Predicting Dike Piping Hazards Using Critical Slowing Down Theory on Electrical Signals

Abstract

Early warning signals of critical transitions in the piping process are essential for predicting dike hazards. This study proposes a new approach that combines Critical Slowing Down (CSD) theory with electrical signals analysis to identify precursor characteristics during the evolution of piping in a dual-layer dike foundation. A laboratory experiment was conducted to simulate the piping process while monitoring electrical signals in real-time. Ensemble Empirical Mode Decomposition (EEMD) was employed to analyze the time-series characteristics of the electrical signals from multiple perspectives. The results demonstrate that low-frequency components effectively track the gradual development of piping, while high-frequency components are sensitive to abrupt transitions near the critical point of failure. Statistical analysis reveals that the variance of the low-frequency components increases suddenly 5.09 min before the formation of the piping outlet and 5.53 min before piping occurs, providing a clear early warning capability. In contrast, the variance of the high-frequency components increases suddenly only 0.26 min and 0.45 min in advance, offering a short-term warning. These sudden increases serve as the effective precursory characteristics of critical transitions in the piping process. These findings confirm the presence of CSD characteristics in electrical signals and establish variance-based indicators as reliable precursors for different stages of piping evolution. The proposed methodology offers both theoretical insight and practical guidance for enhancing early warning strategies for dike failure.

Keywords

• piping
• electrical signals
• critical slowing down theory
• effective precursory characteristics
• early warning
• piping hazards prediction