Intelligent Diagnosis of Broken Bars in Induction Motors Based on New Features in Vibration Spectrum

Author

Sadoughi, Alireza ; Ebrahimi, Mohammad ; Moalem, Mehdi ; Sadri, Saeid

Author_Institution

Esfahan Univ. of Technol., Esfahan

fYear

2007

fDate

6-8 Sept. 2007

Firstpage

106

Lastpage

111

Abstract

This paper presents an intelligent method for diagnosing broken bars in induction motors. The method is based on training a neural network using new features extracted from vibration spectrum. These fault related features depend on slip. The exact value of slip can be determined using vibration spectrum; therefore, a vibration sensor is the only required sensor. The method has been able to diagnose correctly in all the laboratory tests.

Keywords

computerised instrumentation; fault diagnosis; induction motors; neural nets; power engineering computing; sensors; vibration measurement; broken bar intelligent diagnosis; fault diagnosis; induction motor; neural network; vibration sensor; vibration spectrum; Bars; Fault diagnosis; Feature extraction; Frequency estimation; Induction motors; Laboratories; Rotors; Stators; Synchronous motors; Vibration measurement; Broken Bar; Fault Diagnosis; Induction Motor; Intelligent; Vibration;

fLanguage

English

Publisher

ieee

Conference_Titel

Diagnostics for Electric Machines, Power Electronics and Drives, 2007. SDEMPED 2007. IEEE International Symposium on

Conference_Location

Cracow

Print_ISBN

978-1-4244-1061-3

Electronic_ISBN

978-1-4244-1062-0

Type

conf

DOI

10.1109/DEMPED.2007.4393079

Filename

4393079