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一种基于视觉技术的新型防松螺栓连接松动诊断方法。

A novel anti-loosening bolt looseness diagnosis of bolt connections using a vision-based technique.

作者信息

Luo Jun, Li Kaili, Xie ChengQian, 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, China.

出版信息

Sci Rep. 2024 May 20;14(1):11441. doi: 10.1038/s41598-024-62560-8.

DOI:10.1038/s41598-024-62560-8
PMID:38769375
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11106340/
Abstract

Bolt looseness detection is a common problem in engineering. Most vision-based detection techniques focus on diagnosing ordinary bolt looseness, i.e., the methods used for diagnosis are based only on the sidelines of nuts. These methods cannot be used for anti-loosening bolt looseness diagnosis because of the simultaneous rotation of screws and nuts. Therefore, a novel anti-loosening bolt looseness diagnosis method based on a vision-based technique is proposed in this paper. First, a regular hexagonal cap was installed on the screw, which can be used as a reference for the nut. Then, to automatically distinguish the hexagonal borders of the screw cap and nut, a new hexagonal border reconstruction algorithm is proposed. Furthermore, the relative rotation angles of the screw cap and nut hexagons can be determined using the sidelines of the reconstructed hexagonal borders of the screw cap and nut. Finally, a novel anti-loosening bolt looseness diagnosis method is established by using the relative rotation angle of the regular hexagonal borders of the screw cap and nut under initial status and loose status. A prototype flange node of the transmission tower was used for experimental verification. The results show that the proposed method can effectively detect the loosening angle of anti-loosening bolts.

摘要

螺栓松动检测是工程领域中的常见问题。大多数基于视觉的检测技术专注于诊断普通螺栓的松动情况,即所采用的诊断方法仅基于螺母的边缘。由于螺杆和螺母同时旋转,这些方法无法用于防松螺栓松动的诊断。因此,本文提出了一种基于视觉技术的新型防松螺栓松动诊断方法。首先,在螺杆上安装一个正六边形帽,其可作为螺母的参考。然后,为了自动区分螺帽和螺母的六边形边界,提出了一种新的六边形边界重建算法。此外,利用重建后的螺帽和螺母六边形边界的边缘,可以确定螺帽和螺母六边形的相对旋转角度。最后,通过使用螺帽和螺母在初始状态和松动状态下正六边形边界的相对旋转角度,建立了一种新型的防松螺栓松动诊断方法。使用输电塔的原型法兰节点进行了实验验证。结果表明,所提出的方法能够有效地检测防松螺栓的松动角度。

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本文引用的文献

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Sensors (Basel). 2018 Mar 28;18(4):1000. doi: 10.3390/s18041000.
2
A computational approach to edge detection.一种基于计算的边缘检测方法。
IEEE Trans Pattern Anal Mach Intell. 1986 Jun;8(6):679-98.