The condition monitoring (CM) of rotating machinery (RM) is an essential operation for
improving the reliability of mechanical systems. For this purpose, an efficient CM method that …

Blades play a vital role in wind turbine system performances. However, they are susceptible
to damage arising from complex and irregular loading or even cause catastrophic collapse …

Blind deconvolution has been proved to be an effective method for fault detection since it
can recover periodic impulses from mixed fault signals convoluted by noise and periodic …

Intelligent fault diagnosis of rolling element bearings gains increasing attention in recent
years due to the promising development of artificial intelligent technology. Many intelligent …

In recent years, an increasing popularity of deep learning model for intelligent condition
monitoring and diagnosis as well as prognostics used for mechanical systems and …

Feature extraction is a key step in intelligent bearing fault diagnosis. However, bearing
vibration signals are usually nonlinear, nonstationary signal with strong noises. Extracting …

Rotating machinery is widely applied in various types of industrial applications. As a
promising field for reliability of modern industrial systems, early fault diagnosis (EFD) …

Rotating machinery is widely applied in industrial applications. Fault diagnosis of rotating
machinery is vital in manufacturing system, which can prevent catastrophic failure and …

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 …

An immense body of research has focused on chaotic systems, mainly because of their
interesting applications in a wide variety of fields. A comprehensive understanding and …