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 …

Rolling bearing fault detection is critical for improving production efficiency and lowering
accident rates in complicated mechanical systems, as well as huge monitoring data, posing …

With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …

Efficient fault diagnosis of electrical and mechanical anomalies in induction motors (IMs) is
challenging but necessary to ensure safety and economical operation in industries …

As an important stage of life cycle management, machinery PHM (prognostics and health
management), an emerging subject in mechanical engineering, has seen a huge amount of …

Rotating machinery fault diagnosis under nonstationary conditions still mainly relies on
manual analysis of the frequency spectrums or the time-frequency representations of …

Abstract—The fault diagnosis of wind turbines under nonstationary conditions is still
challenging. This paper proposes a novel tacho-less generalized demodulation (NTLGD) …

Due to a difficulty in dealing with the nonlinear vibration signals collected from varying
speeds by conventional signal process method, it was worse to develop fault diagnosis in …

There are more and more bearing fault types under considering the fault location and
degree, and the corresponding fault classification task is becoming increasingly heavy. Raw …

In the era of big data, data‐driven methods mainly based on deep learning have been
widely used in the field of intelligent fault diagnosis. Traditional neural networks tend to be …