The search for effective asset utilization has been constant, especially in industries with
evolving mechanization. In this context, maintenance management gains visibility because it …

Bearing fault diagnosis is an important part of rotating machinery maintenance. Existing
diagnosis methods based on single-modal signals not only have unsatisfactory accuracy …

Accurate prediction of remaining useful life (RUL) has been a critical and challenging
problem in the field of prognostics and health management (PHM), which aims to make …

Vibration signals and infrared images have different advantages and characteristics.
Although a few recent researches have explored their information fusion in rotating …

Early identification of rolling element defects is always a topic of interest for researchers and
the industry. For early fault identification, a simple and effective dynamic degradation …

Condition monitoring and fault diagnosis of bearings play important roles in production
safety and limiting the cost of maintenance on a reasonable level. Nowadays, artificial …

Catastrophic forgetting of learned knowledges and distribution discrepancy of different data
are two key problems within fault diagnosis fields of rotating machinery. However, existing …

Rotating machines are extensively utilized in diverse industries, and their malfunctions can
result in significant financial consequences and safety risks. Consequently, there has been …

Anomaly detection is one of the most fundamental and indispensable components in
predictive maintenance. In this article, anomaly detection is modeled as a one-class …

Tool wear monitoring during the cutting process is crucial for ensuring part quality and
productivity. A data-driven monitoring approach based on radar map feature fusion is …