Damage identification of railway bridge underwater foundations based on optical images
文献类型：期刊论文
| 作者 | Wang Jinchao4; Liu Houcheng5,6; Su Yongan2; Wang Feng3; Wang Baoliang1 |
| 刊名 | URBAN CLIMATE
 |
| 出版日期 | 2023-09-01 |
| 卷号 | 51页码:17 |
| 关键词 | Railway bridges Underwater foundation Damage detection Automatic identification Optical image |
| ISSN号 | 2212-0955 |
| DOI | 10.1016/j.uclim.2023.101662 |
| 英文摘要 | Diagnosing the health status of the underwater foundation of railway bridges is critical for railway environmental assessment. However, traditional underwater optical image detection technology suffers from image blurring. Thus, this paper develops an underwater foundation damage identification method for railway bridges based on optical images, which exploits the various underwater propagation characteristics of different light source wavelengths. This paper mainly reflects the differential characteristics of underwater basic damage images under different wavelength responses by constructing inter-spectral variance feature functions, local feature functions of images, and global feature functions of images. An optical image enhancement model that integrates different wavelength response features has been proposed to effectively enhance basic underwater optical images. An underwater basic damage area automatic recognition method has been developed that can accurately and efficiently extract the boundary contour of the damaged area. Based on combining field test data, the feasibility and effectiveness of this method were verified through comparative analysis with other methods. The results indicate that the damage identification ability of the method proposed in this paper is improved compared to traditional methods, which can effectively improve the quality of underwater optical images and improve the recognition accuracy of damaged areas. It is a new method of underwater damage identification based on optical image, which can provide more effective technical support for the health diagnosis of underwater railway bridges. |
| 资助项目 | Open Projects Foundation of State Key Laboratory for Health and Safety of Bridge Structures[BHSKL-20-05-GF] ; National Natural Science Foundation for the Youth of China[41902294] |
| WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:001129354500001 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/40346]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Wang Jinchao |
| 作者单位 | 1.Southwest Geotech & Design Inst China Nucl Ind, Chengdu 610052, Sichuan, Peoples R China 2.Yichang Water Conservancy & Hydropower Design Ins, Yichang 443100, Peoples R China 3.Ningxia Water Conservancy Ningxia Hui Autonomous, Yinchuan 750002, Ningxia, Peoples R China 4.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China 5.Wuhan Zhongke Kechuang Engn Testing Co Ltd, Wuhan 430071, Peoples R China 6.Chinese Acad Sci, Inst Rock & Soil Mech, Wuhan 430071, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang Jinchao,Liu Houcheng,Su Yongan,et al. Damage identification of railway bridge underwater foundations based on optical images[J]. URBAN CLIMATE,2023,51:17. |
| APA | Wang Jinchao,Liu Houcheng,Su Yongan,Wang Feng,&Wang Baoliang.(2023).Damage identification of railway bridge underwater foundations based on optical images.URBAN CLIMATE,51,17. |
| MLA | Wang Jinchao,et al."Damage identification of railway bridge underwater foundations based on optical images".URBAN CLIMATE 51(2023):17. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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