Research and Application of Structural Plane Identification for Roadway Surrounding Based on Deep Learning
Abstract
:1. Introduction
2. Methods
2.1. Surveying Approach
2.2. Borehole Image Preprocessing
2.3. Convolutional-Neural-Network–Based Model
2.4. Software Implementation
3. Case Study
3.1. Geological Conditions
3.2. Results
3.2.1. Vertical Roof Borehole
3.2.2. Inclined Borehole in Roof
3.3. Discussions
4. Conclusions
- Structural Plane Classification and Processioning: Borehole images from 30 coal mines were categorized into five distinct structural plane types based on morphological characteristics. Segmentation sampling and feature enhancement techniques were applied to preprocess the images, optimizing input data for deep learning models and reducing computational time. Additionally, color-coded annotations were implemented to differentiate between structural plane types during model training.
- Domain-Adaptive CNN Architecture: A Deep CORAL (Correlation Alignment) ar-chitecture, built upon a Convolutional CNN, was designed to classify unlabeled borehole images in target domains by leveraging labeled source domain data. Model training demonstrated a classification accuracy of 86% on target domain images, indicating robust generalization capabilities for structural plane recognition.
- Intelligent Recognition System Development: The Intelligent Recognition System for Surrounding Rock Fracture (IRSSRF) was developed using the Deep CORAL frame-work. This system incorporates five functional modules for automated fracture recognition, classification, and annotation in borehole images. Validation testing re-vealed structural plane recognition accuracy ranging from 0.76 to 1.0 across borehole test cases, meeting practical engineering requirements.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Xu, Q.; Xia, Z.; Huang, G.; Li, X.; Gao, X.; Fan, Y. Research and Application of Structural Plane Identification for Roadway Surrounding Based on Deep Learning. Appl. Sci. 2025, 15, 4756. https://doi.org/10.3390/app15094756
Xu Q, Xia Z, Huang G, Li X, Gao X, Fan Y. Research and Application of Structural Plane Identification for Roadway Surrounding Based on Deep Learning. Applied Sciences. 2025; 15(9):4756. https://doi.org/10.3390/app15094756
Chicago/Turabian StyleXu, Qiang, Ze Xia, Gang Huang, Xuehua Li, Xu Gao, and Yukuan Fan. 2025. "Research and Application of Structural Plane Identification for Roadway Surrounding Based on Deep Learning" Applied Sciences 15, no. 9: 4756. https://doi.org/10.3390/app15094756
APA StyleXu, Q., Xia, Z., Huang, G., Li, X., Gao, X., & Fan, Y. (2025). Research and Application of Structural Plane Identification for Roadway Surrounding Based on Deep Learning. Applied Sciences, 15(9), 4756. https://doi.org/10.3390/app15094756