Aging Status Prediction of Oil Impregnated Insulating Kraft Paper Using GLCM Based Textural Features-Reference-Cited by-同舟云学术

Aging Status Prediction of Oil Impregnated Insulating Kraft Paper Using GLCM Based Textural Features

Published:2021-12 Issue:6 Volume:28 Page:2108-2116
ISSN:1070-9878
Container-title:IEEE Transactions on Dielectrics and Electrical Insulation
language:
Short-container-title:IEEE Trans. Dielect. Electr. Insul.

Author:

Kumaresh S. S.¹,Malleswaran M.²

Affiliation:

1. University College of Engineering Kancheepuram (A Constituent College of Anna University Chennai),Department of Electrical and Electronics Engineering,Kanchipuram,India

2. University College of Engineering Kancheepuram (A Constituent College of Anna University Chennai),Department of Electronics and communication Engineering,Kanchipuram,India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/94/9679679/09679778.pdf?arnumber=9679778

Reference25 articles.

1. Optical object detection in paper improved by refractive index matching and mechanical treatment

2. On the Estimation of Elapsed Life of Oil-Immersed Power Transformers

3. Classification of degradation in oil-impregnated cellulose insulation using texture analysis of optical microscopy images

4. Aging feature extraction of oil-impregnated insulating paper using image texture analysis

5. Texture analysis of fluorescence microscopic images of colonic tissue sections

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Insulation aging condition assessment of transformer in the visual domain based on SE-CNN;Engineering Applications of Artificial Intelligence;2024-02

2. SceneNet: A Multifeature Joint Embedding Network With Complexity Assessment for Power Line Scene Classification;IEEE Transactions on Aerospace and Electronic Systems;2023-12