GB-RAR Deformation Information Estimation of High-Speed Railway Bridge in Consideration of the Effects of Colored Noise

Author:

Wang Cheng,Zhou LvORCID,Ma Jun,Shi Anping,Li Xinyi,Liu Lilong,Zhang Zhi,Zhang DiORCID

Abstract

Safety assessment must accurately grasp deformation information of a high-speed railway bridge. When the ground-based radar collected high-frequency data, white and colored noises will be present in the radar signal due to the influence of environment and instrument errors. The existence of the above-mentioned two kinds of noises will affect the accurate estimation of deformation information. Based on the above situation, a ground-based real aperture radar (GB-RAR) deformation information estimation method considering the effect of colored noise was proposed in this work. The proposed method was applied to the safety monitoring and analysis of East Lake High-tech Bridge during the Wuhan Metro Line 11 shield tunnel crossing underneath this bridge. First, the settlement deformation time series of the bridge was derived based on GB-RAR, and it was verified by leveling at an accuracy better than 0.27 mm. Second, white, and colored noises were detected in the denoised settlement deformation time series through a power spectral analysis and maximum likelihood estimation, and the colored noise spectral indexes were approximately −1. Finally, according to the proposed method, the estimated settlement rates of No. 7 and 8 piers were 0.0112 ± 0.0026 and −0.0046 ± 0.0053 mm/h, and the accumulative settlement values were −0.40 and −0.16 mm, respectively. The results were in good agreement with the results of leveling measurement and more accurate than those of the deformation information estimation method without considering the effect of colored noise. The research results showed the reliability and effectiveness of the method in this work, and the bridge was stable and safe during the monitoring period.

Funder

Natural Science Foundation of Hubei

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3