Even before the COVID-19 pandemic, people spent on average around 90% of their time
indoors. Now more than ever, with work-from-home orders in place, it is crucial that we …

Flight data recorders provide large volumes of heterogeneous data from arrays of sensors
on-board to perform fault diagnosis. Challenges such as large data volumes, lack of labeled …

The vast installment of wind turbines and the development of condition monitoring system
provides large amounts of operational data for condition monitoring and health …

Non-intrusive load monitoring (NILM) of electrical demand for the purpose of identifying load
components has thus far mostly been studied using univariate data, eg, using only whole …

For several years now, smart building energy systems have been a research area of
intensive activity. In light of the increasing need for sustainable buildings and energy …

Combustion instability poses a negative impact on the performance and structural durability
of both land-based and aircraft gas turbine engines, and early detection of combustion …

In a majority of multivariate processes, propagating nature of malfunctions makes the fault
diagnosis a challenging task. This paper presents a novel data-driven strategy for real-time …

To satisfy the market, competition in the industrial sector aims for productivity and safety in
industrial plant control systems. The appearance of a fault can compromise the system's …

Entropy has long been a subject that has attracted researchers from a diverse range of
fields, including healthcare, finance, and fault detection. Slope entropy (SE) has recently …

Modern distributed cyber-physical systems (CPSs) encounter a large variety of physical
faults and cyber anomalies and in many cases, they are vulnerable to catastrophic fault …