The adjuster position prediction in energy meter calibration system using fuzzy learning method

Author

Purnomo, Mauridhi Hery ; Wahyudiati ; Shigeta, Kazuo ; Shimizu, Eiji

Author_Institution

Sch. of Eng., Osaka City Univ., Japan

Volume

2

fYear

1996

fDate

1996

Firstpage

1289

Abstract

The calibration process of the electric energy meter can be improved by using a supervised learning neural network algorithm for computing and determining the exact position adjuster. In this paper we attempt to use a combination of a learning method with a fuzzy inference system to obtain a more intuitive tool as well as more skilful calibration. This method can be used to predict the position of the energy meter adjuster to fit in with the error of the energy meter under calibration

Keywords

adaptive control; calibration; energy measurement; error correction; fuzzy control; fuzzy logic; inference mechanisms; learning (artificial intelligence); measurement errors; multilayer perceptrons; power meters; adjuster position prediction; dynamic equation; electric energy meter; energy meter calibration system; error computation; error fitting; fuzzifier function; fuzzy inference system; fuzzy learning method; intuitive tool; steepest descent method; supervised learning neural network algorithm; three layer neural network; Calibration; Energy measurement; Equations; Fuzzy logic; Fuzzy systems; Learning systems; Neural networks; Power measurement; Temperature; Watthour meters;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 1996. IMTC-96. Conference Proceedings. Quality Measurements: The Indispensable Bridge between Theory and Reality., IEEE

Conference_Location

Brussels

Print_ISBN

0-7803-3312-8

Type

conf

DOI

10.1109/IMTC.1996.507579

Filename

507579