Study On Variation Characteristics And Prediction Models Of Railway Track Geometric Irregularity

Rail track geometric irregularities are the concrete embodiment of track structure deterioration, and give an expression to the comprehensive performance of track members. Therefore, study on variation characteristics of track geometric irregularity caused by repetitive trainloads, and develop feasible prediction models to predict track deterioration in future so as to decide preventive maintenance plans, are of great significance to assisting governor decision-making and safeguarding the transportation.Based on existing theories of track geometry irregularity deterioration and prediction, this paper laid an emphasis on the study of variation characteristics and tried to establish a feasible prediction model. First, this paper introduced items of track geometry irregularities, and proposed computer techniques for track inspection data correction. Second, with plentiful track inspection data, variation characteristics of track irregularity waveform, periodic deterioration, and track irregularity deterioration rate were analyzed, and valuable conclusions were given correspondingly. Then, using these conclusions as reference, and inspired by the thought of integrating factor method for prediction, we developed an improved track geometric irregularity integrating factor prediction model, and applied this model to estimated track irregularity growth in Beijing-Shanghai railway, evaluation results verified high accuracy of this model. Finally, this paper put forward the strategies and relative theories for suggested maintenance planning, and showed the monthly suggested plans for April,2009 in Beijing-Shanghai railway as example. In addition, a practical software was programmed so as to provide useful tools for prediction and decision-making.Variation characteristics of track geometric irregularity reveal the general regularity of track deterioration. This paper has made a comprehensive analysis and developed a new track geometric irregularity prediction model, which has been verified with high accuracy. Furthermore, the software programmed in this paper offers the first step into computer aided track maintenance planning. All of these studies will certainly play positive and promotive roles in guiding rail track maintenance and assisting governor decision-making.