Fossil fuel power plants are a significant contributor to global carbon dioxide (CO2) and
nitrogen oxide (NOx) emissions. Accurate monitoring and effective reduction of these …

Society is going through transformations at a rate that is unprecedented in human history.
One such transformation is the energy transition, which will affect almost every facet of our …

Predictive emissions monitoring systems (PEMSs) are alternatives to continuous emissions
monitoring systems (CEMSs) for monitoring air pollutants, such as NO x. Existing PEMSs …

The reduction of NOx emissions is a paramount endeavor in contemporary engineering and
energy production, as these emissions are closely linked to adverse environmental and …

The study provides an overview of Predictive Emissions Monitoring System's (PEMS)
research, application, installation, and regulatory framework as well as develops predictive …

Predicting emissions for gas turbines is critical for monitoring harmful pollutants being
released into the atmosphere. In this study, we evaluate the performance of machine …

The main objective of this paper is to propose K-Nearest-Neighbor (KNN) algorithm for
predicting NOx emissions from natural gas electrical generation turbines. The process of …

In the context of Industry 4.0, an emerging trend is to increase the reliability of industrial
process by using machine learning (ML) to detect anomalies of production machines. The …

As gas turbine engine manufacturers strive to implement condition-based operation and
maintenance, there is a need for blade monitoring strategies capable of early fault detection …

We present Typhon, a new Deep Learning framework that trains a single model using
multiple, heterogeneous datasets leveraging parallel transfer. This aims to improve the …