As the core component of rotating machinery, the complex loads and sustained rotations in
the harsh conditions are prone to multiple faults. It is the primary researching that extracting …

As the crucial part of the health management and condition monitoring of mechanical
equipment, the fault diagnosis and pattern recognition using vibration signal are essential …

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 …

Generally, the health conditions of rotating machinery are complicated and changeable.
Meanwhile, its fault labeled information is mostly unknown. Therefore, it is man-sized to …

Rotating machinery plays a critical role in many significant fields. However, the
unpredictable machinery faults may lead to the severe damage and losses. Hence, it is of …

A novel intelligent fault diagnosis method based on deep learning and particle swarm
optimization support vectors machine (PSO-SVM) is proposed. The method uses deep …

Intelligent fault diagnosis methods of rotating machinery have attracted much attention in
recent years. In this paper, an intelligent deep learning based method named deep recurrent …

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

To improve the performance in identifying the faults under strong noise for rotating
machinery, this article presents a dynamic feature reconstruction signal graph method …

Rotating machinery are widely used in industry, and vibration analysis is one of the most
common methods to monitor health condition of rotating machinery. However, due to the …