The Internet of Things (IoT) is significantly transforming the maritime industry, enabling the
generation of vast amounts of data that can drive operational efficiency, safety, and …

Prognostics and health management (PHM) are developed to accurately estimate the state
of health (SOH) of lithium-ion batteries, which are crucial parts for planning the employment …

Meta-learning has effectively addressed the limit of deep learning fault diagnosis models
that demands a large number of samples. However, existing meta-learning models lack the …

In severe data imbalance scenarios, fault samples are generally scarce, challenging the
health management of industrial machinery significantly. Generative adversarial network …

As failure data is usually scarce in practice upon preventive maintenance strategy in
prognostics and health management (PHM) domain, transfer learning provides a …

The maturation of sensor network technologies has promoted the emergence of the
Industrial Internet of Things, which has been collecting an increasing volume of monitoring …

Real-time motor fault diagnosis can detect motor faults on time and prompt the repair or
replacement of faulty motors, which minimizes the potential losses caused by motor faults …

The current deep learning-based intelligent diagnosis algorithms depend on large amounts
of well-labeled data, but they may not perform well in engineering practice where the fault …

In recent years, deep learning (DL)-based fault diagnosis methods have witnessed
significant advancements and successful applications in engineering practice. However, the …

Sensing is the fundamental technique for sensor data acquisition in monitoring the operation
condition of the machinery, structures and manufacturing processes. In this paper, we briefly …