Non-Intrusive Efficiency Determination of In-Service Induction Motors using Genetic Algorithm and Air-Gap Torque Methods

Author

Lu, Bin ; Cao, Wenping ; French, Ian ; Bradley, Keith J. ; Habetler, Thomas G.

Author_Institution

Eaton Corp., Milwaukee

fYear

2007

Firstpage

1186

Lastpage

1192

Abstract

In-service testing poses particular difficulties for experimentally determining induction machine efficiency. This paper focuses on non-intrusive methods for testing in-service machines and proposes a hybrid method based on the air-gap torque method and genetic algorithms. The proposed method has been verified from the experimental results from three induction motors rated at 7.5 hp, 100 hp and 225 kW. The overall efficiency estimation accuracy is approximately within 4-5% errors.

Keywords

genetic algorithms; induction motors; torque motors; air gap torque methods; efficiency estimation accuracy; genetic algorithm; hybrid method; in service induction motors; induction machine efficiency; non intrusive methods; nonintrusive efficiency determination; power 225 kW; Air gaps; Circuit testing; Electrical resistance measurement; Genetic algorithms; Induction machines; Induction motors; Parameter estimation; Power generation; Stators; Torque measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Industry Applications Conference, 2007. 42nd IAS Annual Meeting. Conference Record of the 2007 IEEE

Conference_Location

New Orleans, LA

ISSN

0197-2618

Print_ISBN

978-1-4244-1259-4

Electronic_ISBN

0197-2618

Type

conf

DOI

10.1109/07IAS.2007.186

Filename

4347935