WANGShou-zhi,LIU Zhang,WANGDong,et al.Defect Detection and Application of Urban Drainage Network Based on PP-YOLOE[J].China Water & Wastewater,2024,40(18):130-136.
Defect Detection and Application of Urban Drainage Network Based on PP-YOLOE
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第40卷
Number:
第18期
Page:
130-136
Column:
Date of publication:
2024-09-17
- Keywords:
- pipeline defect detection; CCTV detection; PP-YOLOE algorithm; Grounding DINO algorithm; 3D GIS
- Abstract:
- Due to the complex environment of urban drainage networks, regular maintenance is required. Relevant personnel need to check and judge each CCTV video of the pipeline network collected by the pipeline robot. In order to save labor costs, the object detection algorithm PP-YOLOE of deep learning is adopted to intelligently detect defect information in videos, and compared with the zero-sample detection algorithm of Grounding DINO. The test results show that detection precision, recall, and accuracy rate of the PP-YOLOE algorithm are 1.000, 0.875, and 0.944, respectively, which are significantlybetter than the Grounding DINO algorithm and are well suited for drainage network scenarios. Subsequently,images containing defect information are displayed on the three-dimensional GIS visualization management platform of the drainage network, making it easier for management personnel to intuitively grasp the defect situation and assist in providing decision-making support. The research results have been applied in the drainage network of a certain area in Heilongjiang Province, and have achieved good results.
Last Update:
2024-09-17