The correct trace identification of the ionosphere in ionograms is one of the fundamental steps to the automatic scaling of ionograms. In this paper, a new method based on deep learning network is proposed to identify the traces of ionograms and ionospheric irregularities effectively. 12000 ionograms from the Chinese Academy of Sciences Digital Ionosonde installed at Huailai, Wuhan, Naning, Ganzi and Xiamen are utilized to train the deep learning network and satisfying results with 83.9% mAP are obtained.