Visual detection of surface damage on wire ropes based on multi-channel axial attention
In industrial scenarios,there were many challenges,such as difficulty of feature extraction,existence of leakage or misdetection and failure to meet the real-time requirements,in real-time detec-tion of wire ropes surface damage early warning based on visual images.To solve these problems,a visual detection algorithm for wire rope damage was proposed based on multi-channel axial attention.Firstly,on the basis of the morphological characteristics of wire ropes,a multi-channel axial attention mechanism was presented to more efficiently extract and focus on more critical feature of the axial re-gion feature information of wire ropes.Secondly,multi-scale fusion was performed through the cen-tralized feature pyramid module to extract feature information on different scales.The combination of the lightweight MobileNetV3 feature extraction network and the anchor-free frame detection head balances detection speed and accuracy.Experiments carried out on a visible image dataset of wire ropes show that the method improves the accuracy by 1.99%compared to the best performing algorithm among the commonly used target detection algorithms.It is capable of better detecting the damage on the surface of wire ropes.