Sampling rate of digital fault recorders influence on fault diagnosis

Author

Neves, W.L.A. ; Brito, N.S.D. ; Souza, B.A. ; Fontes, A.V. ; Dantas, K.M.C. ; Fernandes, A.B. ; Silva, S.S.B.

Author_Institution

Dept. of Electr. Eng., Fed. Univ. of Campina Grande, Brazil

fYear

2004

fDate

8-11 Nov. 2004

Firstpage

406

Lastpage

411

Abstract

A case study of fault classification in transmission lines using artificial neural networks (ANN) is presented. The database is built from current and voltage waveform samples obtained from fault simulations with the ATP. Utility companies usually have digital fault recorders with different sampling rates, so it is important to evaluate how good the classifier is when the sampling rate changes, this is the main purpose of the paper. A routine to reduce the sampling rate with no loss of accuracy in classifying faults was implemented.

Keywords

data loggers; fault diagnosis; fault simulation; neural nets; power system simulation; power transmission faults; power transmission lines; waveform analysis; ANN; artificial neural networks; current waveform; digital fault recorders; electric power systems; fault diagnosis; fault simulations; oscillographical analysis; sampling rate; transmission lines; utility company; voltage waveform; Artificial neural networks; Data engineering; Fault diagnosis; Frequency; Power transmission lines; Protection; Research and development; Sampling methods; Substations; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Transmission and Distribution Conference and Exposition: Latin America, 2004 IEEE/PES

Print_ISBN

0-7803-8775-9

Type

conf

DOI

10.1109/TDC.2004.1432414

Filename

1432414