Objective: To elucidate the evolution patterns and hazard characteristics of overheating-induced short-circuit faults in energized conductors under external thermal radiation, this study systematically investigated critical heat flux, characteristic temperatures, fault initiation time, insulation resistance evolution, short-circuit current-voltage waveform characteristics, and arc energy variation. The objective was to identify key parameters for the early warning of electrical fires during conductor short-circuit failure under varying thermal radiation intensities. The findings aim to provide experimental evidence for risk identification and assessment of electrical circuit failures in high-temperature environments. Methods: Using an electrical fault simulation apparatus, stable thermal radiation intensities of 23—32kW·m^-2 were applied to ZR-RVVB conductors operating under rated current conditions. Parameters including surface and internal temperatures, insulation resistance, pre-and post-short-circuit current and voltage waveforms, and fault occurrence times were recorded simultaneously. Thermal failure stages were defined using temperature-time curves. Short-circuit types were classified through waveform and time-frequency domain analyses, and short-circuit arc energy was calculated based on voltage-current integration. Comparative analyses were conducted to determine parameter variation patterns across different thermal radiation intensities. Results: Experimental findings indicated that 23kW·m^-2 represents the minimum critical thermal radiation intensity that causes short-circuit failures in ZR-RVVB conductors under rated current conditions. With increasing thermal radiation intensity, the conductor temperature rise showed four stages: transient thermal shock, accelerated pyrolysis, critical failure, and thermal steady state. The initial pyrolysis temperature (T₁), peak temperature (T₂), short-circuit trigger temperature (T_sc), and steady-state temperature (T₃) increased approximately linearly with increasing heat flux. Meanwhile, the duration of each stage decreased with increasing heat flux, showing a power-law relationship. This reduction is associated with faster heating and accelerated insulation degradation under higher thermal radiation intensities. Notably, the short-circuit trigger time shortened from ~1053.4s to 172.4s. At a heat flux of 32kW·m^-2, the insulation resistance dropped rapidly to ~0GΩ within 180s. Overall, insulation resistance declined significantly with increasing thermal radiation intensity. A reduction below ~1GΩ signaled imminent insulation failure. Fault mechanisms transitioned from metallic short circuits to carbonization path-type and arc-type faults as the thermal radiation intensity increased. At a heat flux of 25kW·m^-2, metallic short circuits were the dominant failure mode, accounting for ~70% of failures. When the heat flux exceeded 26kW·m^-2, the frequency of carbonization path-type faults increased significantly, peaking near 31kW·m^-2. Time-frequency energy analysis indicated that arc-type short circuits exhibited the highest high-frequency energy characteristic parameters, with a high-frequency energy peak (HHF) of 0.860 and a high-frequency energy ratio (RHF) of 0.416, both of which were significantly higher than those of the other two fault types. Energy released after short-circuit increased significantly with increasing thermal radiation intensity; arc-type faults released the highest energy (approximately ~9324.89J), followed by carbonization path-type faults. Meanwhile, metallic short circuits released the least energy. This indicated that higher thermal radiation intensities lead to greater short-circuit energy release and increased destructive potential. Conclusions: This study characterized the temperature rise behavior, insulation resistance evolution, fault type transitions, and energy release characteristics of energized conductors under varying thermal radiation intensities. The findings provide a foundation for rapid short-circuit fault classification and the development of early-warning models.