Applications of machine learning to machine fault diagnosis: A review and roadmap
Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …
machine fault diagnosis. This is a promising way to release the contribution from human …
A comprehensive review of artificial intelligence-based approaches for rolling element bearing PHM: Shallow and deep learning
The objective of this paper is to present a comprehensive review of the contemporary
techniques for fault detection, diagnosis, and prognosis of rolling element bearings (REBs) …
techniques for fault detection, diagnosis, and prognosis of rolling element bearings (REBs) …
Deep regularized variational autoencoder for intelligent fault diagnosis of rotor–bearing system within entire life-cycle process
X Yan, D She, Y Xu, M Jia - Knowledge-Based Systems, 2021 - Elsevier
The performance of complex rotor–bearing system usually decreases with the development
of the running time, which indicates that the rotor–bearing system usually goes through …
of the running time, which indicates that the rotor–bearing system usually goes through …
[HTML][HTML] Mechanical fault diagnosis and prediction in IoT based on multi-source sensing data fusion
M Huang, Z Liu, Y Tao - Simulation Modelling Practice and Theory, 2020 - Elsevier
Using multi-source sensing data based on the Internet of Things (IoT) with artificial
intelligence and big data processing technology to achieve predictive maintenance of …
intelligence and big data processing technology to achieve predictive maintenance of …
A hybrid feature model and deep-learning-based bearing fault diagnosis
Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary
machines. It can reduce economical losses by eliminating unexpected downtime in industry …
machines. It can reduce economical losses by eliminating unexpected downtime in industry …
Prognostics and health management of industrial assets: Current progress and road ahead
L Biggio, I Kastanis - Frontiers in Artificial Intelligence, 2020 - frontiersin.org
Prognostic and Health Management (PHM) systems are some of the main protagonists of
the Industry 4.0 revolution. Efficiently detecting whether an industrial component has …
the Industry 4.0 revolution. Efficiently detecting whether an industrial component has …
A novel optimised self-learning method for compressive strength prediction of high performance concrete
Concrete strength (CS) is one of the most important performance parameters that are crucial
in the design of concrete structure. The reliable prediction of strength can reduce the cost …
in the design of concrete structure. The reliable prediction of strength can reduce the cost …
Principal component analysis approach for detecting faults in rotary machines based on vibrational and electrical fused data
M Elsamanty, A Ibrahim, WS Salman - Mechanical Systems and Signal …, 2023 - Elsevier
Rotating machines are frequently used in industrial applications. However, due to their
severity, mechanical failures such as rotor imbalance, shaft imbalance, pulley imbalance …
severity, mechanical failures such as rotor imbalance, shaft imbalance, pulley imbalance …
Manifold sensing-based convolution sparse self-learning for defective bearing morphological feature extraction
Q Li, X Ding, Q He, W Huang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The transient features caused by a local fault are of vital importance for bearing fault
diagnosis in an intelligent industry. Due to the uncertainty of fault forms and nonstationarity …
diagnosis in an intelligent industry. Due to the uncertainty of fault forms and nonstationarity …
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 …