In addition to narrowband interference signals, there are also other noise interference sources on the optical communication link. These noise signals may mask or interfere with the characteristics of narrowband interference signals, increasing the difficulty of identification. Therefore, a coherent optical communication link narrowband interference signal identification method based on wavelet transform is proposed. Obtain optical communication signals through optical communication link functions, and perform wavelet transform processing on the collected signals to remove signal noise while ensuring communication signal quality. Establish an expert knowledge graph of interference signals based on interference types, use convolutional neural networks to construct an interference signal identification model, input the communication signal processed by wavelet transform into the interference signal identification model for feature extraction, and combine the extracted features with the expert knowledge graph to determine the probability of the signal belonging to narrowband interference signals, thereby completing the accurate identification of narrowband interference signals in optical communication links. The experimental results show that using this method to identify narrowband interference signals in optical communication links has high identification accuracy and good identification performance, and has high practical application value.