THREE-LEVEL INVERTER FAULT DIAGNOSIS METHOD BASED ON EMPIRICAL MODE DECOMPOSITION AND DECISION TREE RVM

摘要

A diode neutral point clamped three-level inverter fault diagnosis method based on empirical mode decomposition and a decision tree RVM comprises: for a diode neutral point clamped three-level inverter fault diagnosis problem in a photovoltaic power generation system, firstly analyzing the operation condition of an inverter main circuit and performing fault classification; then extracting each signal component by means of an empirical mode decomposition method by using upper, middle and lower bridge arm voltages as measurement signals, and then calculating the corresponding energy and energy entropy, thus generating a decision tree RVM classification model using a particle swarm clustering algorithm, and finally realizing the fault diagnosis of the photovoltaic diode neutral point clamped three-level inverter. In the diode neutral point clamped three-level inverter fault diagnosis method based on empirical mode decomposition and a decision tree RVM, there is no need to set parameters, the number of classification models is relatively small, the operation efficiency is high and the diagnosis precision is high, and the robustness is strong.