Fault diagnosis is important for the maintenance of rotating machinery. The detection of
faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this …

Because multi-fault vibration signals in rotating machinery are often more complicated than
single faults, human-designed fault feature sets are not yet able to respond adequately to …

Intelligent machinery fault diagnosis system has been receiving increasing attention recently
due to the potential large benefits of maintenance cost reduction, enhanced operation safety …

Fault diagnosis in rotating machinery is significant to avoid serious accidents; thus, an
accurate and timely diagnosis method is necessary. With the breakthrough in deep learning …

Fault diagnosis of rotating machinery plays a significant role in the reliability and safety of
modern industrial systems. The traditional fault diagnosis methods usually need manually …

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 …

Aiming to promptly process the massive fault data and automatically provide accurate
diagnosis results, numerous studies have been conducted on intelligent fault diagnosis of …

Intelligent fault diagnosis has been widely used for mechanical fault diagnosis. Most
intelligent diagnostic methods extract fault features from the frequency domain or other …

Many recent studies on deep learning models have focused on increasing accuracy for
mechanical fault data sets, while disregarding the influences of model complexity on …

The analysis of vibration signals has been a very important technique for fault diagnosis and
health management of rotating machinery. Classic fault diagnosis methods are mainly …