Abstract Predictive Maintenance (PdM) has continually attracted interest from the
manufacturing community due to its significant potential in reducing unexpected machine …

Due to the strategic importance of satellites, the safety and reliability of satellites have
become more important. Sensors that monitor satellites generate lots of multivariate time …

Abstract Space anomaly detection plays a critical role in safeguarding the integrity and
reliability of space systems amid the rising tide of threats. This survey aims to deepen …

Anomaly detection on multivariate time series (MTS) is of great importance in both data
mining research and industrial applications. While a handful of anomaly detection models …

Efficient and feasible anomaly detection scheme that could utilize data collected by
supervisory-control-and-data-acquisition (SCADA) system is essential for wind turbines …

The class imbalance problem is prevalent in the condition monitoring (CM) data of marine
diesel engines. That significantly deteriorates the diagnostic performance of a data-driven …

The performance and reliability of turbomachinery directly affect the efficiency and safety of
energy conversion systems. A dual graph neural network (DGNN) for turbomachinery flow …

For data-driven anomaly detection, it is difficult to model a prediction model with high
accuracy and sensitivity to anomalous states. In order to solve the above problems, this …

Anomaly detection is a crucial matter to ensure the spacecraft stability. During the spacecraft
operation, sensors and controllers generate a large volume of multidimensional time series …

With the development of Internet of Vehicles (IoVs) techniques, many emerging technologies
and their applications are integrated with IoVs. The application of these new technologies …