Fault diagnosis of the bushing infrared images based on mask R‐CNN and improved PCNN joint algorithm

Author:

Jiang Jun12,Bie Yifan1,Li Jiansheng3,Yang Xiaoping4,Ma Guoming5,Lu Yuncai3,Zhang Chaohai1

Affiliation:

1. Jiangsu Key Laboratory of New Energy Generation and Power Conversion Nanjing University of Aeronautics and Astronautics Nanjing China

2. Department of Electrical & Electronic Engineering School of Engineering, The University of Manchester Manchester UK

3. State Grid Jiangsu Electric Power Co. Ltd. Research Institute Nanjing China

4. State Grid Jiangsu Electric Power Co. Ltd. Nanjing China

5. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference25 articles.

1. Estimation of water content in a power transformer using moisture dynamic measurement of its oil

2. On‐line monitoring and diagnoses of power transformer bushings;Setayeshmehr A.;IEEE Trans. Dielectr. Electr. Insul.,2008

3. Detection of power transformer bushing faults and oil degradation using frequency response analysis;Hashemnia N.;IEEE Trans. Dielectr. Electr. Insul.,2018

4. Temperature dependent electric field distribution in ±800 kV valve‐side bushing insulation for a converter transformer;Du B.;High Volt.,2020

5. CIGRE.:Power transformers and reactors ‐ transformer bushing reliability(2019)

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