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Fault diagnosis method of three-level inverter based on empirical mode decomposition and decision tree RVM

机译:基于经验模式分解和决策树RVM的三电平逆变器故障诊断方法

摘要

Disclosed is a fault diagnosis method of a three-level inverter based on an empirical mode decomposition and a decision tree RVM, in view of fault diagnosis problems of a diode neutral-point-clamped three-level inverter in a photovoltaic power generation system, first of all, analysing operating conditions of an inverter main circuit and performing fault classification; extracting each signal component with the empirical mode decomposition method by taking the middle, upper and lower bridge leg voltages as measurement signals; calculating corresponding parameters, such as an energy and an energy entropy; thereby generating a decision tree RVM classification model with a particle swarm clustering algorithm, to finally achieve multi-mode fault diagnosis of the photovoltaic diode neutral-pointclamped three-level inverter. Advantages of the present invention are that, setting of parameters is not needed, the number of classification models is small, both a calculating efficiency and a diagnosis precision are high, and the robustness is good.
机译:鉴于光伏发电系统中二极管中性点钳位的三电平逆变器的故障诊断问题,首先公开了一种基于经验模式分解和决策树RVM的三电平逆变器的故障诊断方法。首先,分析逆变器主电路的工作状况并进行故障分类;以中,上,下桥臂电压为测量信号,采用经验模式分解法提取各个信号分量。计算相应的参数,例如能量和能量熵;从而用粒子群聚类算法生成决策树RVM分类模型,最终实现光伏二极管中性点钳位三电平逆变器的多模式故障诊断。本发明的优点是不需要参数设置,分类模型数量少,计算效率和诊断精度均很高,鲁棒性好。

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