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基于数字边缘投影的铁路扣件夹紧力估算算法。

Digital Fringe Projection-Based Clamping Force Estimation Algorithm for Railway Fasteners.

机构信息

School of Instrument and Electronics, North University of China, Taiyuan 030051, China.

出版信息

Sensors (Basel). 2023 Mar 21;23(6):3299. doi: 10.3390/s23063299.

DOI:10.3390/s23063299
PMID:36992010
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10051881/
Abstract

The inspection of railway fasteners to assess their clamping force can be used to evaluate the looseness of the fasteners and improve railway safety. Although there are various methods for inspecting railway fasteners, there is still a need for non-contact, fast inspection without installing additional devices on fasteners. In this study, a system that uses digital fringe projection technology to measure the 3D topography of the fastener was developed. This system inspects the looseness through a series of algorithms, including point cloud denoising, coarse registration based on fast point feature histograms (FPFH) features, fine registration based on the iterative closest point (ICP) algorithm, specific region selection, kernel density estimation, and ridge regression. Unlike the previous inspection technology, which can only measure the geometric parameters of fasteners to characterize the tightness, this system can directly estimate the tightening torque and the bolt clamping force. Experiments on WJ-8 fasteners showed a root mean square error of 9.272 N·m and 1.94 kN for the tightening torque and clamping force, demonstrating that the system is sufficiently precise to replace manual measurement and can substantially improve inspection efficiency while evaluating railway fastener looseness.

摘要

检测铁路紧固件的夹紧力,可用于评估紧固件的松动情况,提高铁路安全性。虽然有各种检测铁路紧固件的方法,但仍需要在不安装附加装置的情况下,实现非接触、快速的检测。在本研究中,开发了一种使用数字条纹投影技术测量紧固件三维形貌的系统。该系统通过一系列算法进行松动检测,包括点云去噪、基于快速点特征直方图 (FPFH) 特征的粗配准、基于迭代最近点 (ICP) 算法的精配准、特定区域选择、核密度估计和脊回归。与之前只能测量紧固件几何参数来表征紧固程度的检测技术不同,该系统可以直接估计拧紧扭矩和螺栓夹紧力。在 WJ-8 紧固件上的实验表明,拧紧扭矩和夹紧力的均方根误差分别为 9.272 N·m 和 1.94 kN,表明该系统足够精确,可以替代手动测量,在评估铁路紧固件松动的同时,显著提高检测效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322c/10051881/7598d451f715/sensors-23-03299-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322c/10051881/e52d4db17339/sensors-23-03299-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322c/10051881/7598d451f715/sensors-23-03299-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322c/10051881/c28f17934bfa/sensors-23-03299-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322c/10051881/bd85d02f1494/sensors-23-03299-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322c/10051881/324e1de45ba6/sensors-23-03299-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322c/10051881/82e479d6d9ac/sensors-23-03299-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322c/10051881/e52d4db17339/sensors-23-03299-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/322c/10051881/7598d451f715/sensors-23-03299-g011.jpg

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本文引用的文献

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Dynamic Point Cloud Denoising via Manifold-to-Manifold Distance.基于流形到流形距离的动态点云去噪
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A Review of Bolt Tightening Force Measurement and Loosening Detection.螺栓拧紧力测量与松动检测综述
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Sensors (Basel). 2018 Oct 29;18(11):3675. doi: 10.3390/s18113675.
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