Seismic and Corrosion Damage Detection of Reinforced Concrete Structures Based on Deep Transfer Learning
Reinforced concrete buildings often suffer greater damage than expected during earthquakes,and corrosion of steel bars and other damages caused by corrosion are also widely encountered in relatively older structures that have not received sufficient engineering services.In post earthquake damage detection,it is important to determine the cause of damage in a realistic manner,plan future intervention measures for buildings correctly,and accurately determine the financial plan for the required intervention measures.In this sense,it is necessary to activate intelligent systems to accelerate the decision-making process of technical personnel participating in on-site damage assessment investigations after earthquakes.Based on this motivation,this study developed a deep transfer learning algorithm that can distinguish between corrosion damage and seismic damage in reinforced concrete building structural components.
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