Research on broken wire detection algorithm of lightweight mine wire rope based on attention mechanism
The shaft lifting system is the primary transportation equipment in coal mine production,wire rope,as the core component,often experiences breakage due to heavy workloads,corrosion,wear,and other factors,leading to accidents.The traditional wire rope detection algorithm for shaft hoists has limitations such as low efficiency,high labor intensity,poor intelligence,and low accuracy.Therefore,the authors proposed an improved YOLOv5s model for detecting broken wires in mine wire ropes.A Swiener filter algorithm was designed to repair motion blur in wire rope images and suppress noise interference;in the feature extraction stage,the RFC3 lightweight module was introduced to reduce trainable parameters and increase detection speed;a CBAM-R attention mechanism was proposed to enhance the detection ability for small fracture;the introduction of Focal EIoU loss function improved small fracture detection accuracy and accelerated model convergence.Experimental results demonstrated that the broken wire detection algorithm for mine wire rope based on attention mechanism(CTR-YOLO)better met practical application requirements by reducing labor costs waste and minimizing safety accidents caused by false detection or missed detection.
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