Intelligent detection of bonding status in external building insulation layers using ground-penetrating radar

Abstract

The bonding status of external building insulation layer is crucial for thermal insulation and long-term safety, but existing detection methods lack efficiency and accuracy. This paper explores the use of Ground-Penetrating Radar (GPR) technology for accurately estimating bonding areas and precisely identifying top and subgrade debonding defects in external building insulation layers. It proposes an end-to-end intelligent detection method based on GPR, incorporating a multi-task branch network that automatically selects C-scan depth slices for semantic segmentation to estimate bonding areas and utilizes B-scan slices for target detection of debonding defects. Results show that area estimation’s relative error is 0.70%, debonding detection accuracy reaches 78.45%, and the model performs well in complex scenarios. This paper provides the application of GPR in building inspection, promoting hazard discovery and technological advancement. Future work will focus on improving clutter suppression algorithms and C-scan depth slice extraction methods to further enhance detection results.