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In view of the complex environment under the transmission channel and the frequent damage of various engineering vehicles to the transmission line, the problem of detection and identification of engineering vehicles needs to be solved. Based on the single-stage target detection algorithm YoloX, the loss function in YoloX algorithm is modified to balance the positive and negative samples and difficult samples, add CBAM attention mechanism in the network, combine the internal channel information and location information, improve the feature extraction ability, and modify the CspLayer structure in the strong feature extraction part Neck, on the premise of ensuring the detection speed, Improve the detection performance of the model. By screening the pictures with low brightness, the improved MSR algorithm is introduced to improve the brightness of the pictures and optimize the data set. Experimental results show that the proposed algorithm improves the detection accuracy. Compared with the traditional YoloX algorithm, the mAP is improved by 4.64%, and the recognition effect is significantly improved, which proves the effectiveness of the new algorithm.