Data-driven structural condition assessment for highway bridges under operational environments

Yuan, Ye

Data-driven structural condition assessment for highway bridges under operational environments

Yuan, Ye

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Publication Type:: Thesis
Issue Date:: 2022

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Field	Value	Language
dc.contributor.author	Yuan, Ye
dc.date.accessioned	2023-03-31T03:28:59Z
dc.date.available	2023-03-31T03:28:59Z
dc.date.issued	2022
dc.identifier.uri	http://hdl.handle.net/10453/168917
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	Bridges are key transportation infrastructure. In Australia, over 60% of bridges on local roads are over 50 years old. With the deterioration of the bridge performance and ever-increasing amount of traffic, the bridge safety is becoming a concern for engineering community. A method that can assess the bridge's condition in real-time is urgently needed. Structural health monitoring (SHM) provides a practical tool to assess and predict the condition of bridges. From the perspective of the real-time monitoring, the main factor that hinders an ideal bridge condition assessment is the uncertain operational environment. Existing SHM methods either try to assess the structural performance under the controlled environmental conditions or eliminate the influence of the operational environment using long-term monitoring data to train or calibrate the condition assessment model. These two ideas cannot fit the target of the real-time monitoring. To achieve the real-time monitoring, this study proposes a new damage sensitive feature (DSF) based on moving principal component analysis (MPCA). The two main operational environmental factors: environmental temperature and traffic loads, are studied in the assessment process to verify the robustness and practicality of the proposed DSF. The numerical and experimental study has been carried out to show the reliability and accuracy of the proposed method. The mechanism of the DSF variation induced by changes in environmental parameters are discussed to show the interpretability of the proposed DSF. The value of the DSF can precisely reflect bridge's overall vibration 'rhythm' which is reliable to reflect the bridge's instantaneous vibration state. This DSF is not restricted to several few pre-considered parameters but reflects the bridge's damage condition from a dynamic perspective.	en_US.UTF-8
dc.format	Thesis (ME)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/168917/2/02whole.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2022 Ye Yuan
dc.rights	au.edu.uts.lib/ppc
dc.title	Data-driven structural condition assessment for highway bridges under operational environments	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

Bridges are key transportation infrastructure. In Australia, over 60% of bridges on local roads are over 50 years old. With the deterioration of the bridge performance and ever-increasing amount of traffic, the bridge safety is becoming a concern for engineering community. A method that can assess the bridge's condition in real-time is urgently needed. Structural health monitoring (SHM) provides a practical tool to assess and predict the condition of bridges. From the perspective of the real-time monitoring, the main factor that hinders an ideal bridge condition assessment is the uncertain operational environment. Existing SHM methods either try to assess the structural performance under the controlled environmental conditions or eliminate the influence of the operational environment using long-term monitoring data to train or calibrate the condition assessment model. These two ideas cannot fit the target of the real-time monitoring. To achieve the real-time monitoring, this study proposes a new damage sensitive feature (DSF) based on moving principal component analysis (MPCA). The two main operational environmental factors: environmental temperature and traffic loads, are studied in the assessment process to verify the robustness and practicality of the proposed DSF. The numerical and experimental study has been carried out to show the reliability and accuracy of the proposed method. The mechanism of the DSF variation induced by changes in environmental parameters are discussed to show the interpretability of the proposed DSF. The value of the DSF can precisely reflect bridge's overall vibration 'rhythm' which is reliable to reflect the bridge's instantaneous vibration state. This DSF is not restricted to several few pre-considered parameters but reflects the bridge's damage condition from a dynamic perspective.

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http://hdl.handle.net/10453/168917