Fuzzy Logic Based Broken Bar Fault Diagnosis and Behavior Study of Induction Machine

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dc.contributor.authorIbrahim Chouidira
dc.contributor.authorDjalal Eddine Khodja
dc.contributor.authorSalim Chakroune
dc.date.accessioned2021-04-25T09:59:46Z
dc.date.available2021-04-25T09:59:46Z
dc.date.issued2021
dc.description.abstractThis study aims to display fuzzy logic (FL) technique for diagnosis of fault induction machine. This allows monitoring of fuzzy information from different signals to give more accurate judgment on the health of the engine, through using a multi-winding model of induction machine for the simulation of broken bars. This model allows study the influence of defects and appear the behavior of the machine in the different modes of running conditions (healthy and fault). In this work, we focus the application of a fuzzy logic technique based on the fast Fourier transformation (FFT) by analyzing the stator current for fault detection. The results of the simulation obtained allowed us to show the importance of the fuzzy logic approach based on classification of signals for detecting the faulty.en_US
dc.identifier.urihttp://dspace.univ-msila.dz:8080//xmlui/handle/123456789/24252
dc.publisherUniversité de M'silaen_US
dc.subjectinduction machine, detection, diagnosis, fuzzy logic, fast fourier transformationen_US
dc.titleFuzzy Logic Based Broken Bar Fault Diagnosis and Behavior Study of Induction Machineen_US
dc.typeArticleen_US

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