Railway Track Tamping Maintenance Cycle Prediction Model Based on Power-Time-Transformed Wiener Process

Abstract

Predicting the tamping cycles of railway track sections based on track geometry deterioration rules is necessary to reasonably allocate the limited tamping maintenance resources. Existing research on track geometry deterioration modeling for tamping cycle prediction lacks simultaneous consideration of the deterioration characteristics including heterogeneity, uncertainty, and historical dependence, thereby limiting the accuracy of the prediction results. Thus, this study considers a 200 m track segment as the basic object and uses the power-time-transformed Wiener process to develop a deterioration prediction model for the longitudinal level of a segment between two adjacent tamping operations. Moreover, it individually estimates the model parameters for each track segment to predict the tamping maintenance cycle for each segment combined with the tamping maintenance threshold of the longitudinal level index. Finally, through a case study of the Chinese Lanxin Railway line, the effectiveness of the proposed model and different parameter estimation methods is assessed.