Abstract: In order to improve the intelligentization level of surrounding rock classification in the construction stage and enhance the accuracy of intelligent rock classification, an intelligent rock classification method based on multivariate geological information and information fusion is proposed. An intelligent classification software system based on multivariate geological information is developed to realize automatic acquisition of multivariate geological information and automatic classification of surrounding rock for drill-and-blast tunnels. Based on tunnel projects in the western mountainous area of China, four types of multivariate geological information, including drilling parameters, highdefinition digital images of tunnel face, advance geological prediction information, and geological exploration information, are collected. Standardized and structured data processing and feature extraction are carried out. An intelligent classification model of surrounding rock based on multivariate geological information is constructed, and a web-end intelligent classification software system of surrounding rock based on multivariate geological information is developed for drill-and-blast tunnels. The accuracy of the intelligent classification model proposed in this study reached 95.45%, with an average accuracy of 95.05%, an average recall rate of 93.25%, and an average F₁ score of 94.14%. Field applications of the software system have been carried out for rock classification at 844 sections, which had a good performance on identifying unevenly distributed soft and hard rock or locally fractured rock.

Key words: drill-and-blast tunnel, multivariate geological information, surrounding rock classification, intelligent classification, image recognition, information fusion