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Xia C, Ren M, Liu R, Tian Z, Song M, Dong M, Zhang T, Miao J. Tracking moisture contents in the pollution layer on a composite insulator surface using hyperspectral imaging technology. Analyst 2024; 149:2996-3007. [PMID: 38602375 DOI: 10.1039/d3an02033a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2024]
Abstract
Electrical insulators used in transmission lines and outdoor substations are exposed to severe environmental pollution, which significantly increases the risk of power system failure, especially when the pollution layer is highly humid due to adverse weather conditions. The focus of this paper is to establish an effective method for assessing the moisture content (MC) in pollution layers as it serves as a crucial indicator for evaluating the risk of failure in insulators. Hyperspectral imaging (HSI) technology with a spectral range of 371.08-1037.89 nm was applied to determine significant changes in reflectance spectral characteristics in insulators during dynamic wetting and drying periods. Partial least squares regression (PLSR) models were utilized to evaluate the data presentation enhancement abilities of spectral transformation models and the data dimensionality reduction abilities of characteristic band selection methods. Furthermore, PLSR models were developed to calculate the MC along the pixel dimension to visually retrieve the dynamic wetting and drying processes of the pollution layer. The R-squared and root-mean-square error (RMSE) results in the cross-verification set and prediction set of the RE-RF(70%)-PLSR model with two characteristic bands with a wavelength of 543.28 nm and 848.01 nm were as follows: RCV2 = 0.9824, RMSECV = 0.0367, RP2 = 0.9818, RMSEP = 0.0369, respectively. This research contributes towards the visualization retrieval of the MC and offers an important technique for analyzing flashover evolution, optimizing insulator design, and preparing coating materials for insulators.
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Affiliation(s)
- Changjie Xia
- School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China.
| | - Ming Ren
- School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China.
- State Key Lab of Electrical Insulation & Power Equipment, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Runyu Liu
- School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China.
| | - Zhili Tian
- School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China.
| | - Meiyan Song
- School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China.
| | - Ming Dong
- School of Electrical Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China.
- State Key Lab of Electrical Insulation & Power Equipment, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China
| | - Tao Zhang
- The State Grid Wuxi Electric Supply Company, Wuxi, Jiangsu 214000, PR China
| | - Jin Miao
- The State Grid Wuxi Electric Supply Company, Wuxi, Jiangsu 214000, PR China
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Smorkalov IA. Soil Respiration Variability: Contributions of Space and Time Estimated Using the Random Forest Algorithm. RUSS J ECOL+ 2022. [DOI: 10.1134/s1067413622040051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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