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Aiming at the problems of accuracy and efficiency of existing on-line monitoring algorithms for transmission equipment, an on-line detection algorithm based on improved SSD network model is proposed. Firstly, the fault set is preprocessed, and the noise interference of the original fault set is filtered by filtering modulation and resonance demodulation. The SSD network structure is designed based on VGG-16, and auxiliary convolution layer and prediction layer are added. To improve the SSD network model, the attention mechanism module and feature enhancement module are introduced to improve the data sharing performance of each layer of the model and improve the data training efficiency of the model. The multi-scale feature fusion of fault data is carried out based on the channel fusion method, and the pyramid structure of each layer of SSD model is optimized to better match the prior frame and select the best loss function. Experimental results show that the transmission equipment fault detection rate of the proposed algorithm is 98.8%, and the detection efficiency of the proposed algorithm is better than the existing algorithm.