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.
维普
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