Radio Frequency(RF) fingerprinting identification based on the physical layer of wireless devices is an effective way to ensure communication security. The conventional RF feature extraction methods are susceptible to interference from changes in the Signal-to-Noise Ratio(SNR) of the channel, which are not suitable to dynamic SNR communication situation. A RF fingerprint identification method based on Convolutional Neural Network(CNN) is proposed, which could fulfill RF fingerprinting identification under dynamic SNR condition and significantly improve the recognition rate under low SNR condition. In addition, the experiments are implemented to identify four different power amplifier devices. The experimental results show that the comprehensive recognition rate of the proposed method is 89.4% under dynamic SNR of 0.5~14.5 dB.