Metro Turnout Short-term Action Overload Early-warning Method Based on Multi-description Complementary Prediction

[Objective] Metro turnback turnouts undergo frequent movements and complex working conditions, making them prone to overload actions that lead to mechanical failures such as jamming and blockage. A method for predicting short-term action loads and assessing overload early-warnings is proposed. [Method] Focusing on metro turnout short-term action overload early-warning, research is carried out expounding the assessment method for turnout short-term state early-warnings. Utilizing the proposed multi-description weighted prediction mechanism and adaptive kernel density estimation, the approach to achieve interval prediction of action loads and the calculation of early-warning assessment indicators are described, and the early-warning assessment process is outlined. Based on this, an application plan for action overload early-warning is established and empirically tested using turnout action data from Wuhan Metro. [Result & Conclusion] First, real-time continuous collection of turnout power curve characteristic p