Simulation Study on Anti-Interference Performance Degradation of GIS UHF Sensors Based on Substation White Noise Reconstruction

The ultra-high frequency (UHF)-based partial discharge (PD) detection technology for gas-insulated switchgear (GIS) has achieved large-scale applications due to its high sensitivity and real-time monitoring capabilities. However, long-term service-induced antenna corrosion in UHF sensors may lead to degraded reception characteristics. To ensure the credibility of monitoring data, on-site sensor calibration under ambient noise conditions is required. This study first analyzes the time-frequency domain characteristics of white noise received by UHF sensors in GIS environments. Leveraging the transceiver reciprocity principle of sensors, a noise reconstruction method based on external sensors is proposed to simulate on-site white noise. Subsequently, CST simulation models are established for both standard and degraded sensors, quantifying the impact of factors like antenna corrosion on performance parameters such as echo impedance S11 and voltage standing wave ratio (VSWR). Finally, the two sensor models are coupled into GIS handholes for comparative simulation analysis. Results show that antenna corrosion causes resonant frequency shifts in sensors, reducing PD signal power by 55.27% and increasing noise power by 64.11%. The signal-to-noise ratio (SNR) decreases from -9.70 dB to -15.34 dB, with evident waveform distortion in the double-exponential PD pulses. These conclusions provide theoretical references for on-site UHF sensor calibration in noisy environments.

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Journal
Sensors
Published
2026-01-02
DOI
https://doi.org/10.3390/s26010303
Primary Topic
High voltage insulation and dielectric phenomena
Type
article
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article

Simulation Study on Anti-Interference Performance Degradation of GIS UHF Sensors Based on Substation White Noise Reconstruction

Y. Jeffrey Yang, Yiming Xie, Xingwang Wu, Haitao Yang et al.
Sensors
High voltage insulation and dielectric phenomena
article

Simulation Study on Anti-Interference Performance Degradation of GIS UHF Sensors Based on Substation White Noise Reconstruction

Y. Jeffrey Yang, Yiming Xie, Xingwang Wu, Haitao Yang, Zixi Zhu, Lujia Wang, Jie Wu
article en

Abstract

The ultra-high frequency (UHF)-based partial discharge (PD) detection technology for gas-insulated switchgear (GIS) has achieved large-scale applications due to its high sensitivity and real-time monitoring capabilities. However, long-term service-induced antenna corrosion in UHF sensors may lead to degraded reception characteristics. To ensure the credibility of monitoring data, on-site sensor calibration under ambient noise conditions is required. This study first analyzes the time-frequency domain characteristics of white noise received by UHF sensors in GIS environments. Leveraging the transceiver reciprocity principle of sensors, a noise reconstruction method based on external sensors is proposed to simulate on-site white noise. Subsequently, CST simulation models are established for both standard and degraded sensors, quantifying the impact of factors like antenna corrosion on performance parameters such as echo impedance S11 and voltage standing wave ratio (VSWR). Finally, the two sensor models are coupled into GIS handholes for comparative simulation analysis. Results show that antenna corrosion causes resonant frequency shifts in sensors, reducing PD signal power by 55.27% and increasing noise power by 64.11%. The signal-to-noise ratio (SNR) decreases from -9.70 dB to -15.34 dB, with evident waveform distortion in the double-exponential PD pulses. These conclusions provide theoretical references for on-site UHF sensor calibration in noisy environments.

SensorsVol. 26(1)
China University of Mining and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 99%
High voltage insulation and dielectric phenomena
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Simulation Study on Anti-Interference Performance Degradation of GIS UHF Sensors Based on Substation White Noise Reconstruction — Y. Jeffrey Yang, Yiming Xie, et al. · Sensors (2026) | TGRS Research Map | TGRS