Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …

Safety and reliability are absolutely important for modern sophisticated systems and
technologies. Therefore, malfunction monitoring capabilities are instilled in the system for …

Bearing fault diagnosis plays an important role in rotating machinery equipment's safe and
stable operation. However, the fault sample collected from the equipment is seriously …

To extract more distinguishing features of ships, slope entropy (SloE) is introduced into
underwater acoustic signal processing as a new feature to analyze ship-radiated noise …

Entropy, as a complexity measure, has been widely applied for time series analysis. One
preeminent example is the design of machine condition monitoring and industrial fault …

Artificial Intelligence (AI) is a key component in Industry 4.0. Rotating machines are critical
components in manufacturing industries. In the vast world of Industry 4.0, where an IoT …

The working environment of rolling bearings is highly complex and often the vibration signal
of the bearing is mixed with noise, which makes fault diagnosis challenging. As such, it is …

In the last decades, a wide portfolio of Feature Weighting (FW) methods have been
proposed in the literature. Their main potential is the capability to transform the features in …

The health condition of rolling bearing possesses a significant impact on the safety and
efficiency of rotating machinery. Accordingly, to diagnose the faults in rolling bearings …

Obtaining the sensitive feature vectors from the vibration signal is crucial to indicate the
bearing's actual condition. Most often, weak feature vectors are the consequence of heavy …