Adjuster position prediction in energy meter calibration system using fuzzy learning method

Mauridhi Hery Purnomo*, Kazuo Shigeta, Eiji Shimizu

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

8 Citations (Scopus)

Abstract

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

Original languageEnglish
Pages1289-1291
Number of pages3
Publication statusPublished - 1996
Externally publishedYes
EventProceedings of the Joint 1996 IEEE Instrumentation and Measurement Technology Conference & IMEKO Technical Committee 7. Vol 1 (of 2) - Brussels, Belgium
Duration: 4 Jun 19966 Jun 1996

Conference

ConferenceProceedings of the Joint 1996 IEEE Instrumentation and Measurement Technology Conference & IMEKO Technical Committee 7. Vol 1 (of 2)
CityBrussels, Belgium
Period4/06/966/06/96

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