Presenter(s)

    Salah Dauga

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    Description

    This poster deals with stator, bearing, and rotor fault detection of compressors for refrigeration. Mathematical modeling of compressors for refrigeration for healthy and stator , bearing, and rotor fault condition are explained. In this poster Artificial Neural Network technique is applied for stator, bearing, and rotor fault detection in compressors for refrigeration. By collecting the simulation data from the mathematical model developed in MATLAB simulink, based on: 1. Frequency. 2. Temperature. 3. vibration. The neural network can precisely detect the faults before any major problem occurs.

    Publication Date

    4-5-2017

    Project Designation

    Graduate Research - Graduate

    Primary Advisor

    Raul E. Ordonez

    Primary Advisor's Department

    Electrical and Computer Engineering

    Keywords

    Stander Symposium project

    Condition monitoring of Compressors for refrigeration

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