Rapid monitoring of indoor air quality for efficient HVAC systems using fully convolutional network deep learning model
S Shin, K Baek, H So - Building and Environment, 2023 - Elsevier
Indoor air quality (IAQ) monitoring technology is crucial for achieving optimized heating,
ventilation, and air conditioning (HVAC) strategies for efficient energy management. In this …
ventilation, and air conditioning (HVAC) strategies for efficient energy management. In this …
Adaptive knowledge transfer by continual weighted updating of filter kernels for few-shot fault diagnosis of machines
Deep learning (DL) based diagnosis models have to be trained by large quantities of
monitoring data of machines. However, in real-case scenarios, machines operate under the …
monitoring data of machines. However, in real-case scenarios, machines operate under the …
Fault Diagnosis using eXplainable AI: A transfer learning-based approach for rotating machinery exploiting augmented synthetic data
Due to the growing interest for increasing productivity and cost reduction in industrial
environment, new techniques for monitoring rotating machinery are emerging. Artificial …
environment, new techniques for monitoring rotating machinery are emerging. Artificial …
Gear pitting fault diagnosis with mixed operating conditions based on adaptive 1D separable convolution with residual connection
Gear pitting fault diagnosis has always been an important subject to industry and research
community. In the past, the diagnosis of early gear pitting faults has usually been carried out …
community. In the past, the diagnosis of early gear pitting faults has usually been carried out …
Towards a fault diagnosis method for rolling bearing with Bi-directional deep belief network
J Tang, J Wu, B Hu, J Liu - Applied Acoustics, 2022 - Elsevier
Intelligent fault diagnosis model based on machine learning algorithm has extensive
application, while the unsatisfied training data quality leads to the lower accuracy of …
application, while the unsatisfied training data quality leads to the lower accuracy of …
Prognostics and health management of rotating machinery of industrial robot with deep learning applications—A review
The availability of computational power in the domain of Prognostics and Health
Management (PHM) with deep learning (DL) applications has attracted researchers …
Management (PHM) with deep learning (DL) applications has attracted researchers …
Bearing fault detection using scalogram and switchable normalization-based CNN (SN-CNN)
Bearings play a vital role in all rotating machinery, and their failure is one of the significant
causes of machine breakdown leading to a profound loss of safety and property. Therefore …
causes of machine breakdown leading to a profound loss of safety and property. Therefore …
Deep learning-based adversarial multi-classifier optimization for cross-domain machinery fault diagnostics
Despite the recent success in data-driven machinery fault diagnosis, cross-domain
diagnostic tasks still remain challenging where the supervised training data and …
diagnostic tasks still remain challenging where the supervised training data and …
Multi-level features fusion network-based feature learning for machinery fault diagnosis
Bearings are one of the most critical components in rotating machinery. Since the failures of
bearings will cause unexpected machine damages, it is significant to timely and accurately …
bearings will cause unexpected machine damages, it is significant to timely and accurately …
Combinatorial synthesis and analysis of AlxTayVz-Cr20Mo20Nb20Ti20Zr10 and Al10CrMoxNbTiZr10 refractory high-entropy alloys: Oxidation behavior
The combinatorial development of refractory high-entropy alloy Al x Ta y V z-Cr 20 Mo 20 Nb
20 Ti 20 Zr 10 (Al x Ta y V zQ) was carried out, and microstructural analysis was performed …
20 Ti 20 Zr 10 (Al x Ta y V zQ) was carried out, and microstructural analysis was performed …