Abstract: Anomaly detection in sensor time series is a crucial aspect for raw data cleaning in gas turbine (GT) industry. In addition to efficiency, a successful methodology for industrial applications should be also characterized ...

Abstract: The reliability of gas turbine (GT) health state monitoring and forecasting depends on the quality of sensor measurements directly taken from the unit. Outlier detection techniques have acquired a major importance, as they ...

Abstract: Statistical parametric methodologies are widely employed in the analysis of time series of gas turbine (GT) sensor readings. These methodologies identify outliers as a consequence of excessive deviation from a statistical-based ...

Abstract: This paper addresses the challenge of forecasting the future values of gas turbine measureable quantities. The final aim is the simulation of “virtual sensors” capable of producing statistically coherent measurements aimed ...