{"id":15,"date":"2023-11-09T05:37:54","date_gmt":"2023-11-09T05:37:54","guid":{"rendered":"https:\/\/ceshenghan.people.ust.hk\/?page_id=15"},"modified":"2025-12-04T13:39:09","modified_gmt":"2025-12-04T13:39:09","slug":"project-details","status":"publish","type":"page","link":"https:\/\/ceshenghan.people.ust.hk\/?page_id=15","title":{"rendered":"Project Details"},"content":{"rendered":"\n
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Projects<\/h1>\n\n\n\n
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Tile delamination detection on building fa\u00e7ades using drone infrared thermography<\/h2>\n\n\n\n

Source: ITF<\/strong><\/p>\n\n\n\n

In Hong Kong, most buildings approaching 30 years of service, tile delamination due to infrastructure deterioration is a significant concern. The goal of this project is to detect tile delamination on building facades using an infrared thermography-based method and UAV-captured IR images. To achieve this, a comprehensive database will be established through controlled delamination defect testing and on-site facade inspection. Additionally, a rapid defect identification algorithm will be developed based on machine learning. This project is expected to quickly detect delamination on infrastructure and buildings, in order to prevent falling objects from heights that could pose a danger to public safety.<\/p>\n\n\n\n

To address imperfect synchronization between the visual and IR cameras on commercial unmanned aerial vehicles, we developed a multimodal feature description network to register RGB\u2013IR image pairs. Code and dataset are available here<\/a>.<\/p>\n\n\n\n

To more effectively integrate RGB\u2013IR information and accommodate modality-specific characteristics (e.g., spalling is prominent in both modalities, whereas delamination is primarily visible in IR), we developed the Layered Bilateral Feature Fusion Network for efficient RGB\u2013IR fusion. The code<\/a> and dataset<\/a> are publicly available.<\/p>\n\n\n\n

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Collaborator: RaSpect<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Strain transfer mechanism of fiber optic sensors <\/h2>\n\n\n\n

Understanding the mechanical behavior of fiber optic deformation is critical for interpretation of distributed fiber optic sensing results. The project involves conducting experiments, numerical simulations, and analytical investigations to study the deformation fiber optic sensor behavior under different loading conditions and analyzing the results to understand the underlying mechanisms of strain transfer. The outcomes of the project will help to improve the accuracy and reliability of fiber optic sensors by providing insights into their deformation behavior and the factors that affect their performance. <\/p>\n\n\n\n

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Intelligent building monitoring with distributed fiber optic sensing <\/h2>\n\n\n\n

Distributed fiber optic sensing technology provides a unique opportunity to build the nervous system of for infrastructure. The project leverages the unique capabilities of fiber optic sensors to monitor various building parameters such as temperature, strain, and vibration, with high accuracy and reliability. The system is designed to provide early warning of potential issues, and to improve the building’s operational efficiency. This project has significant potential to contribute to the field of building monitoring and maintenance, and its outcomes could have a positive impact on the safety, sustainability, and longevity of buildings. <\/p>\n\n\n\n

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