A Method for Determining Integrity Degree of Tunnel Surrounding Rock Based on MobileNet

Authors

LIU Houxiang, School of Civil and Environmental Engineering ,Changsha University of Science & Technology, Changsha, Hunan 410114, ChinaFollow
YANG Caixia, School of Civil and Environmental Engineering ,Changsha University of Science & Technology, Changsha, Hunan 410114, ChinaFollow

Corresponding Author

杨彩霞, 女, 硕士研究生. E-mail: 21102020405@stu.csust.edu.cn

Abstract

To determine the integrity degree of tunnel surrounding rock more efficiently,a precise determination method for the integrity degree of tunnel surrounding rock based on the lightweight neural network MobileNet-v 2 was proposed.Firstly,the image was grayscaled and denoised,and the edges of cracks were detected.Then,the lightweight neural network MobileNet-v 2 model was pre-trained on the ImageNet dataset,and combined with transfer learning to complete data detection on the training,validation,and testing sets.Finally,a comparative experiment was conducted with traditional neural networks RestNet- 50 and VGG 16.By identifying the area,width,and length of cracks,the crack ratio Ks was introduced as an indicator to evaluate the integrity of the surrounding rock.The results show that:① in terms of accuracy,loss value,and training time,the MobileNet-v 2 model is significantly better than the VGG 16 and RestNet- 50 models;② the MobileNet-v 2 model has the highest accuracy,with a validation set accuracy of around 94%;③ by comparing with the results of on-site experiments,it is proven that using digital image processing methods to evaluate the integrity of rock masses has high accuracy and feasibility.

Publication Date

12-24-2025

DOI

10.14048/j.issn.1671-2579.2025.06.026

First Page

227

Last Page

233

Submission Date

December 2025

Recommended Citation

Houxiang, LIU and Caixia, YANG (2025) "A Method for Determining Integrity Degree of Tunnel Surrounding Rock Based on MobileNet," Journal of China & Foreign Highway: Vol. 45: Iss. 6, Article 26.
DOI: 10.14048/j.issn.1671-2579.2025.06.026
Available at: https://zwgl1980.csust.edu.cn/journal/vol45/iss6/26

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