In this paper, we present an expert diagnostic system for the interpretation of four different categories of system’s functioning based on an innovative feature extraction tequiniques and a Probabilistic Neural Network for the classification of events identifying failures that can occur during in a high-concentration photovoltaic (HCPV) system located in Fleri, Sicily (Italy). In this paper we have considered four different categories of system’s functioning: sun tracking system malfunction, cloudy conditions and temperature sensor malfunction, darkness and night time, normal functioning.
Failure classification in high concentration photovoltaic system (HCPV) by using probabilistic neural networks
Capizzi G.;Famoso F.;
2017-01-01
Abstract
In this paper, we present an expert diagnostic system for the interpretation of four different categories of system’s functioning based on an innovative feature extraction tequiniques and a Probabilistic Neural Network for the classification of events identifying failures that can occur during in a high-concentration photovoltaic (HCPV) system located in Fleri, Sicily (Italy). In this paper we have considered four different categories of system’s functioning: sun tracking system malfunction, cloudy conditions and temperature sensor malfunction, darkness and night time, normal functioning.File in questo prodotto:
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