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作 者:Gang ZHAO Jingyu HU Wenlei XIAO Jie ZOU
机构地区:[1]School of Mechanical Engineering and Automation,Beihang University,Beijing 100191,China [2]MIIT Key Laboratory oj Aeronautics Intelligent Manufacturing,Beihang University,Beijing 100191,China
出 处:《Chinese Journal of Aeronautics》2021年第12期214-226,共13页中国航空学报(英文版)
基 金:supported by the Civil Airplane Technology Development Program。
摘 要:In the aviation industry,cable bracket is one of the most common parts.The traditional assembly state inspection method of cable bracket is to manually compare by viewing 3 D models.The purpose of this paper is to address the problem of inefficiency of traditional inspection method.In order to solve the problem that machine learning algorithm requires large dataset and manually labeling of dataset is a laborious and time-consuming task,a simulation platform is developed to automatically generate synthetic realistic brackets images with pixel-level annotations based on 3 D digital mock-up.In order to obtain accurate shapes of brackets from 2 D image,a brackets recognizer based on Mask R-CNN is trained.In addition,a semi-automatic cable bracket inspection method is proposed.With this method,the inspector can easily obtain the inspection result only by taking a picture with a portable device,such as augmented reality(AR)glasses.The inspection task will be automatically executed via bracket recognition and matching.The experimental result shows that the proposed method for automatically labeling dataset is valid and the proposed cable bracket inspection method can effectively inspect cable bracket in the aircraft.Finally,a prototype system based on client-server framework has been developed for validation purpose.
关 键 词:Aircraft assembly Augmented reality Cable bracket Mask R-CNN Synthetic dataset Template matching Visual inspection
分 类 号:V262.4[航空宇航科学与技术—航空宇航制造工程] TP391.41[自动化与计算机技术—计算机应用技术]
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