Process monitoring technologies play a key role in maintaining the steady state of industrial
processes. However, with the increasing complexity of modern industrial processes …

Recently, to ensure the reliability and safety of high-speed trains, detection and diagnosis of
faults (FDD) in traction systems have become an active issue in the transportation area over …

The study focuses on examining the impact of R&D and industrialization on green economic
growth. Financial assistance for environmentally friendly initiatives, the advancement of new …

Anomaly detection is crucial to ensure the security of cyber-physical systems (CPS).
However, due to the increasing complexity of CPSs and more sophisticated attacks …

Deep learning networks have been recently utilized for fault detection and diagnosis (FDD)
due to its effectiveness in handling industrial process data, which are often with high …

Process fault detection and diagnosis (FDD) is a predominant task to ensure product quality
and process reliability in modern industrial systems. Those traditional FDD techniques are …

Numerous accidents in chemical processes have caused emergency shutdowns, property
losses, casualties and/or environmental disruptions in the chemical process industry. Fault …

Effective fault diagnosis has long been a research topic in the prognosis and health
management of rotary machinery engineered systems due to the benefits such as safety …

The main roles of fault detection and diagnosis (FDD) for industrial processes are to make
an effective indicator which can identify faulty status of a process and then to take a proper …

Principal component analysis (PCA) has been widely applied for data modeling and process
monitoring. However, it is not appropriate to directly apply PCA to data from a dynamic …