This paper presents a new approach to machine health monitoring based on the
Approximate Entropy (ApEn), which is a statistical measure that quantifies the regularity of a …

Nonlinear techniques have been widely and successfully used to analyze the vibration
signals in rotary machines due to the nonlinear nature of such times series. We have …

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 …

This paper investigates the usage of permutation entropy for working status characterization
of rotary machines. As a statistical measure, the permutation entropy describes complexity of …

Bearings are considered to be the most frequent cause for failures in rotational machinery.
Hence efficient means to anticipate the remaining useful life (RUL) on-line, by processing …

Rotating machines have been widely used in industrial engineering. The fault diagnosis of
rotating machines plays a vital important role to reduce the catastrophic failures and heavy …

This paper investigates the performance of the 12 entropy-based features for the monitoring
and detection of bearing faults. These entropy measures were proposed both in time …

Features describing the state of industrial gearboxes and their extraction from the mixed
noisy signal are always an issue of concern. Unfortunately, traditional feature extraction …

Early identification of rolling element defects is always a topic of interest for researchers and
the industry. For early fault identification, a simple and effective dynamic degradation …

Rotating machinery is used at length in a variety of industrial applications. The continuous
monitoring of rotating machines is of excessive importance when it comes to prevent their …