As a core infrastructure of high-speed railways,ballast layers constituted by graded crushed stones feature noteworthy particle movement compared with normal railways,which may cause excessive settlement and have detr...As a core infrastructure of high-speed railways,ballast layers constituted by graded crushed stones feature noteworthy particle movement compared with normal railways,which may cause excessive settlement and have detrimental effects on train operation.However,the movement behavior remains ambiguous due to a lack of effective measurement approaches and analytical methods.In this study,an image-aided technique was developed in a full-scale model test using digital cameras and a colorbased identification approach.A total of 1274 surface ballast particles were manually dyed by discernible colors to serve as tracers in the test.The movements of the surface ballast particles were tracked using the varied pixels displaying tracers in the photos that were intermittently taken during the test in the perpendicular direction.The movement behavior of ballast particles under different combinations of train speeds and axle loads was quantitatively evaluated.The obtained results indicated that the surface ballast particle movements were slight,mainly concentrated near sleepers under low-speed train loads and greatly amplified and extended to the whole surface when the train speed reached 360 km.h-1.Additionally,the development of ballast particle displacement statistically resembled its rotation.Track vibration contributed to the movements of ballast particles,which specifically were driven by vertical acceleration near the track center and horizontal acceleration at the track edge.Furthermore,the development trends of ballast particle movements and track settlement under long-term train loading were similar,and both stabilized at nearly the same time.The track performance,including the vibration characteristics,accumulated settlement,and sleeper support stiffness,was determined to be closely related to the direction and distribution of ballast particle flow,which partly deteriorated under high-speed train loads.展开更多
GNSS( global navigation satellite systems) are unavailable in challenging environments such as urban canyon and indoor locations due to signal blocking and jamming. Camera / IMU( inertial measurement units) integrated...GNSS( global navigation satellite systems) are unavailable in challenging environments such as urban canyon and indoor locations due to signal blocking and jamming. Camera / IMU( inertial measurement units) integrated navigation systems can be alternatives to GNSS. In this paper,a tightly coupled Camera / IMU algorithm modeled by IEKF( iterated extended kalman filter) is presented. This tight integration approach uses image generated pixel coordinates to update the Kalman Filter directly. The developed algorithm is verified by a hybrid simulation,i.e. using inertial data from field test to fuse with simulated image feature measurements. The results show that the tight approach is superior to the loose integration when the image measurements are insufficient( i.e. less than three ground control points).展开更多
基金The financial supports from the National Natural Science Foundation of China(52008369,52125803,and 51988101)。
文摘As a core infrastructure of high-speed railways,ballast layers constituted by graded crushed stones feature noteworthy particle movement compared with normal railways,which may cause excessive settlement and have detrimental effects on train operation.However,the movement behavior remains ambiguous due to a lack of effective measurement approaches and analytical methods.In this study,an image-aided technique was developed in a full-scale model test using digital cameras and a colorbased identification approach.A total of 1274 surface ballast particles were manually dyed by discernible colors to serve as tracers in the test.The movements of the surface ballast particles were tracked using the varied pixels displaying tracers in the photos that were intermittently taken during the test in the perpendicular direction.The movement behavior of ballast particles under different combinations of train speeds and axle loads was quantitatively evaluated.The obtained results indicated that the surface ballast particle movements were slight,mainly concentrated near sleepers under low-speed train loads and greatly amplified and extended to the whole surface when the train speed reached 360 km.h-1.Additionally,the development of ballast particle displacement statistically resembled its rotation.Track vibration contributed to the movements of ballast particles,which specifically were driven by vertical acceleration near the track center and horizontal acceleration at the track edge.Furthermore,the development trends of ballast particle movements and track settlement under long-term train loading were similar,and both stabilized at nearly the same time.The track performance,including the vibration characteristics,accumulated settlement,and sleeper support stiffness,was determined to be closely related to the direction and distribution of ballast particle flow,which partly deteriorated under high-speed train loads.
基金Sponsored by the National High Technology Research and Development Program(Grant No.2012AA12A209)the National Natural Science Foundation of China(Grant No.41174028,41374033)+2 种基金the Key Laboratory Development Fund from the Ministry of Education of China(Grant No.618-277176)the LIESMARS Special Research Fund,the Research Start-up Fund from Wuhan Univesity(Grant No.618-273438)the Fundamental Research Funds for the Central Universities(Grant No.201161802020002)
文摘GNSS( global navigation satellite systems) are unavailable in challenging environments such as urban canyon and indoor locations due to signal blocking and jamming. Camera / IMU( inertial measurement units) integrated navigation systems can be alternatives to GNSS. In this paper,a tightly coupled Camera / IMU algorithm modeled by IEKF( iterated extended kalman filter) is presented. This tight integration approach uses image generated pixel coordinates to update the Kalman Filter directly. The developed algorithm is verified by a hybrid simulation,i.e. using inertial data from field test to fuse with simulated image feature measurements. The results show that the tight approach is superior to the loose integration when the image measurements are insufficient( i.e. less than three ground control points).
