Underwater Structure Health Status Assessment Using Fractal Theory-Based Crack Detection Algorithm
Publication: Journal of Performance of Constructed Facilities
Volume 37, Issue 4
Abstract
Image processing-based health assessment of underwater concrete structures is a challenging task. The complex underwater environmental disturbances and serious image degradation significantly affect the accuracy of crack detection. To reduce the impact of these factors, an underwater concrete crack detection algorithm based on fractal theory [fractal underwater crack detection algorithm (F-UCD)] is proposed in this study. Meanwhile, a four-level structural assessment criterion is established to assist in underwater crack measurement and structural health assessment. To validate the optimal distance of the algorithm, four distances of , , , and are set. The results show that the F-UCD algorithm can effectively detect cracks in underwater concrete members within . The structural assessment standards based on fractal theory can be used to assist managers in determining the health condition of structures.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
The authors gratefully acknowledge the financial support provided by the Fujian Provincial Department of Science and Technology (Grant No.: 2021I0014) and the Xiamen Municipal Construction Bureau (Grant No.: XJK2022-1-7).
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Published In
Journal of Performance of Constructed Facilities
Volume 37 • Issue 4 • August 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Nov 15, 2022
Accepted: Feb 27, 2023
Published online: Apr 22, 2023
Published in print: Aug 1, 2023
Discussion open until: Sep 22, 2023
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