DocumentCode
3000976
Title
Specialist tool for monitoring the measurement degradation process of induction active energy meters
Author
Silva, M.R. ; Galotto, L., Jr. ; Pinto, J.O.P. ; Canesin, C.A. ; Cardoso, E.H., Jr. ; Amorim, S. ; Mertens, E.A., Jr.
Author_Institution
Sao Paulo State Univ. - UNESP, Sao Paulo, Brazil
fYear
2011
fDate
17-19 Oct. 2011
Firstpage
1
Lastpage
6
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.
Keywords
computerised monitoring; electricity supply industry; expert systems; failure analysis; human computer interaction; power engineering computing; power meters; probability; risk analysis; sampling methods; watthour meters; Delphi language; automatic sampling; distribution company; failure probability analysis; geographical localization; induction active energy meters; induction type watt-hour meters; measurement degradation process monitoring; metering park database; risk analysis; risk classification expert system; user friendly platform; Companies; Data mining; Data models; Databases; Decision trees; Expert systems; Watthour meters; Artificial intelligence; Expert system for sampling; Hazard rate; Induction type Watt-hour meters; Risk Model;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical Power Quality and Utilisation (EPQU), 2011 11th International Conference on
Conference_Location
Lisbon
ISSN
2150-6647
Print_ISBN
978-1-4673-0379-8
Type
conf
DOI
10.1109/EPQU.2011.6128831
Filename
6128831
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