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 …

Process monitoring technologies play a key role in maintaining the steady state of industrial
processes. However, with the increasing complexity of modern industrial processes …

Deep learning architectures usually require large scale labeled datasets for achieving good
performance on general classification tasks including computer vision and natural language …

Process fault detection and diagnosis (FDD) is a predominant task to ensure product quality
and process reliability in modern industrial systems. Those traditional FDD techniques are …

Regular detection of defects in drainage pipelines is crucial. However, some problems
associated with pipeline defect detection, such as data scarcity and defect counting difficulty …

Currently, convolutional neural networks (CNNs) have shown great potential in the field of
rotating machinery fault diagnosis. To maximize accuracy, the network architecture of novel …

In recent years, deep learning has been widely applied in process fault diagnosis due to its
powerful feature extraction ability. A predominant property of these fault diagnosis models is …

Abstract Prognostics and Health Management (PHM) is the core task in modern industries to
provide the reliability and availability of mechanical systems. In recent years, the …

The traditional fault diagnosis models cannot achieve good fault diagnosis accuracy when a
new unseen fault class appears in the test set, but there is no training sample of this fault in …

Fault diagnosis plays a vital role in assessing the health management of industrial robots
and improving maintenance schedules. In recent decades, artificial intelligence-based data …