Generalized Soft Failure Identification enabled by Digital Residual Spectrum and Autoencoder

We propose a highly generalized soft failure identification model based on digital residual spectrum and autoencoder. In case of random fluctuation, it could reach identification accuracy of more than 97.61% for five different transmission distances.