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Hussain, M.M., Farokhi, S., McMeekin, S.G. and Farzaneh, M. (2016) Prediction of Surface Degradation of Composite Insulators Using PD Measurement in Cold Fog. 2016 IEEE International Conference on Dielectrics (ICD), Montpellier, 3-7 July 2016, 697-700.
https://doi.org/10.1109/icd.2016.7547711

has been cited by the following article:

• TITLE: Development of a Platform for Real-Time, Non-Disruptive Monitoring and Early Fault Detection of Critical High Voltage Transformers and Switchgears in High Speed-Rail

  AUTHORS: Ming Zhu, Jiawei Fan, Yingtao Jiang, Hualiang Teng

  KEYWORDS: Partial Discharge, Real-Time Monitoring, Robust Detection, Radio Frequency

  JOURNAL NAME: Journal of Transportation Technologies, Vol.16 No.1, December 8, 2025

  ABSTRACT: Partial discharge (PD) incidents in high-speed rail systems, such as transformers and switchgears, arise from insulation defects under electric stress, leading to potential flashovers, breakdowns, downtime, and safety risks. PD emits radio frequency (RF) signals, enabling the development of a non-invasive, real-time PD detection and monitoring platform. This system uses an RF antenna and a high-speed data acquisition system to scan a frequency range (100 MHz to 2.5 GHz) with intermediate frequency modulation for precise detection and analysis. PD events exceeding a preset power threshold are recorded, capturing both signal data and spectrum snapshots. Real-time data is streamed to a cloud server, accessible via a smartphone app, allowing remote monitoring and quick responses by maintenance teams. Laboratory tests confirm the system’s effectiveness in accurately capturing PD signals, enhancing high-speed rail infrastructure reliability and safety.