Specialist tool for monitoring the measurement degradation process of induction active energy meters

M. R. Silva, L. Galotto, J. O.P. Pinto, C. A. Canesin, E. H. Cardoso, S. Amorim, E. A. Mertens

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper presents a methodology and a specialist tool for failure probability analysis of induction type watt-hour meters, considering the main variables related to their measurement degradation processes. The database of the metering park of a distribution company, named Elektro Electricity and Services Co., was used for determining the most relevant variables and to feed the data in the software. The modeling developed to calculate the watt-hour meters probability of failure was implemented in a tool through a user friendly platform, written in Delphi language. Among the main features of this tool are: analysis of probability of failure by risk range; geographical localization of the meters in the metering park, and automatic sampling of induction type watt-hour meters, based on a risk classification expert system, in order to obtain information to aid the management of these meters. The main goals of the specialist tool are following and managing the measurement degradation, maintenance and replacement processes for induction watt-hour meters.

Original languageEnglish
Title of host publication11th International Conference on Electrical Power Quality and Utilisation, EPQU 2011
Pages541-546
Number of pages6
DOIs
StatePublished - 2011
Externally publishedYes
Event11th International Conference on Electrical Power Quality and Utilisation, EPQU 2011 - Lisbon, Portugal
Duration: Oct 17 2011Oct 19 2011

Publication series

NameProceeding of the International Conference on Electrical Power Quality and Utilisation, EPQU
ISSN (Print)2150-6647
ISSN (Electronic)2150-6655

Conference

Conference11th International Conference on Electrical Power Quality and Utilisation, EPQU 2011
Country/TerritoryPortugal
CityLisbon
Period10/17/1110/19/11

Keywords

  • Artificial intelligence
  • Expert system for sampling
  • Hazard rate
  • Induction type Watt-hour meters
  • Risk Model

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