This paper presents the method for automatic recognition of defects in aircraft riveted joints. The proposed method consists of three steps: pre-processing, feature extraction and classification. Feature extraction was then performed using discrete wavelet transform. Classification was performed using deep neural network. An example of solving the problem of detecting and recognizing a defect in rivets is considered.