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Modelling and Simulation in Engineering
Volume 2016 (2016), Article ID 5949140, 12 pages
Research Article

Combined Diagnosis of PD Based on the Multidimensional Parameters

Department of Mechanical Engineering, Abadan Branch, Islamic Azad University, Abadan, Iran

Received 5 August 2016; Accepted 15 September 2016

Academic Editor: Aiguo Song

Copyright © 2016 Mohammad Heidari. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a comprehensive multiparameter diagnosis method based on multiple partial discharge (PD) signals which include high-frequency current (HFC), ultrasound, and ultrahigh frequency (UHF). The HFC, ultrasound, and UHF PD are calculated under different types of faults. Therefor the characteristic values, as nine basic characteristic parameters, eight phase characteristic parameters, and the like are calculated. Diagnose signals are found with the method based on information fusion and semisupervised learning for HFC PD, adaptive mutation parameters of particle entropy for ultrasonic signals, and IIA-ART2A neural network for UHF signals. In addition, integrate the diagnostic results, which are the probability of fault of various defects and matrix, of different PD diagnosis signals, and analysis with Sugeno fuzzy integral to get the final diagnosis.