Advanced Signal Processing Methods And Deep Neural Networks For Machine Fault Diagnosis

This article discusses the use of advanced signal processing methods and deep neural networks for machinery fault diagnosis. These techniques can extract fault features from machine condition monitoring signals and assess the operating status of the machine. However, deep neural networks lack interpretability, so researchers have developed interpretable deep neural networks using classical signal processing theories. This Special Issue aims to collect research on these topics.