Momentous increase in the popularity of explainable machine learning models coupled with
the dramatic increase in the use of synthetic data facilitates us to develop a cost-efficient …

The ultimate goal of most prognostic systems is accurate prediction of the remaining useful
life (RUL) of individual systems or components based on their use and performance. This …

As condition-based maintenance (CBM) has risen as a new trend, there has been an active
movement to apply information technology for effective implementation of CBM in power …

Data mining is the analytics and knowledge discovery process of analyzing large volumes of
data from various sources and transforming the data into useful information. Various …

Sensors health monitoring is essentially important for reliable functioning of safety‐critical
chemical and nuclear power plants. Autoassociative neural network (AANN) based …

As interest in safety and performance of power plants becomes more serious and wide-
ranging, the significance of research on turbine cycles has attracted more attention. This …

This paper presents an approach for the detection of the degradation onset and the
identification of the degradation state of industrial components with inhomogeneous …

The general path model (GPM) is one approach for performing degradation-based, or Type
III, prognostics. The GPM fits a parametric function to the collected observations of a …

Early detection of significant abnormal changes is highly desirable for oil refinery processes,
which consist of sophisticated unit operations handling hazardous and flammable …

The Venturi flow meters that are being used to measure the feedwater flow rate in most
pressurized water reactors are confronted with fouling phenomena, resulting in an …