Dynamic health monitoring (DHM) and performance degradation assessment (PDA) is
critical for mechanical bearings throughout their long in-service life. For this issue, it is …

Abstract Rolling Element Bearings are one of the most ubiquitous machine elements used in
various machineries in the manufacturing industry. Prognosis and estimation of residual life …

Fault diagnosis of rotating machinery is vital to identify incipient failures and avoid
unexpected downtime in industrial systems. This paper proposes a new rolling bearing fault …

This paper presents a new fault feature extraction method based on the combination of local
mean decomposition (LMD) and multi-scale symbolic dynamic information entropy (MSDE) …

High-efficiency motors are being gradually introduced in many industrial applications
because of their positive impacts on the environment by reducing energy consumption and …

Background: Physical and mathematical theories have made it possible to generate
methods for the characterization and diagnosis of physiological variables such as cardiac …

Multiscale Permutation Entropy (MPE) has been applied as a non-linear measure for
estimating the complexity of time series. Nevertheless, the coarse-grained procedure in MPE …

The fourth industrial age takes the manufacturing factory to a new level by introducing smart,
extendible, flexible, modular and customized mass production technologies. Production …

Bearing fault diagnosis is imminent due to the extensive use of rotary machines in the
industries. Rotating machines contain bearings which are prone to health degradation with …

In this paper, an application of Convolutional Neural Network (CNN) to detect a predefined
fault in vibration signal without any feature extraction. The vibration signal, after being …