Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …

Abstract Fault Detection and Diagnosis (FDD) of rotating machinery plays a key role in
reducing the maintenance costs of the manufacturing systems. How to improve the FDD …

Fault diagnosis of rolling bearings has attracted extensive attention in industrial fields, which
plays a vital role in guaranteeing the reliability, safety, and economical efficiency of …

Intelligent fault diagnosis of rolling element bearings has made some achievements based
on the availability of massive labeled data. However, the available data from bearings used …

This paper proposes a novel intelligent fault diagnosis method to automatically identify
different health conditions of wind turbine (WT) gearbox. Unlike traditional approaches …

This paper presents a data-driven intelligent fault diagnosis approach for rotating machinery
(RM) based on a novel continuous wavelet transform-local binary convolutional neural …

Blind deconvolution has been proved to be an effective method for fault detection since it
can recover periodic impulses from mixed fault signals convoluted by noise and periodic …

Automatic and accurate identification of rolling bearings fault categories, especially for the
fault severities and fault orientations, is still a major challenge in rotating machinery fault …

Fault diagnosis of rotating machinery is essential for maintaining system performance and
ensuring the operation safety. Deep learning (DL) has been recently developed rapidly and …

The vibration signals collected from rolling bearing are usually complex and non-stationary
with heavy background noise. Therefore, it is a great challenge to efficiently learn the …