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基于棋盘格透视校正法的基于图像的螺栓松动检测

Image-Based Bolt-Loosening Detection Using a Checkerboard Perspective Correction Method.

作者信息

Xie Chengqian, Luo Jun, Li Kaili, Yan Zhitao, Li Feng, Jia Xiaogang, Wang Yuanlai

机构信息

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

Chongqing Urban Investment Infrastructure Construction Co., Ltd., Chongqing 400015, China.

出版信息

Sensors (Basel). 2024 May 21;24(11):3271. doi: 10.3390/s24113271.

DOI:10.3390/s24113271
PMID:38894066
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11174449/
Abstract

In this paper, a new image-correction method for flange joint bolts is proposed. A checkerboard is arranged on the side of a flange node bolt, and the homography matrix can be estimated using more than four feature points, which include the checkerboard corner points. Then, the perspective distortion of the captured image and the deviation of the camera position angle are corrected using the estimated homography matrix. Due to the use of more feature points, the stability of homography matrix identification is effectively improved. Simultaneously, the influence of the number of feature points, camera lens distance, and light intensities are analyzed. Finally, based on a bolt image taken using an iPhone 12, the prototype structure of the flange joint in the laboratory is verified. The results show that the proposed method can effectively correct image distortion and camera position angle deviation. The use of more than four correction points not only effectively improves the stability of bolt image correction but also improves the stability and accuracy of bolt-loosening detection. The analysis of influencing factors shows that the proposed method is still effective when the number of checkerboard correction points is reduced to nine, and the average error of the bolt-loosening detection result is less than 1.5 degrees. Moreover, the recommended camera shooting distance range is 20 cm to 60 cm, and the method exhibits low sensitivity to light intensity.

摘要

本文提出了一种用于法兰连接螺栓的新型图像校正方法。在法兰节点螺栓一侧布置棋盘格，利用包括棋盘格角点在内的四个以上特征点估计单应性矩阵。然后，利用估计出的单应性矩阵校正采集图像的透视畸变和相机位置角度偏差。由于使用了更多特征点，有效提高了单应性矩阵识别的稳定性。同时，分析了特征点数量、相机镜头距离和光强的影响。最后，基于用iPhone 12拍摄的螺栓图像，对实验室中法兰连接的原型结构进行了验证。结果表明，该方法能有效校正图像畸变和相机位置角度偏差。使用四个以上校正点不仅有效提高了螺栓图像校正的稳定性，还提高了螺栓松动检测的稳定性和准确性。影响因素分析表明，当棋盘格校正点数量减少到九个时，该方法仍然有效，螺栓松动检测结果的平均误差小于1.5度。此外，推荐的相机拍摄距离范围为20 cm至60 cm，该方法对光强的敏感性较低。

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