Resistant Statistical Methodologies for Anomaly Detection in Gas Turbine Dynamic Time Series: Development and Field Validation

Giuseppe Fabio Ceschini
Giuseppe Fabio Ceschini
Nicolò Gatta
Nicolò Gatta
Alin Murarasu
Alin Murarasu

JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME, no. 5 (2018): 052401

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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 are capable of removing anomalous measurements and improve data quality. To this purpose, statistical parametric meth...More

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