Transformer Fault Diagnosis Based on BP-Adaboost and PNN Series Connection

المؤلفون المشاركون

Yan, Chun
Li, Meixuan
Liu, Wei

المصدر

Mathematical Problems in Engineering

العدد

المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-10، 10ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2019-07-03

دولة النشر

مصر

عدد الصفحات

10

التخصصات الرئيسية

هندسة مدنية

الملخص EN

Dissolved gas-in-oil analysis (DGA) is a powerful method to diagnose and detect transformer faults.

It is of profound significance for the accurate and rapid determination of the fault of the transformer and the stability of the power.

In different transformer faults, the concentration of dissolved gases in oil is also inconsistent.

Commonly used gases include hydrogen (H2), methane (CH4), acetylene (C2H2), ethane (C2H6), and ethylene (C2H4).

This paper first combines BP neural network with improved Adaboost algorithm, then combines PNN neural network to form a series diagnosis model for transformer fault, and finally combines dissolved gas-in-oil analysis to diagnose transformer fault.

The experimental results show that the accuracy of the series diagnosis model proposed in this paper is greatly improved compared with BP neural network, GA-BP neural network, PNN neural network, and BP-Adaboost.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Yan, Chun& Li, Meixuan& Liu, Wei. 2019. Transformer Fault Diagnosis Based on BP-Adaboost and PNN Series Connection. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1194196

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Yan, Chun…[et al.]. Transformer Fault Diagnosis Based on BP-Adaboost and PNN Series Connection. Mathematical Problems in Engineering No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1194196

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Yan, Chun& Li, Meixuan& Liu, Wei. Transformer Fault Diagnosis Based on BP-Adaboost and PNN Series Connection. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1194196

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1194196