引用本文:张琦,张秀芬,蔚刚.基于图像三维重建的退役零件表面失效特征表征方法∗[J].中国表面工程,2021,34(3):149~158
Zhang Qi,Zhang Xiufen,Wei Gang.Methods of Surface Failure Characterization for Retired Parts Based on Image 3D Reconstruction[J].China Surface Engineering,2021,34(3):149~158
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基于图像三维重建的退役零件表面失效特征表征方法∗
张琦1,2, 张秀芬1,2, 蔚刚3
1.内蒙古工业大学机械工程学院 呼和浩特 010051;2.内蒙古自治区先进制造技术重点实验室 呼和浩特 010051;3.内蒙古机电职业技术学院 呼和浩特 010070
摘要:
退役零件的失效程度是判断其可再制造性的关键因素之一,为克服失效程度难以快速精确量化的问题,提出一种基于图像三维重建的退役零件失效特征表征方法。 针对失效特征重建精度要求高的特点,在由运动恢复形状( Shape from motion, SFM)算法的基础上提出一种自标定全局 SFM 三维点云重建算法,利用光束平差法优化相机焦距、径向畸变参数,实现了相机自标定,增加了全局 SFM 算法的鲁棒性;以重建有效三维点数量占比、点云完整度和相机位姿准确度为评价指标,构建了重建精度评价模型,实现了图像三维重建精度的量化评价;提出了退役零件表面失效特征量化方法和实施流程,并定义了失效特征信息计算公式;最后,以电梯导靴为例,对其表面磨损失效特征进行了量化表征。 试验结果表明,该方法可以有效地用于毫米级及以上的退役零件表面失效特征的快速量化表征。
关键词:  图像三维重建  由运动恢复形状 (SFM)  退役零件  失效特征表征  自标定
DOI：10.11933/j.issn.1007-9289.20210117001
分类号:TH17;TP24
基金项目:国家自然科学基金(51965049)、内蒙古自治区关键技术攻关计划(2020SGG2992)、内蒙古自治区高等学校科学研究项目(NJZY19272)和内蒙古机电职业技术学院科学研究项目(NJDZJZR1813)资助项目
Methods of Surface Failure Characterization for Retired Parts Based on Image 3D Reconstruction
Zhang Qi1,2, Zhang Xiufen1,2, Wei Gang3
1.Inner Mongolia University of Technology, College of Mechanical Engineering, Hohhot 010051 , China;2.Inner Mongolia Key Laboratory of Advanced Manufacturing Technology, Hohhot 010051 , China;3.Inner Mongolia Vocational College of Mechanical and Electrical Technology, Hohhot 010070 , China
Abstract:
The degree of failure is one of the key factors to determine the remanufacturability of retired parts. And the degree of failure is difficult to quantify quickly, which is a big chanllege. To address this problem, a surface failure characterization method for the retired parts was proposed based on image 3D reconstruction. Aiming at the high accuracy reguires of failure feature reconstruction, the 3D point cloud reconstruction algorithm-shape from motion( SFM) was studied and a self-calibration global SFM was proposed, and realized the camera self-calibration, the focal-length and radial distortion parameters of the camera were optimized by using the beam adjustment method, which increases the robustness of the global SFM algorithm. Taking the number proportion of effective 3D reconstruction points, the integrity of point cloud and the accuracy of camera pose as the evaluation indexes, an evaluation model of reconstruction accuracy was established to perform the quantitative evaluation of image 3D reconstruction accuracy. Furthermore, the quantitative method of retired parts surface failure characteristics was proposed and the calculation formula of the failure characteristics information was defined. Based on this, the implementation flow chart was presented. Finally, a case study of elevator guide boots was provided to verify the proposed method. And the experimental results show that it can be used effectively for the rapid quantification of surface failure characteristics of retired parts with millimeter grade and above.
Key words:  image 3D reconstruction  shape form motion (SFM)  retired parts  failure characterization  self-calibration
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