数据采集与处理2025，Vol.40Issue(3)：675-685,11.DOI:10.16337/j.1004-9037.2025.03.009
基于深度学习的岩石钻孔全景图像识别
Panoramic Image Recognition of Rock Borehole Based on Deep Learning
摘要
Abstract
Geotechnical borehole monitoring,as one of the most common tunneling advanced detection techniques,can truly reflect the material properties,characteristics,and groundwater conditions of geomaterials,which is vital to ensure construction safety.Based on the characteristics of the geotechnical borehole monitoring objectives,a smart visual system based on panoramic cameras is developed.The system is suitable for close-range and dynamic high-resolution imaging of the inner walls of long geotechnical boreholes.Based on the improved EfficientNetV2 network and the sliding window prediction,the rapid intelligent recognition of eight types of rock borehole images is realized.Experimental results show that the visual system can meet the requirements for close-range high-resolution panoramic imaging of long boreholes and achieve intelligent state assessment of rock materials.The recognition success rate reaches 91.49%on the test set,and the system preliminarily possesses the comprehensive intelligent evaluation capability of geotechnical borehole status.关键词
钻孔监测/全景成像/EfficientNetV2网络/智能识别Key words
borehole monitoring/panoramic imaging/EfficientNetV2 network/intelligent recognition分类
计算机与自动化引用本文复制引用
先永利,陈学健,彭真明,汪杰,彭波..基于深度学习的岩石钻孔全景图像识别[J].数据采集与处理,2025,40(3):675-685,11.基金项目
国家自然科学基金(62205342) （62205342）
四川省自然科学基金(2025ZNSFSC0522) （2025ZNSFSC0522）
特种环境机器人技术四川省重点实验室开放基金(22kftk03). （22kftk03）
