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首页> 外文期刊>International Journal of Applied Engineering Research >Failure Classification in High Concentration Photovoltaic System (HCPV) by using Probabilistic Neural Networks
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Failure Classification in High Concentration Photovoltaic System (HCPV) by using Probabilistic Neural Networks

机译:利用概率神经网络,高浓度光伏系统(HCPV)中的故障分类

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摘要

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.
机译:在本文中,我们基于创新特征提取Tequiniques和概率神经网络来阐述四种不同类别的系统功能的专家诊断系统,用于识别在高浓度光伏( HCPV)系统位于Sicily(意大利)的Fleri。 在本文中,我们考虑了四种不同类别的系统功能:太阳跟踪系统故障,多云条件和温度传感器故障,黑暗和夜间,正常运行。

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