With the rapid development of industry, fault diagnosis plays a more and more important role
in maintaining the health of equipment and ensuring the safe operation of equipment. Due to …

Over the last decade, transfer learning has attracted a great deal of attention as a new
learning paradigm, based on which fault diagnosis (FD) approaches have been intensively …

Recent studies on machinery anomaly detection only based on normal data training models
have yielded good results in improving operation reliability. However, most of the studies …

The increased complexity and intelligence of automation systems require the development
of intelligent fault diagnosis (IFD) methodologies. By relying on the concept of a suspected …

In real industries, there often exist application scenarios where the target domain holds fault
categories never observed in the source domain, which is an open-set domain adaptation …

Accurate bearing fault diagnosis is of great significance of the safety and reliability of rotary
mechanical system. In practice, the sample proportion between faulty data and healthy data …

Contactless fault diagnosis is one of the most important technique for fault identification of
equipment. Based on the idea of contactless fault diagnosis, this paper presents a sound …

Deep-neural network-based fault diagnosis methods have been widely used according to
the state of the art. However, a few of them consider the prior knowledge of the system of …

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 …

Wavelet transform, a time-frequency analysis method for evaluating non-stationary signals,
can assist in representing equipment degradation over prolonged usage. However, a single …