A new method is proposed in the present work for identifying fault severity in the ball
bearings. Proposed method named as multi-scale refined composite standard deviation …

Background In general, diagnostics can be defined as the procedure of mapping the
information obtained in the measurement space to the presence and magnitude of faults in …

Many traditional bearing fault detection techniques rely on pattern recognition using black
box machine learning models, which lack generalizability to out of sample cases and are …

This paper presents the application of recurrence plots (RPs) and recurrence quantification
analysis (RQA) in the diagnostics of various faults in a gear-train system. For this study …

This paper applies a novel feature extraction method called Extended Phase Space
Topology (EPST) in order to diagnose various faults in a gear-train system. The EPST …

In general, diagnostics can be defined as the procedure of mapping the information
obtained in the measurement space to the presence and magnitude of faults in the fault …

The research focuses on fault detection and diagnostics of cracks in a rotating shaft by using
the Extended Phase Space Topology approach (EPST). EPST is based on extracting …

This paper presents the application of Extended Phase Space Topology (EPST) and
conventional statistical time domain features in the diagnostics of various bearing faults in …

The paper considers the identification of chaotic behavior dynamics using the data extracted
from an experimental model of rotor supported on rolling elements. A description of the …

The current study concerns diagnostics of a one-stage gearbox based on the integration of
physics and machine learning. A physics-based model of this system is developed, then a …