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A comprehensive overview and comparative analysis on deep learning models: CNN, RNN, LSTM, GRU
Deep learning (DL) has emerged as a powerful subset of machine learning (ML) and
artificial intelligence (AI), outperforming traditional ML methods, especially in handling …
artificial intelligence (AI), outperforming traditional ML methods, especially in handling …
[HTML][HTML] Digital twins enabling intelligent manufacturing: from methodology to application
S Hu, C Li, B Li, M Yang, X Wang, T Gao… - Intelligent and …, 2024 - sciepublish.com
Digital twin technology develops virtual models of objects digitally, simulating their real-
world behavior based on data. It aims to reduce product development cycles and costs …
world behavior based on data. It aims to reduce product development cycles and costs …
Review of resampling techniques for the treatment of imbalanced industrial data classification in equipment condition monitoring
Y Yuan, J Wei, H Huang, W Jiao, J Wang… - … Applications of Artificial …, 2023 - Elsevier
In an actual industrial scenario, machines typically operate normally for the majority of the
time, with malfunctions occurring only occasionally. As a result, there is very little recorded …
time, with malfunctions occurring only occasionally. As a result, there is very little recorded …
Comparison of tool wear, surface roughness, cutting forces, tool tip temperature, and chip shape during sustainable turning of bearing steel
In this study, a comparison of measured cutting parameters is discussed while machining
AISI 52100 low-alloy hardened steel under two different sustainable cutting environments …
AISI 52100 low-alloy hardened steel under two different sustainable cutting environments …
Fault diagnosis of rolling bearing using CNN and PCA fractal based feature extraction
A novel adaptive decomposition algorithm based on CEEMDAN and fractal dimension is
proposed in this study to overcome limitations like redundancy and mode confusion in …
proposed in this study to overcome limitations like redundancy and mode confusion in …
Health monitoring of CNC machining processes using machine learning and wavelet packet transform
Monitoring the health of a machining process plays a crucial role in advancing fully
automated manufacturing. Faulty machining processes (abnormal process) leads to part …
automated manufacturing. Faulty machining processes (abnormal process) leads to part …
Indentation reverse algorithm of mechanical response for elastoplastic coatings based on LSTM deep learning
The load-penetration depth (P–h) curves of different metallic coating materials can be
determined by nanoindentation experiments, and it is a challenge to obtain stress–strain …
determined by nanoindentation experiments, and it is a challenge to obtain stress–strain …
Multi-scale one-dimensional convolution tool wear monitoring based on multi-model fusion learning skills
Effective tool wear monitoring (TWM) is crucial for accurately assessing the degree of tool
wear, guiding tool replacement during actual cutting processes, ensuring stable machine …
wear, guiding tool replacement during actual cutting processes, ensuring stable machine …
Early diagnosis of oral cancer using a hybrid arrangement of deep belief networkand combined group teaching algorithm
W Wang, Y Liu, J Wu - Scientific Reports, 2023 - nature.com
Oral cancer can occur in different parts of the mouth, including the lips, palate, gums, and
inside the cheeks. If not treated in time, it can be life-threatening. Incidentally, using CAD …
inside the cheeks. If not treated in time, it can be life-threatening. Incidentally, using CAD …
Motor on-line fault diagnosis method research based on 1D-CNN and multi-sensor information
Y Gu, Y Zhang, M Yang, C Li - Applied Sciences, 2023 - mdpi.com
The motor is the primary impetus source of most mechanical equipment, and its failure will
cause substantial economic losses and safety problems. Therefore, it is necessary to study …
cause substantial economic losses and safety problems. Therefore, it is necessary to study …