Simulation of multi interval secondary protection equipment state interaction cascade detection based on random forest

Abstract This paper proposes a multi-interval secondary protection device state interaction cascading detection simulation based on random forest, effectively handling complex device state interaction relationships and timely detecting device state anomalies and cascading faults. We obtain the status characteristics of multi-interval secondary protection equipment, input this feature into a random forest model, construct multiple decision trees, fully utilize the correlation and interaction between features, classify the status of multi-interval secondary protection equipment, and further improve model performance by selecting appropriate weight coefficients, achieving effective detection of multi interval secondary protection equipment status. The experimental results show that the features extracted by this method can reflect the operating status of multi-interval secondary protection equipment. This method can effectively detect the interaction cascade relationship between multiple-interval secondary protection devices.