Event-based cameras are the emerging bioinspired technology in vision sensing. Different
from the traditional standard cameras, the event-based cameras asynchronously record the …

In the era of the fourth industrial revolution (Industry 4.0) and the Internet of Things (IoT), real-
time data is enormously collected and analyzed from mechanical equipment. By classifying …

In most current intelligent diagnosis methods, fault classifiers of electric machine are built
based on complex handcrafted features extractor from raw signals, which depend on prior …

Being able to detect, identify, and diagnose a fault is a key feature of industrial supervision
systems, which enables advance asset management, in particular, predictive maintenance …

Feature extraction from a time sequence signal without manual information is an important
part for bearing intelligent diagnosis. With the merits of signal information and feature …

We develop a novel deep learning framework to achieve highly accurate machine fault
diagnosis using transfer learning to enable and accelerate the training of deep neural …

In recent years, the rapid development of convolutional neural networks (CNNs) has
significantly advanced the progress of intelligent fault diagnosis. Most currently-available …

Recently, numerous new data-driven methods have been proposed. But most of them
focused on the innovation of models and algorithms, and rarely discussed and optimized …

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …

To realize high‐precision and high‐efficiency machine fault diagnosis, a novel deep
learning framework that combines transfer learning and transposed convolution is proposed …