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An Optimized YOLOv11 Framework for the Efficient Multi-Category Defect Detection of Concrete Surface
Zhuang Tian1, Fan Yang1,2, Lei Yang1
1School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China.
Sensors (Basel, Switzerland)
|March 17, 2025
Summary
A new concrete defect detection model, YOLOv11-EMC, improves accuracy and reduces errors in identifying structural flaws. This enhances structural safety and extends the service life of concrete infrastructure.
Area of Science:
- Civil Engineering
- Computer Vision
- Artificial Intelligence
Background:
- Accurate concrete defect identification is vital for structural safety and longevity.
- Existing models struggle with the complexity and variability of concrete defects, leading to detection inaccuracies.
- These limitations pose risks to structural integrity in real-world engineering applications.
Purpose of the Study:
- To develop an efficient and robust concrete defect detection model.
- To enhance the accuracy and generalization capabilities of existing detection models.
- To address the challenges posed by irregular defect shapes and complexities in engineering inspections.
Main Methods:
- Proposed YOLOv11-EMC (efficient multi-category concrete defect detection) model.
- Incorporated modified deformable convolution to extract irregular defect features effectively.
- Integrated C3k2 module with a revised dynamic convolution module for computational efficiency and improved feature representation.
Main Results:
- YOLOv11-EMC demonstrated significant improvements over Yolov11 in precision (+8.3%), recall (+2.1%), mAP50 (+4.3%), and F1 (+3%).
- Field tests using drone imagery confirmed reduced false and under-detections.
- The model achieved higher overall detection accuracy in practical engineering scenarios.
Conclusions:
- YOLOv11-EMC offers a superior methodology for identifying tangible flaws in concrete structures.
- The enhanced model improves robustness and generalization for concrete defect detection.
- This contributes to better structural safety and extended service life in engineering applications.
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