Design and Verification of Contamination Insulator Conductivity Detecting System

Zhong, Rongfu; Liu, Congcong; He, Wei

doi:10.1109/powercon.2018.8602095

Cited by 1 publication

(1 citation statement)

References 4 publications

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“…There are mainly two kinds of contamination perception methods for insulators: contact methods and non-contact methods (Jin et al, 2017). The contact ones include leakage current (Banik et al, 2016;Wang et al, 2019;Salem et al, 2020), surface conductivity (Wang et al, 2017;Zhong et al, 2018), ESDD (Equivalent Salt Deposit Density) (Cao et al, 2019) and so on. Generally speaking, the above approaches have clear physical meaning and are relatively accurate.…”

Section: Introductionmentioning

confidence: 99%

Insulator Contamination Perception Based on Feature Fusion of Infrared Image and Meteorological Parameters

Wang

et al. 2021

Front. Energy Res.

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Polluted insulators seriously threaten the safe and stable operation of power grids, which attaches great significance to insulator contamination perception. Among the present methods, the non-contact approaches based on infrared images have gradually been widely used, as they are much more safe and are of low cost. However, the thermal effect of insulators is largely affected by meteorological conditions, which makes the infrared image-based methods less accurate. To solve the above problem, we take infrared image and meteorological parameters including humidity and temperature as input, and propose a feature fusion model to perceive insulator contamination in different weather conditions. Firstly, different feature extraction networks are used to perform feature extraction on the two types of data; secondly, the two features are concatenated to fuse together; thirdly, further feature extraction is performed and contamination is classified according to the pollution severity. Case studies show that the proposed method can better explore the relationship between humidity, temperature and pollution level of the insulators, thus can better separate the contamination grades and outperform the conventional infrared image based methods.

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Section: Introductionmentioning

confidence: 99%

Insulator Contamination Perception Based on Feature Fusion of Infrared Image and Meteorological Parameters

Wang

et al. 2021

Front. Energy Res.

View full text Add to dashboard Cite

show abstract

Design and Verification of Contamination Insulator Conductivity Detecting System

Cited by 1 publication

References 4 publications

Insulator Contamination Perception Based on Feature Fusion of Infrared Image and Meteorological Parameters

Insulator Contamination Perception Based on Feature Fusion of Infrared Image and Meteorological Parameters

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