Abstract：Abstract : Research purposes ： Typically， during the indoor - world process of fine adjustment on blast less track of high - speed railway，data would be partly deposited，adjustments would be set tentatively with manual method，and final result would be gotten by comparison，judgement and screening. However，this method is resource intensive and time consuming. What ( s more，too much manual intervention makes the quality of data varies，and the overall coordination of data may not be guaranteed. Wavelet transform performs its advantages，not only in ensuring the similarity between global and regional data，but also in smoothing the local data. The objective of the current study in this paper is to use the wavelet transform method to filter out the irregular data，remain the smooth part and ensure the available indicators of smoothness meeting the requirements. By performing this method，the indoor - work would turn into a kind of semi - automatic data processing. Research conclusions ：( 1) Wavelet transform could eficiently reduce TQ! in fine adjustment of high - speed railway. (2) After many wavelet transforms， the qualification rate of longitudinal evaluation factor will increase， while the qualification rate of horizontal evaluation factor will diverge after a convergenceona specific value. ( 3 ) After many wavelet transforms， the percentage of adjusted data will increase， but the adjustment amount of most data will be controlled within - 1 1 mm , which leaves enough room for subsequent adjustment step and prevents that there is no fastener left to be used. (4)The algorithms have been successfully applied in indoor - work process of fine adjustments on ballastless track, and wavelet transform could compute the adjustments automatically, make the error rate of adjustment reduced to less than 7% ,and largely reduce the degree of manual intervention.
2017, Vol. 34 
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