摘要
桥吊摆角的准确测量是实现吊车防摇控制的前提条件;文中将视觉识别技术引入到吊车防摆控制中来,提出了基于局部梯度变化和标准差的图像自适应增强处理算法,解决了不同背光条件下吊绳摆动位置信息获取问题,有效地实现了桥吊负载摆绳图像特征的提取;同时,采用两次下采样和梯度法相结合的圆心的识别算法,解决了圆检测的实时性问题,从而成功识别出目标及其所在的空间位置,并用几何方法准确地测量出负载钢丝绳的摆角;最后,实验结果证实了该方法的有效性。
The key point to clearing out overhead crane＇ s swaying is the accurate measurement of the angle.The thesis introduces vision technique into the anti-swaying control over the crane.The adaptive image enhancement method based on local gradient and standard deviation is proposed to solve the problem of acquiring the rope＇ s swaying position under different backlight conditions.It extracts the image features effectively.Meanwhile,twice down--sampling algorithm combined with gradient algorithm is introduced in this paper to identify the goal and its location;and it satisfies the real-time performance.Then,we use the geometric method to guarantee the measuring accuracy of the angle.The performance of the proposed method is verified by the experimental results.
出处
《计算机测量与控制》
2015年第7期2263-2265,2269,共4页
Computer Measurement &Control
基金
交通部应用基础项目(主干学科)(2013329810190)
上海市自然科学基金(13ZR1418800)
上海海事大学科研基金(20130456)的资助
关键词
桥吊
图像增强
两次下采样
梯度法
overhead crane
local gradient
backlight condition
