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.
Once seen as a routine technical task with little influence on research outcomes, data integration has rapidly evolved and at times has become the backbone of modern research innovation.
In today's data-driven world, the sheer volume of information generated daily is staggering overwhelming. The massive influx of data today presents many complex challenges for research departments across all sectors.