The advances of intelligent fault diagnosis in recent years show that deep learning has
strong capability of automatic feature extraction and accurate identification for fault signals …

Prognosis and health management plays an important role in the control of costs associated
with operating large industrial equipment, such as wind turbines and aircraft. It is only fair …

As a critical component in agriculture, industry, and the military, pump anomaly detection
has recently aroused wide attention, which requires deep and abundant development and …

Using reinforcement learning (RL) for torque distribution of skid steering vehicles has
attracted increasing attention recently. Various RL-based torque distribution methods have …

Ensuring the safety and reliability of rotating machinery in modern industrial production and
intelligent manufacturing is of paramount importance. While deep learning-based fault …

There are two limitations in the existing researches based on data-driven fault diagnosis: 1)
the diversity of the original signal features is ignored; 2) the number of fault samples is …

Due to changes in model dynamics or unexpected disturbances, an autonomous robotic
system may experience unforeseen challenges during real-world operations which may …

Changes in model dynamics due to factors like actuator faults, platform aging, and
unexpected disturbances can challenge an autonomous robot during real-world operations …

Advancements in robotics have opened possibilities to automate tasks in various fields such
as manufacturing, emergency response and healthcare. However, a significant challenge …

Deep learning methods such as convolutional neural networks (CNN) have achieved state-
of-the-art success in a variety of medical imaging applications such as pathology …