Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance
Landslides are one of the catastrophic natural hazards that occur in mountainous areas,
leading to loss of life, damage to properties, and economic disruption. Landslide …
leading to loss of life, damage to properties, and economic disruption. Landslide …
Artificial intelligence for fault diagnosis of rotating machinery: A review
Fault diagnosis of rotating machinery plays a significant role for the reliability and safety of
modern industrial systems. As an emerging field in industrial applications and an effective …
modern industrial systems. As an emerging field in industrial applications and an effective …
Robust fault recognition and correction scheme for induction motors using an effective IoT with deep learning approach
Maintaining electrical machines in good working order and increasing their life expectancy
is one of the main challenges. Precocious and accurate detection of faults is crucial to this …
is one of the main challenges. Precocious and accurate detection of faults is crucial to this …
Bearing fault diagnosis of induction motors using a genetic algorithm and machine learning classifiers
RN Toma, AE Prosvirin, JM Kim - Sensors, 2020 - mdpi.com
Efficient fault diagnosis of electrical and mechanical anomalies in induction motors (IMs) is
challenging but necessary to ensure safety and economical operation in industries …
challenging but necessary to ensure safety and economical operation in industries …
The experimental application of popular machine learning algorithms on predictive maintenance and the design of IIoT based condition monitoring system
With the fourth industrial revolution, which has become increasingly widespread in the
manufacturing industry, traditional maintenance has been replaced by the industrial internet …
manufacturing industry, traditional maintenance has been replaced by the industrial internet …
Reliable deep learning and IoT-based monitoring system for secure computer numerical control machines against cyber-attacks with experimental verification
This paper introduces a new intelligent integration between an IoT platform and deep
learning neural network (DNN) algorithm for the online monitoring of computer numerical …
learning neural network (DNN) algorithm for the online monitoring of computer numerical …
A review of physics-based models in prognostics: Application to gears and bearings of rotating machinery
A Cubillo, S Perinpanayagam… - Advances in …, 2016 - journals.sagepub.com
Health condition monitoring for rotating machinery has been developed for many years due
to its potential to reduce the cost of the maintenance operations and increase availability …
to its potential to reduce the cost of the maintenance operations and increase availability …
A deep learning method for bearing fault diagnosis based on time-frequency image
Rolling element bearing is a critical component in rotating machinery that reduces the
friction between moving pairs. Bearing fault diagnosis is always considered as a research …
friction between moving pairs. Bearing fault diagnosis is always considered as a research …
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 deep learning model based on target transformer for fault diagnosis of chemical process
Z Wei, X Ji, L Zhou, Y Dang, Y Dai - Process safety and environmental …, 2022 - Elsevier
Deep learning is a powerful tool for feature representation, and many methods based on
convolutional neural networks (CNNs) and recurrent neural networks (RNNs) have been …
convolutional neural networks (CNNs) and recurrent neural networks (RNNs) have been …