Towards the future of smart electric vehicles: Digital twin technology
Worldwide, transportation accounts for 18% of global carbon dioxide emissions (as of 2019).
In order to battle the impending threat of climate change, consumers and industry must …
In order to battle the impending threat of climate change, consumers and industry must …
A comprehensive review on convolutional neural network in machine fault diagnosis
With the rapid development of manufacturing industry, machine fault diagnosis has become
increasingly significant to ensure safe equipment operation and production. Consequently …
increasingly significant to ensure safe equipment operation and production. Consequently …
A review on fault detection and diagnosis techniques: basics and beyond
Safety and reliability are absolutely important for modern sophisticated systems and
technologies. Therefore, malfunction monitoring capabilities are instilled in the system for …
technologies. Therefore, malfunction monitoring capabilities are instilled in the system for …
Understanding and learning discriminant features based on multiattention 1DCNN for wheelset bearing fault diagnosis
Recently, deep-learning-based fault diagnosis methods have been widely studied for rolling
bearings. However, these neural networks are lack of interpretability for fault diagnosis …
bearings. However, these neural networks are lack of interpretability for fault diagnosis …
Central frequency mode decomposition and its applications to the fault diagnosis of rotating machines
To overcome current challenges in variational mode decomposition (VMD) and its variants
for the fault diagnosis of rotating machines, the decomposing characteristics of two sub …
for the fault diagnosis of rotating machines, the decomposing characteristics of two sub …
Multibranch and multiscale CNN for fault diagnosis of wheelset bearings under strong noise and variable load condition
The critical issue for fault diagnosis of wheel-set bearings in high-speed trains is to extract
fault features from vibration signals. To handle high complexity, strong coupling, and low …
fault features from vibration signals. To handle high complexity, strong coupling, and low …
Coupling fault diagnosis of wind turbine gearbox based on multitask parallel convolutional neural networks with overall information
With the development of smart grid, capacity of wind power that connects to the grid
increases gradually, which makes the continuous and stable operation of wind turbine (WT) …
increases gradually, which makes the continuous and stable operation of wind turbine (WT) …
Novel three-stage feature fusion method of multimodal data for bearing fault diagnosis
D Wang, Y Li, L Jia, Y Song… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Bearing faults are among the most common causes of machine failures. Therefore, bearing
fault diagnosis should be performed reliably and rapidly. Currently, many types of modal …
fault diagnosis should be performed reliably and rapidly. Currently, many types of modal …
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 …
Digital twin for propulsion drive of autonomous electric vehicle
Autonomous driving is no longer just an idea of technology vision, instead a real technical
trend all over the world. The continuing development to a further level of autonomy requires …
trend all over the world. The continuing development to a further level of autonomy requires …