Fault Diagnosis of Power Transformer based on Probability-box Theory
Jiaman Ding, Yi Du, Qingxin Wang, Lianyin Jia, Yingna Li
Available Online March 2014.
- https://doi.org/10.2991/mce-14.2014.109How to use a DOI?
- Fault diagnosis; Power transformer; Uncertainty; Probability box; Fusion
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 2014 International Conference on Mechatronics, Control and Electronic Engineering (MCE-14) PB - Atlantis Press SP - 490 EP - 493 SN - 1951-6851 UR - https://doi.org/10.2991/mce-14.2014.109 DO - https://doi.org/10.2991/mce-14.2014.109 ID - Ding2014/03 ER -