孔祥玲, 付经伦. 基于计算机视觉的三维重建技术在燃气轮机行业的应用及展望[J]. 发电技术, 2021, 42(4): 454-463. DOI: 10.12096/j.2096-4528.pgt.21031
引用本文: 孔祥玲, 付经伦. 基于计算机视觉的三维重建技术在燃气轮机行业的应用及展望[J]. 发电技术, 2021, 42(4): 454-463. DOI: 10.12096/j.2096-4528.pgt.21031
KONG Xiangling, FU Jinglun. Computer-Vision Based on Three-dimensional Reconstruction Technology and Its Applications in Gas Turbine Industry[J]. Power Generation Technology, 2021, 42(4): 454-463. DOI: 10.12096/j.2096-4528.pgt.21031
Citation: KONG Xiangling, FU Jinglun. Computer-Vision Based on Three-dimensional Reconstruction Technology and Its Applications in Gas Turbine Industry[J]. Power Generation Technology, 2021, 42(4): 454-463. DOI: 10.12096/j.2096-4528.pgt.21031

基于计算机视觉的三维重建技术在燃气轮机行业的应用及展望

Computer-Vision Based on Three-dimensional Reconstruction Technology and Its Applications in Gas Turbine Industry

  • 摘要: 燃气轮机的整机性能及运行安全与其各部件的性能和工作状态密切相关,部件性能优劣和健康状态直接反映在表面的形貌上。因此,根据部件的形貌特征对其性能及健康状态进行判读,是评估燃机设计和健康状态的最为高效的方法,而三维重建技术是实现这一方法的关键技术。首先围绕基于计算机视觉的三维重建,系统地阐述了基于单目视觉、基于双目视觉及基于深度学习的三维重建技术及其发展现状;之后讨论了三维重建技术在燃气轮机行业的发展现状及可能的发展方向;最后,以燃气轮机透平叶片为对象,比较了基于阴影信息及多视图学习网络的三维重建效果并讨论了其各自的优缺点。

     

    Abstract: The operational safety and performance of gas turbine is closely related to the health status of its components. Generally, the status of gas turbine components can be evaluated by the morphological characters, such as size, shape, color, etc. Therefore, the method of feature extraction, especially the three- dimensional (3D) feature extraction, has become a key technology for component health status assessment. The existing computer vision based on 3D reconstruction algorithms was reviewed. After that, the research status and development directions of the 3D reconstruction in the gas turbine industry were discussed. In the end, the reconstruction results of a turbine blade using the shape from shading (SFS) algorithm and the Mvsnet were presented and compared.

     

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