Accurate detection of internal partial discharge (PD) in gas-insulated switchgear (GIS), a core component of modern power systems, is crucial for assessing insulation condition, ensuring equipment reliability, and maintaining power grid stability. However, the practical application of traditional ultra-high frequency (UHF) electromagnetic sensors in GIS condition-based maintenance faces significant limitations, including severe signal attenuation (20～40 dB/m) caused by the metal enclosure, the risk of SF6 leakage due to compromised airtightness with window-based installation, and a limited dynamic range (60～80 dB) insufficient for covering the full range of discharge magnitudes. To overcome these technical bottlenecks, this paper innovatively proposes a quantum-based UHF electric field sensing method utilizing the Rydberg atomic electromagnetically induced transparency (EIT) effect. The core advantages of this method lie in: leveraging the extremely high electric polarizability of highly excited cesium atoms (n=72D5/2) to achieve intrinsically safe measurement through an optical readout mechanism；establishing a stable EIT window using a dual-frequency laser system (852 nm probe light and 509 nm pump light) combined with precise frequency-locking technology；and designing a non-metallic atomic vapor cell antenna to realize the first near-field sensing of transient pulse electric fields in the 0.5～3 GHz band excited by particle discharge within GIS. This research demonstrates the capability of Rydberg atomic sensing technology to effectively detect discharges from a typical GIS defect (metal particles) for the first time. By employing quantum precision measurement, it provides a novel optical fiber sensing solution characterized by high sensitivity, broadband capability, and intrinsic safety for the online insulation monitoring of power equipment. This approach holds significant promise for advancing condition-based maintenance towards intelligent and precise evolution, offering key supporting technologies for the development of smart grids.