Technical Papers
Aug 17, 2016

Detection of Track Static Regularities Based on a Laser Tracker

Publication: Journal of Surveying Engineering
Volume 143, Issue 2

Abstract

This study proposes a method for detecting track static regularities based on a laser tracker. Given the laser tracker’s advantages of high tracking-measuring accuracy and high sampling rate, the proposed method integrates static and dynamic measurements and is simultaneously applicable to both fine-adjustment measurement in the construction stage and detection in the operation-maintenance stage. In this paper, the design and implementation of the hardware-integration scheme, software development, and data processing are discussed. To verify the detection and data-processing methods for track static regularity, a case study was conducted on part of the Shanghai Metro Line 13 at Nature Museum Station. An SGJ-T-CEC-I passenger-dedicated line track geometric state measurement device of China Railway Engineering Consulting Group Co., Ltd., was used for comparative analysis. The feasibility and high accuracy of the proposed method were verified by using this device.

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Acknowledgments

This work was supported by the China Special Fund for Surveying, Mapping and Geoinformation Research in the Public Interest (Grant HY14122136) and the Planned Scientific Programs of Shanghai (Grant 15ZR1443700).

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Published In

Go to Journal of Surveying Engineering
Journal of Surveying Engineering
Volume 143Issue 2May 2017

History

Received: Dec 30, 2015
Accepted: Jun 8, 2016
Published online: Aug 17, 2016
Discussion open until: Jan 17, 2017
Published in print: May 1, 2017

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Authors

Affiliations

Professor, College of Surveying and Geo-informatics and Key Laboratory of Advanced Engineering Surveying of NASMG (National Administration of Surveying, Mapping and Geoinformation), Tongji Univ., 1239 Siping Rd., Shanghai 200092, China. E-mail: [email protected]
Assistant Professor, College of Resource Environment and Tourism, Capital Normal Univ., 105 North Xisanhuan Rd., Beijing 100048, China (corresponding author). E-mail: [email protected]
Xuan Wang
M.S. Candidate, College of Surveying and Geo-informatics, Tongji Univ., 1239 Siping Rd., Shanghai 200092, China.
Yueyin Zhou
Ph.D. Candidate, College of Surveying and Geo-informatics, Tongji Univ., 1239 Siping Rd., Shanghai, China.

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