The SOM tool in mechanical fault detection over an electric asynchronous drive

This paper presents a rotor bars Modeling. The rotor of an Electrical asynchronous machine is modeled by an equivalent electrical diagram related to the squirrel-cage connected together electrically and coupled magnetically, the frequencies characteristics of fault break bars. An intelligent strategy was adopted for fault detection in rotor using the map SOM (Self Organizing Map). It involves the most significant parameters of SOM, such as the topological structure of the map, the Kohonen learning algorithm, and also the activity diagram UML (Unified Modeling Language). Eventually, the measurement of the stator current on the experimental bench at a specific moment in the NDC (Non Destructive Control) Laboratory was applied. A comparative study of the fault detection performance was conducted under the SOM neural map and the spectral analysis method. It will be a more synthetic analysis.