In the secondary side management of the substation, the pressure plate plays a major role. This paper proposes an improved SSD image recognition algorithm to realize the recognition of the pressure state of the plate. The novel algorithm embeds the attention mechanism in the SSD target recognition algorithm, utilizes the attention mechanism to mine the importance of each feature channel, increases the weight of useful features, suppresses invalid features, and improves the detection accuracy of the original algorithm. In order to solve the problem of insufficient training samples, the novel algorithm trains the parameters of the proposed novel SSD algorithm by means of sample expansion and migration learning, which is verified by simulation experiments. Experimental results show that the improved SSD algorithm has a recognition accuracy rate of 96%, a recall rate of 94%, and 23 images per second can be detected, which can effectively improve the efficiency of the pressure plate status in the substation.
