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contributor authorMasaru Kitahara
contributor authorDaichi Masuda
contributor authorKai Xue
contributor authorTomonori Nagayama
contributor authorDi Su
contributor authorHirofumi Tanaka
date accessioned2024-12-24T10:13:50Z
date available2024-12-24T10:13:50Z
date copyright9/1/2024 12:00:00 AM
date issued2024
identifier otherAJRUA6.RUENG-1259.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4298534
description abstractThis study presents an efficient, but effective, approach to infer railroad track geometries and locate hanging sleepers from the car body responses. A half-car model is employed to represent the bounce and pitch motions of the car body, and an augmented state space model is derived in which the track geometry is treated as a state variable. In the Kalman filter process, both the process and observation noise covariance matrices are adaptively updated by the Robbins-Monro algorithm, and the resulting state estimates are further smoothed using the Rauch-Tung-Striebel smoother. In addition, the output-only model optimization can determine the unknown vehicle parameters by minimizing a novel cost function that accounts for engineering constraints on the railroad track geometries. Local discrepancy in the inferred track geometries using two vehicles of different weight is then used as an indicator to identify hanging sleepers. The feasibility of the proposed framework is first demonstrated upon a numerical simulation, and it is furthermore applied to the experimental measurements on passenger vehicles in Japan.
publisherAmerican Society of Civil Engineers
titleTrack Geometry Estimation and Hanging Sleeper Detection Using Vehicle Dynamic Responses with Unknown System Parameters
typeJournal Article
journal volume10
journal issue3
journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
identifier doi10.1061/AJRUA6.RUENG-1259
journal fristpage04024044-1
journal lastpage04024044-16
page16
treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2024:;Volume ( 010 ):;issue: 003
contenttypeFulltext


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