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Tracking moisture contents in the pollution layer on a composite insulator surface using hyperspectral imaging
Changjie Xia1, Ming Ren1,2, Runyu Liu1
1School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China. renming@xjtu.edu.cn.
The Analyst
|April 11, 2024
Summary
This study introduces a hyperspectral imaging method to assess moisture content in polluted electrical insulators, crucial for preventing power system failures. The technique accurately visualizes wetting and drying, enhancing insulator reliability.
Area of Science:
- Electrical Engineering
- Materials Science
- Remote Sensing
Background:
- Outdoor electrical insulators face failure risks due to environmental pollution, exacerbated by humidity.
- Assessing moisture content (MC) in pollution layers is vital for predicting insulator failure.
Purpose of the Study:
- To develop an effective method for assessing moisture content in polluted insulator layers.
- To visualize dynamic wetting and drying processes of pollution layers on insulators.
Main Methods:
- Utilized hyperspectral imaging (HSI) technology (371.08-1037.89 nm) to capture spectral changes.
- Applied Partial Least Squares Regression (PLSR) models for data analysis and MC calculation.
- Employed characteristic band selection methods to identify key spectral features.
Main Results:
- Developed PLSR models to calculate MC pixel-wise, enabling visualization of wetting/drying.
- Achieved high accuracy with the RE-RF(70%)-PLSR model (R²=0.9824, RMSE=0.0367).
- Identified specific characteristic bands (543.28 nm and 848.01 nm) for MC assessment.
Conclusions:
- HSI combined with PLSR offers a powerful technique for real-time MC monitoring of polluted insulators.
- This method aids in analyzing flashover evolution and optimizing insulator design.
- Provides insights for developing protective coating materials for insulators.
