A novel method for induction motors stator inter-turn short circuit fault diagnosis based on wavelet energy and neural network

Autor:	Mohamed Boumehraz, Hakima Cherif, B. Bessam, Arezki Menacer
Rok vydání:	2015
Předmět:	Engineering Artificial neural network business.industry Stator Computer Science::Neural and Evolutionary Computation Fast Fourier transform Backpropagation Fault detection and isolation law.invention Wavelet law Electronic engineering business Algorithm Energy (signal processing) Induction motor
Zdroj:	2015 IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED).
DOI:	10.1109/demped.2015.7303682
Popis:	This paper presents a wavelet neural network technique for the inter turn short-circuit fault detection and location of the induction machine at non stationary state. This technique is used in order to remedy the problem from using the classical signal-processing (FFT). This method is based from using the discrete wavelet energy (DWE) as the input for the neural network (NN). The fault detection and location are achieved by a feed-forward multilayer-perceptron neural network trained by back propagation. Simulation results are presented to illustrate the effectiveness of the proposed method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::e51159e25b266dee47a0d9ca04e4b7e4 https://doi.org/10.1109/demped.2015.7303682 Zobrazit plný text záznamu