基于光度立体视觉三维重构算法的微观磨损形貌原位测量原理及方法

doi:10.3901/JME.2021.10.001

机械工程学报 ›› 2021, Vol. 57 ›› Issue (10): 1-9.doi: 10.3901/JME.2021.10.001

• 仪器科学与技术 • 下一篇

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基于光度立体视觉三维重构算法的微观磨损形貌原位测量原理及方法

朱可¹, 霍彦文¹, 武通海¹, 陈志雄²

1. 西安交通大学现代设计及转子轴承系统教育部重点实验室西安 710049;
2. 上海工程技术大学航空运输学院上海 201620

收稿日期:2020-07-22 修回日期:2021-01-28 出版日期:2021-05-20 发布日期:2021-07-23
通讯作者: 武通海(通信作者),男,1976年出生,教授,博士研究生导师。主要研究方向为监测大数据的人工智能、显微图像3D测量技术、嵌入式油液传感技术、装备PHM方法及应用。E-mail:wt-h@163.com
作者简介:朱可,男,1996年出生。主要研究方向为显微图像3D测量技术。E-mail:zhukecn@163.com
基金资助:
国家重点研发计划（2018YFB1306100）和国家自然科学基金（51675403）资助项目。

Principle and Method for In-situ Measurement of Micro-scale Worn Surface Morphology Based on 3D Reconstruction with Photometric Stereo Vision Algorithm

ZHU Ke¹, HUO Yanwen¹, WU Tonghai¹, CHEN Zhixiong²

1. Key Laboratory of Education Ministry for Modern Design & Rotor-Bearing System, Xi'an Jiaotong University, Xi'an 710049;
2. School of Air Transportation, Shanghai University of Engineering Science, Shanghai 201620

Received:2020-07-22 Revised:2021-01-28 Online:2021-05-20 Published:2021-07-23

摘要/Abstract

摘要： 基于图像的表面微观磨损形貌分析在磨损机理及状态分析中具有重要的地位，三维显微成像技术的应用已经将二维磨损形貌图像分析拓展到更丰富的三维分析领域。然而，从设备维护及故障监测的角度，在机或原位测量显然比上述先进测量更具吸引力，并且复杂、昂贵的先进表面测量技术至今无法打破其在机或原位测量的壁垒。针对现场检测与三维分析的需求，将光度立体视觉原理引入至微观磨损形貌的原位测量，借助便携式平面图像采集系统进行光学设计，提出一种采用多阴影平面图像的三维表面重构方法。首先，通过张正友标定法实现空间点由图像坐标系到相机坐标系的转换；然后，基于成像系统建立近场点光源模型，并由光度立体视觉算法求解表面法向量；最后，基于FC算法计算表面深度与高度信息，完成磨损表面微观形貌三维重构。基于上述方法，研制便携式图像采集与三维重构系统，分别对平面和曲面两类表面进行检测试验，并与共聚焦显微镜测量结果进行对比。测量与对比结果表明，截面曲线上特征点之间的高度差误差小于4.2%，截面二维参数误差小于10.9%，三维表面参数误差小于12.9%。上述工作表明，所提出的方法为机械设备部件磨损表面原位测量与分析提供有效的技术手段。

关键词: 磨损表面形貌, 原位测量, 三维重构图像, 光度立体视觉, 微观形貌

Abstract: Image-based micro-wear morphology analysis plays important role in both wear mechanism and wear state analysis. This technique has been improved from 2D analysis to 3D analysis with the application of 3D microscopic imaging technology. However, for the maintenance and fault monitoring of equipment, the on-machine or in-situ measurement are more attractive than the advanced measurements described above. The reason lies in the fact that these expensive and advanced techniques still find their barriers in the application of in-machine or in-situ measurements. Aiming at this pain point, a new method based on the photometric stereo vision is introduced for the on-site and three-dimensional analysis of microscopic worn morphology. With a portable 2D image acquisition system, a 3D reconstruction method is constructed using multi-shadow 2D images. First, the calibration method is applied to perform the coordinate transform of the spatial points from the image coordinate to the camera coordinate. Second, the near-field point light source model is established and the surface 3D normal vector for each points is obtained using the photometric stereo vision algorithm. Finally, the surface depth and height for each points are calculated based on the FC algorithm, so far the 3D reconstruction of the wear surface micro-morphology is accomplished. Based on the above methods, a portable image acquisition system is developed to detect the plane and the curved surface respectively. Compared with the results of the laser scanning confocal microscopy, the current method shows acceptable precision with the height error of the feature points less than 4.2%, the cross-section curve error less than 10.9%, and the 3D surface error less than 12.9%. It can be generalized from above works that an effective technical means for in-situ and 3D analysis of worn surface of mechanical components.

Key words: worn surface morphology, in-situ measurement, 3D reconstruction image, photometric stereo vision, micro-scale morphology

中图分类号:

TH117

朱可, 霍彦文, 武通海, 陈志雄. 基于光度立体视觉三维重构算法的微观磨损形貌原位测量原理及方法[J]. 机械工程学报, 2021, 57(10): 1-9.

ZHU Ke, HUO Yanwen, WU Tonghai, CHEN Zhixiong. Principle and Method for In-situ Measurement of Micro-scale Worn Surface Morphology Based on 3D Reconstruction with Photometric Stereo Vision Algorithm[J]. Journal of Mechanical Engineering, 2021, 57(10): 1-9.

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基于光度立体视觉三维重构算法的微观磨损形貌原位测量原理及方法

Principle and Method for In-situ Measurement of Micro-scale Worn Surface Morphology Based on 3D Reconstruction with Photometric Stereo Vision Algorithm

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