Christine A. Ward-Paige

A multi-way data analysis approach for structural health monitoring of a cable-stayed bridge

Publisher: SAGE Publications

Date: 30-08-2019

DOI: 10.1177/1475921718790727

Abstract: A large-scale cable-stayed bridge in the state of New South Wales, Australia, has been extensively instrumented with an array of accelerometer, strain gauge, and environmental sensors. The real-time continuous response of the bridge has been collected since July 2016. This study aims at condition assessment of this bridge by investigating three aspects of structural health monitoring including damage detection, damage localization, and damage severity assessment. A novel data analysis algorithm based on incremental multi-way data analysis is proposed to analyze the dynamic response of the bridge. This method applies incremental tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies. A total of 15 different damage scenarios were investigated damage was physically simulated by locating stationary vehicles with different masses at various locations along the span of the bridge to change the condition of the bridge. The effect of damage on the fundamental frequency of the bridge was investigated and a maximum change of 4.4% between the intact and damage states was observed which corresponds to a small severity damage. Our extensive investigations illustrate that the proposed technique can provide reliable characterization of damage in this cable-stayed bridge in terms of detection, localization and assessment. The contribution of the work is threefold first, an extensive structural health monitoring system was deployed on a cable-stayed bridge in operation second, an incremental tensor analysis was proposed to analyze time series responses from multiple sensors for online damage identification and finally, the robustness of the proposed method was validated using extensive field test data by considering various damage scenarios in the presence of environmental variabilities.

Shark conservation, governance and management: The science–law disconnect

Publisher: Routledge

Date: 05-06-2014

DOI: 10.4324/9780203750292

Multifunctional cementitious composites with integrated self-sensing and hydrophobic capacities toward smart structural health monitoring

Publisher: Elsevier BV

Date: 04-2021

DOI: 10.1016/J.CEMCONCOMP.2021.103962

Characterization of carbon fiber reinforced polymer strengthened concrete and gap detection with a piezoelectric-based sensory technique

Publisher: SAGE Publications

Date: 11-10-2019

DOI: 10.1177/1475921718803790

Abstract: In this article, a piezoelectric-based sensory technique is proposed for detection of the gap between surfaces of a carbon fiber reinforced polymer plate and a concrete specimen and characterization of shrinkage of early-age concrete. The proposed technique uses the propagation properties of the guided waves in the carbon fiber reinforced polymer plate excited and received by piezoelectric transducers attached to an external surface of the carbon fiber reinforced polymer–strengthened concrete specimen. Measurements are conducted with fresh and hardened early-age concrete specimens and two carbon fiber reinforced polymer plates at different gaps. A piezoelectric actuator is excited using a sine burst signal, and the generated wave is received by a sensor after propagation along the specimen. The received signal at different gap values is used to detect a gap. To quantify the gap, damage indices, including correlation coefficient, peak-to-peak litude of resultant signal, and root-mean-square deviation, are used. The shrinkage of concrete is detected and predicted by comparing the damage indices at different gaps with the indices at different stages of early-age concrete. The proposed technique is relatively simple method using small transducers. It is one-sided, non-destructive, and cost-effective solution for gap detection and concrete characterization.

Hong Kong Polytechnic University

Location: China

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University Of Technology Sydney

Location: Australia

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University Of Western Australia

Location: Australia

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University Of Manchester

Location: United Kingdom of Great Britain and Northern Ireland

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EOceans

Location: Canada

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Dalhousie University

Location: Canada

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Zhejiang Sci-Tech University

Location: China

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Western Sydney University

Location: Australia

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Southwest Jiaotong University

Location: China

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Discovery Projects - Grant ID: DP110101328

Start Date: 2011

End Date: 03-2015

Amount: $255,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP160103197

Start Date: 03-2016

End Date: 06-2020

Amount: $225,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP220102045

Start Date: 11-2022

End Date: 10-2025

Amount: $403,000.00

Funder: Australian Research Council