Bayesian Multiple Linear Regression and New Modeling Paradigm for Structural Deflection Robust to Data Time Lag and Abnormal Signal-Reference-Cited by-同舟云学术

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Bayesian Multiple Linear Regression and New Modeling Paradigm for Structural Deflection Robust to Data Time Lag and Abnormal Signal

Published:2023-09-01 Issue:17 Volume:23 Page:19635-19647
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Zhao Hanwei¹^ORCID,Ding Youliang¹^ORCID,Meng Libo²,Qin Zuowei³,Yang Fan¹,Li Aiqun⁴

Affiliation:

1. Key Laboratory of Concrete and Prestressed Concrete Structures of the Ministry of Education, Southeast University, Nanjing, China

2. China Merchants Chongqing Communications Technology Research & Design Institute Company Ltd., Chongqing, China

3. Hubei Communications Planning and Design Institute Company Ltd., Wuhan, China

4. Beijing Advanced Innovation Center for Future Urban Design, Beijing University of Civil Engineering and Architecture, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10235271/10185198.pdf?arnumber=10185198

Reference44 articles.

1. Numerical Prediction of Long-Term Deformation for Prestressed Concrete Bridges under Random Heavy Traffic Loads

2. State-monitoring for abnormal vibration of bridge cables focusing on non-stationary responses: From knowledge in phenomena to digital indicators

3. Investigation of Live Load Deflection Limit for Steel Cable Stayed and Suspension Bridges

4. Sensor data-based probabilistic monitoring of time-history deflections of railway bridges induced by high-speed trains

5. Deflection-based multilevel structural condition assessment of long-span prestressed concrete girder bridges using a connected pipe system

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