Due to the advances in the digitalization process of the manufacturing industry and the
resulting available data, there is tremendous progress and large interest in integrating …

In a carbon-constrained world, future uses of nuclear power technologies can contribute to
climate change mitigation as the installed electricity generating capacity and range of …

Data-based process monitoring has become a key technology in process industries for
safety, quality, and operation efficiency enhancement. This paper provides a timely update …

Early detection of incipient faults in industrial processes is increasingly becoming important,
as these faults can slowly develop into serious abnormal events, an emergency situation, or …

Multivariate statistical process monitoring (MSPM) methods are significant for improving
production efficiency and enhancing safety. However, to the authors' best knowledge, there …

Accident prevention is one of the most desired and challenging goals in process industries.
For accident prevention, fault detection and diagnosis (FDD) is critical. FDD has been an …

There are more and more bearing fault types under considering the fault location and
degree, and the corresponding fault classification task is becoming increasingly heavy. Raw …

Independent component analysis (ICA) is a commonly used non-Gaussian process fault
diagnosis method. A fault detection algorithm of kernel dynamic ICA (KDICA) has been …

This paper proposes a novel approach for dealing with fault detection of multivariate
processes, which will be referred to as kernel dynamic independent component analysis …

Data-driven models require high-fidelity data of sufficient quantity and granularity. This is
challenging in a complex chemical processing system due to frequent sensor breakdown …