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

孔祥玲; 付经伦

doi:10.12096/j.2096-4528.pgt.21031

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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

智能涡轮发电技术 | 更新时间：2025-07-04

- 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
- 发电技术 2021年42卷第4期页码：454-463
- 作者机构：
  
  1.中国科学院工程热物理研究所南京未来能源系统研究院, 江苏省南京市 210000
  2.中国科学院工程热物理研究所先进燃气轮机实验室, 北京市海淀区 100190
  3.中国科学院大学, 北京市海淀区 100049
  4.中国科学院先进能源动力重点实验室, 北京市海淀区 100190
  5.中国科学院轻型动力创新研究院, 北京市海淀区 100190
- 作者简介：
  
  [ "孔祥玲(1984), 女, 博士, 副研究员, 从事机器人运动控制、机器视觉、最优化理论及应用、路径优化控制等方面的研究, kongxiangling@njiet.cn" ]
  [ "付经伦(1979), 女, 博士, 研究员, 研究方向为燃气轮机透平气动冷却设计及数字化, fujl@iet.cn" ]
- 基金信息：
  
  国家自然科学基金项目(51776201)
- DOI：10.12096/j.2096-4528.pgt.21031
  中图分类号： TK05
- 收稿：2021-04-25，
  
  纸质出版：2021-08-31
- 稿件说明：
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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.

Xiangling KONG, Jinglun FU. Computer-Vision Based on Three-dimensional Reconstruction Technology and Its Applications in Gas Turbine Industry[J]. Power Generation Technology, 2021, 42(4): 454-463.
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.

Xiangling KONG, Jinglun FU. 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.

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.

关键词

Keywords

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