Anomaly detection is a crucial aspect for both safety and efficiency of modern process
industries. This paper proposes a two-steps methodology for anomaly detection in industrial …

In the field of industrial process monitoring, scholars and practitioners are increasing interest
in time-varying processes, where different phases are implemented within an unknown time …

Multivariate analysis is an important kind of method in process monitoring and fault
detection, in which the canonical correlation analysis (CCA) makes use of the correlation …

The effect of gear contact state change due to shaft misalignment on meshing stiffness is
usually neglected in the traditional stiffness calculation model with misalignment error, the …

Most industrial batch processes involve inherent dynamic characteristics in both within-batch
time direction and batch-wise direction. In order to ensure process safety and improve …

Vibration analysis is widely used as an efficient condition monitoring (CM) tool for rotating
machines in various industries. Fault detection and diagnosis (FDD) models play an …

Fault feature extraction plays an important role in rotating machinery fault diagnosis. With
progress in the development of signal processing methods, more and more features can be …

The particle filter (PF) has been widely studied in the prognostics' field due to its ability to
deal with nonlinear and non-stationary systems. However, there is no update of the model …

Recent advances in sensor technology and computing capabilities have enabled the
creation of data-driven models that can support real-time decision making. Such a decision …

Momentum wheel bearing is a critical component within satellite systems, and its condition
monitoring not only extends the operational lifespan of the satellite but also ensures the …