Automated detection and quantification of pavement cracking around manhole

Abstract

Damage detection plays an important role in pavement health monitoring and inspection. Unfortunately, research about damage detection of the special component of pavement structures, such as pavement manhole covers, is relatively few. A new pipeline for the detection and quantification of damage around the pavement manhole covers is proposed in this research. In this pipeline, the Attention-enhanced Manhole Detection Model (AMDM) is proposed to detect manhole covers. AMDM achieves an ideal balance between accuracy and speed by eliminating redundant structures and incorporating an attention mechanism. The BCSM (Boundary-enhanced Crack Segmentation Model) is proposed to segment the damage around the manhole cover, and the boundary loss function is used to enhance the fine segmentation ability of the model on the boundary. The MAP (Mean Average Precision) of the manhole covers detection model is 96.68%, and the MIOU (Mean Intersection Over Union) of the crack segmentation model is 89.73%. Attributing to this efficient and accurate pipeline, a reasonable damage evaluation method is proposed in the end, which is based on statistical data and engineering experience. Overall, not only this research will contribute an automatic and cost-effective method to the detection and evaluation of damage around the manhole cover, but also inspire the detection and evaluation of other special components of civil engineering structures.