The secondary circuit of the substation is the basis of the secondary advanced integrated business. The automatic feature recognition and information extraction of the secondary circuit by image recognition technology can realize the secondary circuit's intelligent operation and maintenance business. However, the images collected by the substation have messy backgrounds, low resolution, and distortion, making it very challenging to identify irregular text using image recognition technology. Therefore, a text detection and recognition method of a secondary loop terminal based on an attention mechanism is proposed. This method mainly includes preprocessing, text detection, and text recognition. In the text recognition part, a spatiotemporal embedding encoding method is proposed, which can better use the picture's location information. Compared with the unimproved method, only the sequence?level annotation information is needed in the training process, and no additional fine?grained character level box or segmentation mask is needed. Finally, it is proved that the proposed method is not only easy to use and has good performance but is also better than other methods in recognition accuracy.