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Classical short-circuit theory assumes instantaneous resistance collapse, preventing direct measurement and mandating threshold-based protection. This paper establishes a governed measurement paradigm using a bidirectional diode-clamp circuit that transforms the short circuit into a sustained, observable process for up to 15-minutes forward and 15-minutes reverse polarities without component destruction. The theoretical foundation is the Modified Ohm’s Law with exponential resistance decay, derived from a Langevin dissipative framework. The paper principal contribution is a comprehensive signal validation methodology grounded in the Nyquist-Shannon criterion, Shannon entropy, Fourier analysis, and the short-time Fourier transform, introducing six quantitative metrics: Nyquist Compliance Index (NCI), Transient Complexity Index (TCI), Spectral Compactness Coefficient (SCC), Spectral Entropy Score (SES), Time-Frequency Stability Metric (TFSM), and Composite Validation Index (CVI). Experimental validation across 54 configurations with a low-cost Arduino system reveals governed fault signals are intrinsically low-frequency ( f max = k / 2 π from 10 − 7 H z to 10 − 3 H z ), with NCI exceeding unity by three to seven orders of magnitude-confirming that 10 H z − 100 H z sampling suffices, contrary to conventional k H z -rate practice. The mean decay constant decreases from 9.6 × 10 − 4 s − 1 at 2.5 V to 2.3 × 10 − 4 s − 1 at 5.0 V and 10.0 V , establishing that above the 2.4 V clamp threshold fault stabilisation becomes voltage-independent, enabling scaling to higher power. Decay constants exhibit systematic polarity dependence ( 2 × 10 − 6 s − 1 to 1 × 10 − 2 s − 1 , forward/reverse differ by factors up to six). The TCl ranges 0 − 0.66 , quantifying informational richness; TFSM averages 0.85 , confirming stationary fault states. This work provides a complete methodological framework for non-destructive, time-resolved short-circuit measurement, enabling adaptive protection and low-cost distributed monitoring-transforming short-circuit analysis into a diagnostic discipline.
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Kimuya et al. (2026) studied this question.