摄像机标定技术研究[J].计算机测量与控制,2016,24(5):213-215,219.
[16]段峰,王耀南,雷晓峰等.机器视觉技术及其应用综述[J]自动化博览.2002.(12):59-67.
[17]刘占.基于局部期望阈值分割的图像边缘检测算法[J].计算机与现代化.2016.(8):52-56.
[2]赵妮娜.皮革收缩温度测量仪的研制[D].西安:陕西科技大学,2010.
[3]薛峰,郭萍.计算机视觉检测技术的发展及应用研究[J].通信电源技术,2016,33(6):133-134.
[4]刘曙光,刘明远,何钺.机器视觉及其应用[J].河北科技大学学报,2000,55(4):11-15,26.
[5]陈苏,陈国兴,韩晓健等.基于计算机视觉的位移测试方法研究与实现[J].振动与冲击,2015,34(18):71-76.
[6]宁铎,石秉恒,吕斌等.基于神经网络提高皮革收缩温度测量精度的研究[J].中国皮革,2013,42(21):29-33.
[7]符耀庆,刘换来.基于.NET平台的岩屑图像灰度化方法研究与实现[J].硅谷,2013(1):73-109.
[8]谢凤英.数字图像处理及应用[M].北京:电子工业出版社,2014.
[9]卢瑜,郝兴文,王永俊.Moravec和Harris角点检测方法比较研究[J].计算机技术与发展,2011,21(6):95-100.
[10]郭晨曦.基于Harris角点检测算法的图像拼接技术的研究与应用[D].西安:西安科技大学,2016.
[11]卢英,王慧琴,佟威等.基于Harris-张正友平面标定法的摄像机标定算法[J].西安建筑科技大学学报,2014,46(6):860-864.
[12]赵永志,彭国华.一种有效的图像二值化方法[J].科学技术与工程,2007,7(1):139-141,144.
[13]谢季峰.基于霍夫变换的划痕检测算法应用[J].电脑知识与技术,2012,8(20):4957-4958,4961.
[14]李礁.基于色彩矩阵优化的自适应阈值算法[J].信息系统工程,2011(8):43-44.
[15]曹兵,李文博,张云波.基于改进Harris角点算法的摄像机标定技术研究[J].计算机测量与控制,2016,24(5):213-215,219.
[16]段峰,王耀南,雷晓峰等.机器视觉技术及其应用综述[J]自动化博览.2002.(12):59-67.
[17]刘占.基于局部期望阈值分割的图像边缘检测算法[J].计算机与现代化.2016.(8):52-56.