Machine learning in predictive maintenance towards sustainable smart manufacturing in industry 4.0
Recently, with the emergence of Industry 4.0 (I4. 0), smart systems, machine learning (ML)
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
Role of artificial intelligence in rotor fault diagnosis: A comprehensive review
Artificial intelligence (AI)-based rotor fault diagnosis (RFD) poses a variety of challenges to
the prognostics and health management (PHM) of the Industry 4.0 revolution. Rotor faults …
the prognostics and health management (PHM) of the Industry 4.0 revolution. Rotor faults …
[HTML][HTML] GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms
Hazards and disasters have always negative impacts on the way of life. Landslide is an
overwhelming natural as well as man-made disaster that causes loss of natural resources …
overwhelming natural as well as man-made disaster that causes loss of natural resources …
Performance analysis of IoT-based sensor, big data processing, and machine learning model for real-time monitoring system in automotive manufacturing
With the increase in the amount of data captured during the manufacturing process,
monitoring systems are becoming important factors in decision making for management …
monitoring systems are becoming important factors in decision making for management …
Modeling flood susceptibility using data-driven approaches of naïve bayes tree, alternating decision tree, and random forest methods
Floods are one of the most devastating types of disasters that cause loss of lives and
property worldwide each year. This study aimed to evaluate and compare the prediction …
property worldwide each year. This study aimed to evaluate and compare the prediction …
Review on machine learning algorithm based fault detection in induction motors
Fault detection prior to their occurrence or complete shut-down in induction motor is
essential for the industries. The fault detection based on condition monitoring techniques …
essential for the industries. The fault detection based on condition monitoring techniques …
Unlocking the power of industrial artificial intelligence towards Industry 5.0: Insights, pathways, and challenges
With the continuous development of human-centric, resilient, and sustainable manufacturing
towards Industry 5.0, Artificial Intelligence (AI) has gradually unveiled new opportunities for …
towards Industry 5.0, Artificial Intelligence (AI) has gradually unveiled new opportunities for …
Assessment of groundwater quality in arid regions utilizing principal component analysis, GIS, and machine learning techniques
Assessing water quality in arid regions is vital due to scarce resources, impacting health and
sustainable management. This study examines groundwater quality in Assuit Governorate …
sustainable management. This study examines groundwater quality in Assuit Governorate …
A rotating machinery fault diagnosis method based on multi-scale dimensionless indicators and random forests
Q Hu, XS Si, QH Zhang, AS Qin - Mechanical systems and signal …, 2020 - Elsevier
Fault diagnosis methods based on dimensionless indicators have long been studied for
rotating machinery. However, traditional dimensionless indicators frequently suffer a low …
rotating machinery. However, traditional dimensionless indicators frequently suffer a low …
Motor fault diagnosis using attention mechanism and improved adaboost driven by multi-sensor information
Z Long, X Zhang, L Zhang, G Qin, S Huang, D Song… - Measurement, 2021 - Elsevier
Fault diagnosis driven by the single signal has been widely used in motor fault diagnosis,
but it can not meet the diagnostic requirements of complex motor system. In this study, a …
but it can not meet the diagnostic requirements of complex motor system. In this study, a …