An Accurate Approach for Automatic Segmentation of Power Distribution Voltage Waveforms

This paper addresses one of the fundamental steps in automatic waveform analysis: transient segmentation. We present a new approach which incorporates the advantages of a multilevel wavelet decomposition and the representation of the support vector data description. Real data from a monitoring syste...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on power delivery 2015-06, Vol.30 (3), p.1611-1619
Main Authors: Lazzaretti, Andre E., Vieira Neto, Hugo, Ferreira, Vitor H.
Format: Article
Language:English
Subjects:
Automatic waveform analysis
Discrete wavelet transforms
Estimation
novelty detection
oscillography segmentation
support vector data description
Support vector machines
Time-frequency analysis
Transient analysis
transient segmentation
wavelet transform
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper addresses one of the fundamental steps in automatic waveform analysis: transient segmentation. We present a new approach which incorporates the advantages of a multilevel wavelet decomposition and the representation of the support vector data description. Real data from a monitoring system developed for lightning overvoltage detection in overhead distribution power lines was used for comparison and validation of segmentation performance. The experiments involve the proposed segmentation approach and usual segmentation methods, such as Kalman filtering, autoregressive models, and standard discrete wavelet transform. The results show that the proposed segmentation method based on DWT+SVDD yields better overall accuracy for transient segmentation when compared to currently used methods, demonstrating the potential for applications in oscillographic recorders for smart distribution networks, where identification, characterization, and mitigation of events are critical for network operation and maintenance.
ISSN:0885-8977
1937-4208
DOI:10.1109/TPWRD.2015.2410173