钢丝绳表面缺陷检测方法及系统
By constructing an improved YOLO26 lightweight defect detection model, the problems of low detection efficiency and insufficient accuracy of mining wire ropes were solved, achieving high-precision detection in complex environments, adapting to the spiral texture of wire ropes and suppressing underground interference.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUBEI ELEVATOR FACTORY
- Filing Date
- 2026-05-14
- Publication Date
- 2026-07-17
AI Technical Summary
Existing wire rope testing methods are inefficient, costly, and have limited ability to detect micro-cracks on the surface, making them unsuitable for testing mining wire ropes under high load, high humidity, and corrosive environments.
A lightweight defect detection model based on the improved YOLO26 was constructed, including a backbone feature extraction network, a neck feature fusion network, and a detection head network. Through multi-level alternating cascaded lightweight adaptive sampling units and dual-path frequency domain downsampling units, the model dynamically adapts to the spiral texture of the wire rope, preserves the high-frequency features of minor defects, and suppresses downhole interference to achieve accurate detection.
It significantly improves the accuracy and robustness of surface defect detection for mining steel wire ropes, can adapt to the detection needs in complex environments, effectively identify minute defects and suppress noise interference.
Smart Images
Figure CN122199545B_ABST