Related Experiment Video
Updated: Jan 13, 2026
08:27
Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
Published on: January 5, 2024
1.6K
Intelligent Identification of Micro-NPR Bolt Shear Deformation Based on Modular Convolutional Neural Network
Guang Han1,2,3, Chen Shang1,2, Zhigang Tao3
1Hebei Provincial Collaborative Innovation Center of Transportation Power Grid Intelligent Integration Technology and Equipment, Shijiazhuang Tiedao University, Shijiazhuang 050043, China.
Sensors (Basel, Switzerland)
|January 10, 2026
Summary
Micro-Negative Poisson Ratio (Micro-NPR) bolts enhance slope stability. Stress wave non-destructive testing combined with a convolutional neural network accurately detects shear deformation in these advanced bolt anchoring systems.
Area of Science:
- Geotechnical Engineering
- Materials Science
- Non-Destructive Testing
Background:
- Slope instability is a critical issue in civil engineering.
- Conventional bolts have limitations in mitigating large deformations.
- Micro-Negative Poisson Ratio (Micro-NPR) bolts offer improved performance.
Purpose of the Study:
- To develop and validate a non-destructive testing method for Micro-NPR bolt anchoring systems.
- To accurately detect shear deformation in slope support structures.
- To enhance the quality inspection of bolt anchoring systems.
Main Methods:
- Utilized stress wave non-destructive detection technology.
- Employed a modular convolutional neural network (CNN) approach.
- Integrated shear angle and shear location identification sub-modules.
Main Results:
- Successfully identified shear deformation in Micro-NPR bolt anchoring systems.
- The integrated CNN approach significantly improved detection accuracy.
- Demonstrated the effectiveness of time-domain signal characteristics for defect detection.
Conclusions:
- The combined stress wave NDT and CNN method is effective for detecting shear deformation in Micro-NPR bolt anchoring systems.
- This technology aids in quality inspection and ensures the stability of slope support.
- The findings will benefit future engineering applications in geotechnical stability.
