Data Mining Applications in the Electrical Industry-Reference-Cited by-同舟云学术

Data Mining Applications in the Electrical Industry

Published:2012 Issue: Volume: Page:380-402
ISSN:
Container-title:Logistics Management and Optimization through Hybrid Artificial Intelligence Systems
language:
Short-container-title:

Author:

Vacio Rubén Jaramillo¹,Ortiz Zezzatti Carlos Alberto Ochoa²,Rios Armando³

Affiliation:

1. CFE – LAPEM & CIATEC – CONACYT, Mexico

2. Juarez City University, México

3. Institute Technologic of Celaya, Mexico

Abstract

This chapter describes the experimental study partial discharges (PD) activities with artificial intelligent tools. The results present different patterns using a hybrid system with Self Organizing Maps (SOM) and Hierarchical clustering, this combination constitutes an excellent tool for exploration analysis of massive data such a partial discharge on underground power cables and electrical equipment. The SOM has been used for nonlinear feature extraction and the hierarchical clustering to visualization. The hybrid system is trained with different dataset using univariate phase-resolved distributions. The results show that the clustering method is fast, robust, and visually efficient.

Publisher

IGI Global

Reference22 articles.

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