Bearings are one of the most important parts of a rotating machine. Bearing failure can lead
to mechanical failure, financial loss, and even personal injury. In recent years, various deep …

Rolling bearings are the core components of rotating machinery. Their health directly affects
the performance, stability and life of rotating machinery. To prevent possible damage, it is …

In recent years, deep learning technique has been used in mechanical intelligent fault
diagnosis and it has achieved much success. Among the deep learning models …

Deep learning method is gradually applied in the field of mechanical equipment fault
diagnosis because it can learn complex and useful features automatically from the vibration …

Intelligent operation and maintenance is an important part of Industry 4.0. In order to realize
the intelligent of plant equipment, it will make full use of artificial intelligence methods to …

Rolling bearing fault signals are non-smooth, non-linear, and susceptible to background
noise interference. A feature layer fusion model combining multi-sensor signals and parallel …

Aiming at the problems of traditional fault diagnosis methods that do not represent the time
correlation between signals, low recognition accuracy under complex working conditions …

Bearing fault diagnosis is essential for the safe and stable operation of rotating machinery.
Existing methods use signals from a single dimension, limiting diagnostic generality and …

An effective fault diagnosis method of bearing is the key to predictive maintenance of
modern industrial equipment. With the single use of equipment failure mechanism or …

Intelligent algorithms based on convolutional neural network (CNN) has demonstrated
remarkable potential in diagnosing bearing faults. However, Accurate and robust fault …