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Automatic Detection and Association Analysis of Multiple Surface Defects on Shield Subway Tunnels
Ziren Yin1, Zhanzhan Lei2,3,4, Ao Zheng2,3,4
1College of Urban Transportation and Logistics, Shenzhen Technology University, Shenzhen 515118, China.
Sensors (Basel, Switzerland)
|August 26, 2023
Summary
Tunnel inspection trolleys detect surface defects like water leakage, dislocation, and spalling in subway tunnels. Association rules reveal dislocation and spalling often cause water leakage, aiding maintenance and safety.
Area of Science:
- Civil Engineering
- Geotechnical Engineering
- Structural Health Monitoring
Background:
- Surface defects in shield subway tunnels critically impact structural integrity and operational safety.
- Effective detection of multiple defects is essential for timely maintenance and risk mitigation.
Purpose of the Study:
- To detect and identify various surface defects in shield subway tunnels.
- To explore the root causes of these defects using association rule mining.
Main Methods:
- Utilized a tunnel inspection trolley (TIT) equipped with mobile laser scanning technology.
- Applied an improved Apriori algorithm to calculate association rules between different tunnel defects.
Main Results:
- Identified defects including water leakage, dislocation, spalling, and cross-section deformation.
- Found significant variations in association rules among defects.
- The rule "dislocation & spalling → water leakage" showed high confidence (57.78%), indicating these defects commonly precede water leakage.
Conclusions:
- Association rule analysis effectively predicts critical defects like water leakage.
- Findings support optimizing construction and maintenance strategies for shield subway tunnels.
- Understanding defect correlations enhances structural reliability and operational safety.
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