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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