In this network, a network US-WGAN, which can generate ultrasonic guided wave signals, is proposed to solve the problem of lack of data sets for ultrasonic nondestructive testing based on deep neural networks. This network was trained on the pre-enhanced data set and US-WGAN-enhanced data set with 3000 epochs, and the ultrasound signals generated by US-WGAN are proved to be of high quality (peak signal to noise ratio score of 30 – 50 dB) and belong to the same distribution population as the original data set.