A novel approach towards the determination of the time to breakdown of electrical machine insulating materials

Author

Nyanteh, Yaw ; Graber, Lukas ; Srivastava, Sanjeev ; Edrington, Chris ; Cartes, David ; Rodrigo, Horatio

Author_Institution

Center for Adv. Power Syst., Florida State Univ., Tallahassee, FL, USA

Volume

22

Issue

1

fYear

2015

fDate

Feb. 2015

Firstpage

232

Lastpage

240

Abstract

This paper presents new approach to using Partial Discharge (PD) data for the prediction of the Remaining Useful Life (RUL) of dielectric materials undergoing breakdown. The method presented uses a thermodynamic macro-model in conjunction with an artificial neural network to associate the features in the PD data detected during breakdown to the electrical tree characteristics. The method is presented using electrical tree simulation data from a new dielectric breakdown simulation model. The simulation model is confirmed using experimental data.

Keywords

dielectric materials; electric machine analysis computing; electric machines; insulating materials; machine insulation; neural nets; partial discharges; remaining life assessment; thermodynamics; trees (electrical); PD data; RUL; artificial neural network; dielectric breakdown simulation model; dielectric materials; electrical machine insulating materials; electrical tree simulation data; partial discharge data; remaining useful life; thermodynamic macro-model; time to breakdown determination; Breakdown voltage; Dielectric materials; Equations; Insulation; Mathematical model; Partial discharges; Dielectrics; artificial neural network; electrical tree; partial discharge; remaining useful life;

fLanguage

English

Journal_Title

Dielectrics and Electrical Insulation, IEEE Transactions on

Publisher

ieee

ISSN

1070-9878

Type

jour

DOI

10.1109/TDEI.2014.004156

Filename

7033392