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基于图像的螺栓松动检测使用克板视角校正方法

Chengqian Xie¹, Jun Luo¹, Kaili Li¹

¹School of Civil Engineering and Architecture, Chongqing University of Science and Technology, No. 20, East University Town Road, Shapingba District, Chongqing 401331, China.

Sensors (Basel, Switzerland)

|June 19, 2024

概括

这项研究引入了一种图像校正技术,用于使用棋盘图案来提高边接头螺栓的精度. 该方法提高了螺栓松动检测稳定性和准确性,即使更少的校正点.

科学领域:

工程工程师工程师工程师
计算机视觉计算机视觉
机械系统机械系统

背景情况:

接在机械系统中至关重要,螺栓的完整性对于结构安全至关重要.
由于图像扭曲和摄像头定位错误,精确的螺栓状态监控具有挑战性.

研究的目的:

开发和验证一个新的图像校正方法,用于接接头螺栓.
为了提高螺栓松动检测的稳定性和准确性.
分析各种因素对校正方法性能的影响.

主要方法:

用一个棋盘图案来识别侧边接头螺栓上的特征点.
使用多个特征点进行同谱矩阵估计,纠正图像视角扭曲和相机角度偏差.
分析包括特征点数,相机距离和光强度在内的因素.

主要成果:

提出的方法有效地纠正图像扭曲和相机位置角度偏差.
使用超过四个校正点显著提高了螺栓图像校正和螺栓松动检测的稳定性.
这种方法在只有九个棋盘点的情况下仍然有效,实现了平均螺栓松动检测误差低于1.5度.

结论:

开发的图像校正技术提供了一个强大的解决方案,用于接联接螺栓分析.
该方法在检测螺栓松动时表现出更好的稳定性和准确性.
摄像机最佳拍摄距离在20厘米至60厘米之间,对光强度的敏感性较低.

关键词:

螺栓松动松动螺栓松动摄像机的校准摄像机的校准国际象棋棋牌上的棋盘.边缘连接边缘连接边缘连接视角纠正视角纠正纠正

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