ArticleMicromachines2024
Passive Wireless Partial Discharge Sensors with Multiple Resonances.
Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Partial Discharge Detection from Large Motor Stator Slots Using EFPI Sensors.Sensors (Basel, Switzerland) · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
Partial discharge (PD) is the dominant insulating defect in Gas-Insulated Switchgear (GIS). The existing detection methods are mainly divided into built-in wire-connected disk antennas with destructive drilling and external ultra-high frequency antennas with poor anti-interference ability. This research introduces a passive wireless PD sensor implanted inside GIS on the observation window. The sensor is implemented by a sheeting branch-inductor with multiple resonances which is able to enhance detection sensitivity. A coaxially aligned readout circuit, positioned outside the GIS, interrogates the PD sensor to wirelessly obtain the PD signal. The proposed sensing scheme improves signal-to-noise ratio and ensures minimal disruption to the electric field distribution inside GIS. An experimental setup was established in a controlled laboratory environment to benchmark the multi-resonant sensor against the commercial UHF sensor. A 2.5-times enhancement of signal strength was observed. Since our sensor was implanted inside the GIS, a high signal-to-noise ratio (68.82 dB) was obtained. Moreover, we constructed a wireless calibration test to investigate the accuracy of the proposed sensor. The precision of the signal test was as high as 0.72 pC. The pulse phase distribution information was collected to demonstrate a phase-resolved partial discharge (PRPD) pattern. The experiment results validate the effectiveness of the proposed method and demonstrate excellent performance in PD detection.
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Registered trials
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