TY - JOUR
AU1 - Chen, Chun-jun
AU2 - Wang, Huan
AU3 - Qin, Hui-jie
AU4 - Xiong, Wen-hui
AB - Considering the current ballasted track bed quality state evaluation and detection method is off-line, low efficiency and other defects, the lateral displacement of the rail row has been proposed as a new evaluation index for the quality state of the track bed. Regarding the track as a dynamic system, the vehicle-mounted excitation device applies lateral excitation to the rail row and measures its lateral displacement. It is difficult to directly measure the lateral displacement of the rail row. An estimation algorithm based on Kalman filter is designed to calculate the lateral displacement of rail row in real time; Meanwhile, wavelet transform and covariance matching algorithm is introduced to adaptively optimize the two key design parameters of the Kalman filter: measurement noise covariance matrix R and system noise covariance matrix Q to improve the robustness of Kalman filter algorithm. Finally, the measured data of the railway line verifies that the algorithm can accurately estimate the lateral vibration displacement of the track row through the acceleration signal, and provide technical support for the future research on the continuous online detection of the quality state of ballast track bed.
TI - On-line detection of vehicle-mounted ballast bed quality status based on improved Kalman filter
JF - Proceedings of SPIE
DO - 10.1117/12.2623906
DA - 2022-02-07
UR - https://www.deepdyve.com/lp/spie/on-line-detection-of-vehicle-mounted-ballast-bed-quality-status-based-RWuzyOlf5E
SP - 120810E
EP - 120810E-12
VL - 12081
IS - 
DP - DeepDyve
ER -