Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images
The bearings are the crucial components of rotating machines in an industrial firm.
Unplanned failure of these components not only increases the downtime, but also leads to …
Unplanned failure of these components not only increases the downtime, but also leads to …
A systematic review of machine learning algorithms for prognostics and health management of rolling element bearings: fundamentals, concepts and applications
This article aims to present a comprehensive review of the recent efforts and advances in
applying machine learning (ML) techniques in the area of diagnostics and prognostics of …
applying machine learning (ML) techniques in the area of diagnostics and prognostics of …
Fault diagnosis of machines operating in variable conditions using artificial neural network not requiring training data from a faulty machine
In the maintenance of rotating machinery, the vibration signal is the basis of condition
monitoring systems. Dedicated signal analysis methods are applied depending on the …
monitoring systems. Dedicated signal analysis methods are applied depending on the …
Non-contact fault diagnosis of bearings in machine learning environment
Timely detection of faults in bearings can save time, efforts and maintenance costs of
rotating equipments. To avoid the physical connection of vibration pickup to the machine …
rotating equipments. To avoid the physical connection of vibration pickup to the machine …
A review of phase space topology methods for vibration-based fault diagnostics in nonlinear systems
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 …
information obtained in the measurement space to the presence and magnitude of faults in …
Stochastic resonance in cascaded monostable systems with double feedback and its application in rolling bearing fault feature extraction
J Li, X Wang, Z Li, Y Zhang - Nonlinear Dynamics, 2021 - Springer
Stochastic resonance (SR) has been widely concerned and studied in the field of
mechanical fault detection due to the capability of weak signal detection. However, research …
mechanical fault detection due to the capability of weak signal detection. However, research …
On extraction, ranking and selection of data-driven and physics-informed features for bearing fault diagnostics
TH Mohamad, A Abbasi, K Kappaganthu… - Knowledge-Based …, 2023 - Elsevier
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 …
box machine learning models, which lack generalizability to out of sample cases and are …
Gesture recognition–based smart training assistant system for construction worker earplug-wearing training
Thousands of construction workers suffer noise-induced hearing loss (NIHL) every year from
excessive noise exposure on the job, which impairs the quality of their lives and increases …
excessive noise exposure on the job, which impairs the quality of their lives and increases …
[PDF][PDF] Fault Classification of Rolling Element Bearing in Machine Learning Domain.
Industrial machines have high investment costs, and their practical usage depends on low
operating and maintenance costs. Rolling element bearings (REBs) are a vital component of …
operating and maintenance costs. Rolling element bearings (REBs) are a vital component of …
An adaptive periodical stochastic resonance method based on the grey wolf optimizer algorithm and its application in rolling bearing fault diagnosis
B Hu, C Guo, J Wu, J Tang… - … of Vibration and …, 2019 - asmedigitalcollection.asme.org
As a weak signal processing method that utilizes noise enhanced fault signals, stochastic
resonance (SR) is widely used in mechanical fault diagnosis. However, the classic bistable …
resonance (SR) is widely used in mechanical fault diagnosis. However, the classic bistable …