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Fault detection of switches in multilevel inverter using wavelet and neural network

机译:基于小波和神经网络的多电平逆变器开关故障检测

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A Multilevel Inverter (MLI) with an advantage of low Total Harmonic Distortion (THD) is appropriate for the grid integration of solar photovoltaic power plants but the high number of switches makes them prone to failures affecting their reliability. In this paper a comprehensive outlook of fault diagnosis method along with practical implementation of 5 level Cascaded H-Bridge Multilevel (CHBMLI) is done. An algorithm is developed based on the output of CHBMLI. The operating range of input voltage to CHBMLI for proper working of algorithm is determined and an attempt is made to determine the operating range for a neural network based fault detection.
机译:具有低总谐波失真(THD)优势的多电平逆变器(MLI)适用于太阳能光伏电站的电网集成,但是开关数量众多,使它们易于出现故障,从而影响其可靠性。本文对故障诊断方法进行了全面的展望,并结合了5级层叠H桥多级(CHBMLI)的实际实现。基于CHBMLI的输出,开发了一种算法。确定用于算法的正确工作的输入到CHBMLI的输入电压的工作范围,并尝试确定基于神经网络的故障检测的工作范围。

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