The research for co-channel multi-signal modulation classification has become urgent with the increasing shortage of spectral bandwidth. Single-signal modulation classification methods which have been widely studied are not applicable for co-channel multi-signal modulation classification problem. In this paper, we developed a method for co-channel multi-signal modulation classification based on Convolution Neural Network(CNN). The proposed method can identify 31 mixed signals from 5 modulation types. The proposed method are also found to be robust to the changes of SNR from 0dB to 15dB. The experiments are performed to prove the effectiveness of the proposed method.