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 review of artificial intelligence methods for condition monitoring and fault diagnosis of rolling element bearings for induction motor
The fault detection and diagnosis (FDD) along with condition monitoring (CM) and of rotating
machinery (RM) have critical importance for early diagnosis to prevent severe damage of …
machinery (RM) have critical importance for early diagnosis to prevent severe damage of …
A review on data-driven fault severity assessment in rolling bearings
Health condition monitoring of rotating machinery is a crucial task to guarantee reliability in
industrial processes. In particular, bearings are mechanical components used in most …
industrial processes. In particular, bearings are mechanical components used in most …
An adaptive deep transfer learning method for bearing fault diagnosis
Bearing fault diagnosis has made some achievements based on massive labeled fault data.
In practical engineering, machines are mostly in healthy and faults seldom happen, it's …
In practical engineering, machines are mostly in healthy and faults seldom happen, it's …
Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies
A Shoeibi, N Ghassemi, M Khodatars… - … Signal Processing and …, 2022 - Elsevier
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
The entropy algorithm and its variants in the fault diagnosis of rotating machinery: A review
Rotating machines have been widely used in industrial engineering. The fault diagnosis of
rotating machines plays a vital important role to reduce the catastrophic failures and heavy …
rotating machines plays a vital important role to reduce the catastrophic failures and heavy …
A survey of machine-learning techniques for condition monitoring and predictive maintenance of bearings in grinding machines
It is important to minimize the unscheduled downtime of machines caused by outages of
machine components in highly automated production lines. Considering machine tools such …
machine components in highly automated production lines. Considering machine tools such …
An enhancement deep feature fusion method for rotating machinery fault diagnosis
H Shao, H Jiang, F Wang, H Zhao - Knowledge-Based Systems, 2017 - Elsevier
It is meaningful to automatically learn the valuable features from the raw vibration data and
provide accurate fault diagnosis results. In this paper, an enhancement deep feature fusion …
provide accurate fault diagnosis results. In this paper, an enhancement deep feature fusion …
Development of intelligent fault-tolerant control systems with machine leaprning, deep learning, and transfer learning algorithms: A review
Abstract Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …
Optimization of VMD using kernel-based mutual information for the extraction of weak features to detect bearing defects
In this work, genetic algorithm (GA), kernel based mutual information (KEMI) fitness function
and variational mode decomposition (VMD) based strategy is proposed for the purpose of …
and variational mode decomposition (VMD) based strategy is proposed for the purpose of …