An intelligent icons approach for rotor bar fault detection

Author

Karvelis, Petros ; Tsoumas, I.P. ; Georgoulas, George ; Stylios, Chrysostomos D. ; Antonino-Daviu, J.A. ; Climente-Alarcon, Vicente

Author_Institution

Dept. of Applic. of Inf. Technol. in Adm. & Econ., Technol. & Educ. Inst. of Ionian Islands, Lefkada, Greece

fYear

2013

fDate

10-13 Nov. 2013

Firstpage

5526

Lastpage

5531

Abstract

In this paper we propose the use of Intelligent Icons for both automatic assessment and representation of asynchronous machines´ condition. The method focuses on the analysis of the start-up current for the isolation of a component that is able to pinpoint faulty signatures. The analysis is based on the application of Empirical Mode Decomposition (EMD) which acts as an adaptive filter during the start up and subsequently on the application of Symbolic Aggregate approXimation (SAX) for the transformation of the extracted component into a symbolic representation. Using this symbolic representation, an automated detection procedure can be developed that discriminates between faulty and normal conditions using an intelligent Icons approach while at the same time the information can be presented to the user in a more intuitive way.

Keywords

asynchronous machines; fault diagnosis; rotors; EMD; asynchronous machines; empirical mode decomposition; intelligent icons; rotor bar fault detection; start-up current; symbolic aggregate approximation; Aggregates; Approximation methods; Bars; Induction motors; Rotors; Stators; Time series analysis; Empirical Mode Decomposition; Intelligent Icons; Symbolic Aggregate approXimation; sympolic representation;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE

Conference_Location

Vienna

ISSN

1553-572X

Type

conf

DOI

10.1109/IECON.2013.6700038

Filename

6700038