Deconvolution methods (DMs) which can adaptively design the filter for the feature
extraction is the most effective tool to counteract the effect of the transmission path …

Due to the complex and rugged working environment of real machinery equipment, the
resulting fault information is easily submerged by severe noise interference. Additionally …

Adaptive extraction of concerned components (CC) from mixed frequency components
remains to be a challenging topic in various research domains. Most existing adaptive mode …

Because actual vibration signal collected from mechanical equipment (eg, wind turbines and
high-speed trains) are strongly non-stationary and have low signal-to-noise ratios, which …

In this paper, a novel scheme for detecting bearing defects is proposed utilizing single-
valued neutrosophic cross-entropy (SVNCE). Initially, the artificial hummingbird algorithm …

Due to the severe working condition and long-term service, the key rotating parts including
the bearing and gearbox, are susceptible to damage. Blind deconvolution which can …

Due to their short duration, concealability, and random occurrence, intermittent faults have
become the most dangerous hazard in electronic circuit systems. However, existing …

This article provides a comprehensive overview of state-of-the-art techniques for detecting
and diagnosing stator winding inter-turn short faults (ITSFs) in permanent-magnet …

Harmonics-to-noise ratio (HNR) is an important health index of rotating machine, which has
been applied in blind deconvolution (BD) method to realize periodic impulse detection …

This study investigates the potential to improve the fault detection capability of sparsity-
based blind filtering. It optimizes a finite impulse response filter to maximize the sparsity of …