Design And Key Technology Research Of On-line Detection System For Ballasted Track Bed Quality

Ballasted track is one of the main structural form of current railway track.The continuous increase of railway operating mileage and train operation leads to increasingly heavy maintenance tasks for ballast bed.The results of ballast bed maintenance require manual sampling detection according to the detection methods specified by the railway industry standards.The off-line detection method is inefficient and damages the track structure.In respect of the issues above,the basic principle of the on-line detection method for ballasted track bed quality is proposed,and an on-line detection system is established.The on-line detection algorithm of the lateral vibration displacement of the rail row and the on-line identification algorithm of the quality evaluation indexes of ballasted bed in the on-line detection system of ballasted track bed quality are researched.The main research contents of this thesis are as follows:1.A comprehensive analysis of the correlation between the existing ballast bed quality status evaluation indexes is carried out to determine the ballast bed lateral resistance as an index of the overall quality status of the ballast bed.The research and analysis of the formation mechanism and detection methods of the ballast bed lateral resistance are performed.The equivalent lateral stiffness and equivalent lateral damping are used as new indexes to evaluate the quality of the ballast bed.Based on this,the basic principle of the on-line detection method of ballasted track bed quality is proposed.2.The overall scheme of the on-line detection system is determined based on the basic principle of the on-line detection method for ballasted track bed quality.The selection and performance of the main equipments are introduced.The hardware equipments of the on-line detection system are installed at the test site,and the railway line test is carried out.3.It is difficult to directly measure the lateral displacement of the key parameters of the rail row in the detection scheme with large errors and high measurement costs.A displacement estimation algorithm is designed with Kalman filter algorithm based on the state estimation theory.Considering the problem that the noise variance change of the measured acceleration affects the accuracy of Kalman filter and even causes divergeence of the filtering results,an improved Kalman filter algorithm based on wavelet transform and covariance matching is designed.This algorithm can achieve accurately displacement estimation which is verified based on the actually measured data of the railway line.The on-line detection system is optimized according to the displacement comparison results.4.Considering the problem of on-line identification of the equivalent lateral stiffness and equivalent lateral damping of ballast bed in the on-line detection system,the discrete difference equation of the transfer function of the on-line detection system is established.The concept of "window function" in modern signal processing methods is introduced to design the windowed least square identification algorithm which realizes real-time and on-line identification of equivalent lateral stiffness and equivalent lateral damping of ballast bed.Finally,the identification results and the lateral resistance of ballast bed obtained by off-line measurement are analyzed to determine that the equivalent lateral stiffness of ballast bed is uesd as the new index for evaluating the quality of the ballasted track bed.