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AC circuit fault simulation system design for residential electrical fires and its experimental validation
Liu Tao, Wei Zongfeng, Guo Yuhang, Tang Haijun, Jiang Wentao
2026, 45 (1):
21-27.
The frequent occurrence of electrical fires is closely associated with AC line faults. Among them, hidden or sudden faults such as ground faults, overload operation, and short circuits pose significant challenges in fire prevention and control, due to limitations of traditional monitoring methods including delayed response and insufficient risk identification accuracy. To address this, this study develops an AC line fault simulation system for electrical fire prevention, which integrates three typical fault modules, including short circuit, overload, and ground fault, and establishes a synchronous multi-source signal acquisition and analysis platform. Experimental results demonstrate that the energy release of short-circuit faults exhibits significant phase dependence. The energy released during a short circuit at the voltage rising edge reaches 158.8 J, an increase of 249.8% compared to the condition at the voltage falling edge. A ground fault without leakage protection causes rapid local temperature rise under a continuous current of 3 A, indicating a fire risk. Overload experiments reveal a nonlinear coupling relationship among wire diameter, current intensity, and temperature rise rate. A 1.5 mm² wire under 56 A overload exhibits a temperature rise rate of 3.32 °C/s, far exceeding that of a 2.5 mm² wire under the same operating conditions. Based on experimental data and distinguishing protection states, a fire risk classification system is established: under unprotected conditions, the risk of a ground fault without leakage protection is higher than that of overload operation; under protected conditions, short-circuit faults become the primary fire hazard due to instantaneous high-energy release accompanied by arcing, while ground faults can be effectively and promptly interrupted by leakage protection. The research outcomes provide data support for setting fire warning thresholds, fault backtracking analysis, and fire evidence identification, contributing practical value to enhancing the active fire prevention capabilities of electrical systems.
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