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Ensemble Learning Approach to the Prediction of Gas Turbine Trip
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: In the field of gas turbine (GT) monitoring and diagnostics, GT trip is of great concern for manufactures and users. In fact, due to the number of issues that may cause a trip, its occurrence is not infrequent, and its ...
Detection of the Onset of Trip Symptoms Embedded in Gas Turbine Operating Data
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: One of the most disrupting events that affect gas turbine (GT) operation is trip, since its occurrence reduces machine life span and also causes business interruption. Thus, early detection of incipient symptoms of GT trip ...
Methodology to Monitor Early Warnings Before Gas Turbine Trip
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: The current energy scenario requires that gas turbines (GTs) operate at their maximum efficiency and highest reliability. Trip is one of the most disrupting events that reduces GT availability and increases maintenance ...
Development and Validation of a General and Robust Methodology for the Detection and Classification of Gas Turbine Sensor Faults
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Sensor fault detection and classification is a key challenge for machine monitoring and diagnostics, since raw data cleaning represents a key process in the gas turbine industry. To this end, this paper presents a comprehensive ...
Statistical Rule Extraction for Gas Turbine Trip Prediction
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: Gas turbine trip is an operational event that arises when undesirable operating conditions are approached or exceeded, and predicting its onset is a largely unexplored area. The application of novel artificial intelligence ...
Structured Methodology for Clustering Gas Turbine Transients by Means of Multivariate Time Series
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: At present, the challenges related to energy market force gas turbine owners to improve the reliability and availability of gas turbine engines, especially in the ever competitive Oil and Gas sector. Gas turbine trip leads ...
Capability of the Bayesian Forecasting Method to Predict Field Time Series
Publisher: The American Society of Mechanical Engineers (ASME)
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 ...
Prediction of Gas Turbine Trip: A Novel Methodology Based on Random Forest Models
Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: A gas turbine trip is an unplanned shutdown, of which the most relevant consequences are business interruption and a reduction of equipment remaining useful life. Thus, understanding the underlying causes of gas turbine ...
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