Based On Track Survey Data Of The Machine Maintenance Method Research

With the comprehensive speed of China's railway,traffic density continues to increase and driving distance is shortened and skylight time has been compressed and contradictions between the maintenance and safety operations are increasingly prominent.Therefore,it is very important to improve the operational efficiency and quality of work in the public works department.Now,with the existing line level measurement as a long-wave longitudinal control method,in both the high-speed ballasted railway relying on precision measurement network(CP ? measurement network)as a long-wave control means,how to effectively use good track test data used in large track maintenance machinery is a very critical issue.In addition,the track inspection vehicle as the main means of track detection at this stage,with detection speed,high efficiency,but its role is still mainly in the evaluation of the state of the railway line,the detection of disease and railway line maintenance work Sexual guidance,and can not be directly applied to the rail track maintenance applications.The use of rail inspection data is still to be studied.So as to improve its utilization and make it better for working site.In this paper,we focus on the detection data of elevation data and the data of vertical height data in rail transit vehicle data.Firstly,the principle and method of the railway track detection are analyzed,and the principle of the dynamic detection data of the track dynamic analysis is analyzed from the angle of mathematics.The source process of the data is analyzed.Second,the working principle and working mode of the treadmill are carried out.The source of the error is estimated to provide a theoretical basis for the proper use of the data.Third,according to the idea of "cutting peak and filling the valley",the static data of the existing railway line and the static and dynamic data of the ballasted high-speed railway line are processed.Finally,the model is analyzed and combined with the empirical coefficient calculation method of optimizing operation volume based on starting and working effect.It is found that the static data pretreatment measured by the precision measurement network(CP ?measurement network)has a similarity with the pretreated track vehicle data,reaching 73%.In addition,the mileage of the survey data There is a deviation in the ultra-high mileage alignment,there are still about 50 m deviation,and the curve of the tamper and the detection wheel wear.It is recommended to pay attention to the detection of vehicle mileage correction and tamper the measurement of the wheel calibration and curve for the mileage adjustment,so as to improve the accuracy of the use of test data.Through the tamping effect of the amount of work based on the idea of "cutting peak and valley filling",it is found that the dynamic waveform has obviously improved,and the TQI deduction and the overrun are reduced.It is proved that the dynamic detection data can be used to optimize the smoothness of the line,which can improve the efficiency of the maintenance work of the line smoothness,so as to keep the running state of the railway line,ensure the safety of the traffic and improve the comfort of the passengers degree.