Aiming at the high requirements for both accuracy and detection speed of the target detection model in intelligentinspection of transmission lines

and the complex and variable background of transmission lines

a transmission line externalforce damage detection algorithm based on improved YOLOv8 is proposed.The spatial channel reconstruction convolutionmodule is used to reduce the computational resources required for redundant feature extraction;an adaptive spatial featurefusion technique is employed to address the feature fusion of external force damage targets in complex backgrounds;Abounding box loss function based on the minimum point distance is used in the loss function to increase the detection accuracyof the algorithm.Comparison experiments with traditional algorithms and other improved target detection algorithms find thatthe detection accuracy and detection speed of the proposed algorithm are significantly better than other algorithms.The resultsshow that

on the transmission line external force damage dataset

the mean average precision(mAP)at 50% confidence

themAP at 50% to 95% confidence

and the detection speed are improved by 5.3%

9.2%

and 23.6 frames per second(FPS)

respectively

which effectively enhance both detection accuracy and speed

making the proposed algorithm applicable fordetecting external force damage to transmission lines.