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This paper investigates the impact of power electronics converter when attempting wind turbine condition monitoring system and fault diagnosis by the analysis of fault signatures in the electrical output of the turbine. A wind turbine model has been implemented in the MATLAB/Simulink environment. Fault signature analysis for electrical signals is presented. A signal processing algorithm based on a...
This paper aims at proposing an effective approach, based on neural networks, to the fault diagnosis of Class-E DC-AC resonant inverters. A MultiLayer artificial Neural Network based on MultiValued Neuron (MLMVN) with a complex QR-decomposition is used to identify parameter value changing (i.e. fault detection) on a Class-E resonant inverter through steady state measurements of voltages and currents.
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