In this paper, we investigated the influence of climatic factors, particularly low temperature and humidity, on the grounding resistance of transmission towers in severely cold regions. Drawing on a full year of field monitoring data, we first identified a clear negative linear correlation between temperature and grounding resistance. Notably, the inclusion of precipitation as an additional variable led to a significant increase in the model's explanatory power and indicated that the resistance behavior was influenced by multiple environmental factors. To further explore the nonlinear and dynamic aspects of this relationship, we used multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA). The computational results showed that the resistance time series exhibits strong multifractal characteristics and suggests high variability across temporal scales. Moreover, the combined influence of temperature and precipitation demonstrated a markedly stronger cross-correlation with resistance than temperature alone. These findings emphasize the complex and multiscale nature of grounding behavior in harsh climates and underscore the importance of moving beyond simplified linear models. Our research offers both methodological insights and practical implications for the design, maintenance, and risk assessment of power transmission infrastructure operating under extreme weather conditions, particularly in high-latitude or alpine environments.
Citation: Guangxin Zhang, Minzhen Wang, Jian Wang, Junseok Kim. Multifractal time series analysis of grounding resistance in transmission line towers under cold-climate conditions[J]. AIMS Mathematics, 2025, 10(11): 27985-28003. doi: 10.3934/math.20251229
In this paper, we investigated the influence of climatic factors, particularly low temperature and humidity, on the grounding resistance of transmission towers in severely cold regions. Drawing on a full year of field monitoring data, we first identified a clear negative linear correlation between temperature and grounding resistance. Notably, the inclusion of precipitation as an additional variable led to a significant increase in the model's explanatory power and indicated that the resistance behavior was influenced by multiple environmental factors. To further explore the nonlinear and dynamic aspects of this relationship, we used multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA). The computational results showed that the resistance time series exhibits strong multifractal characteristics and suggests high variability across temporal scales. Moreover, the combined influence of temperature and precipitation demonstrated a markedly stronger cross-correlation with resistance than temperature alone. These findings emphasize the complex and multiscale nature of grounding behavior in harsh climates and underscore the importance of moving beyond simplified linear models. Our research offers both methodological insights and practical implications for the design, maintenance, and risk assessment of power transmission infrastructure operating under extreme weather conditions, particularly in high-latitude or alpine environments.
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Guangxin Zhang, Minzhen Wang, Jian Wang, Junseok Kim. Multifractal time series analysis of grounding resistance in transmission line towers under cold-climate conditions[J]. AIMS Mathematics, 2025, 10(11): 27985-28003. doi: 10.3934/math.20251229
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