Fault Diagnosis of Power Transformer based on Probability-box Theory

DOI

10.2991/mce-14.2014.109How to use a DOI?

Keywords

Fault diagnosis; Power transformer; Uncertainty; Probability box; Fusion

Abstract

In practice, fault diagnosis of power transformer is often performed on the basis of limited data. Under this circumstance, there are practical difficulties in identifying unique distributions as input for fault diagnosis. In order to solve the problem and improve the diagnosis ability of power transformer by analyzing the dissolved gas, a new method based on probability boxes theory was proposed. Firstly, the raw percentages of dissolved gas were used as the information source to construct the tow p-boxes about H2 and C2H6 gas content. Then, to take advantage of the complementation of the information source, the tow p-boxes about H2 and C2H6 gas content were fused. Finally, the SVM features database was established by extracting different types of cumulative uncertainty measures from p-boxes. The analysis result shows that the proposed method has high degree of di-agnosis accuracy and is characterized by fast diagnosis and good real-time, demonstrating the model is practical and effective.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jiaman Ding
AU  - Yi Du
AU  - Qingxin Wang
AU  - Lianyin Jia
AU  - Yingna Li
PY  - 2014/03
DA  - 2014/03
TI  - Fault Diagnosis of Power Transformer based on Probability-box Theory
BT  - Proceedings of the 2014 International Conference on Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 490
EP  - 493
SN  - 1951-6851
UR  - https://doi.org/10.2991/mce-14.2014.109
DO  - 10.2991/mce-14.2014.109
ID  - Ding2014/03
ER  -