Research On The Pick Locating Method Of Tamping Operation In Tamping Wagon

Due to the long-term pressure of train operation and the adverse effects caused by climate change,the railway track with ballast bed has caused residual deformation of railway line,which caused different degrees of settlement and movement of the ballast,and brought significant danger to vehicle operation.Therefore,maintenance and repair are essential for railway line.The aim of tamping track ballasts under railway is to tamp the gap between sleepers and the ballast bed,make sleepers and the rail evenly stressed,and let ballast bed flat and compact.After tamped,the buffer capacity of track ballast can be enhanced,the positions of track are stabilized,and thus the safe operation of the railway will be ensured.The track tamping operation is done by a tamping machine,which usually needs to determine the positions of tamping in advance.If locating is wrong,the pick may damage the railway and sleepers,and even tamping machine itself.Therefore,how to find the positions of tamping is one of the most important steps in the tamping operation.With the rapid development of intelligent equipment manufacturing industry,the line operation standards have gradually increased.In the past,traditional tamping operations could not meet the requirements of high-speed,heavy-duty and comfortable railways.In addition,traditional tamping operations rely on manual methods,as for practical operators,technical requirements are high,the labor intensity is large,the operation is easy to make mistakes,and the operation efficiency is greatly reduced.However,the research on intelligent tamping technology has not made substantial progress.Researching on the pick locating method of tamping operation is the center of this work.When a Tamping Wagon is tamping in ballasted track,it is necessary to determine the position of a pick in advance.A peak detection algorithm is proposed for locating rail spikes by magnetic sensing signals,to accurately determine the position of the pick.In this algorithm,it uses some methods,such as downsampling,slid-window peak detection,threshold classification and secondary search to complete peak signal detection.Especially,it discusses how some parameters,sliding window length,downsampling frequency and secondary search window length affect the performance of the algorithm.In the experiment,a group of magnetic sensing signals obtained on the ballasted track are tested.The experimental results show that,compared with the traditional scheme,the scheme using downsampling,sliding window peak detection,threshold classification and secondary peak search has better detection performance.At the same time,in order to ensure that the algorithm does not appear false positive and missing detection,and reduces the computational complexity,the algorithm should also consider a smaller window length,a larger downsampling frequency and a moderate secondary search window length.Finally,when the window length is set to 3,the downsampling frequency is set to 30 and the secondary search window length is set to 70,the missed detection and false positive are both 0,the search times are only 10~4,while the maximum rail spike location error will not more than 1cm.