ORCID Profile
0000-0002-4807-7934
Current Organisation
Queensland University of Technology
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Civil Engineering | Infrastructure Engineering and Asset Management | Structural Engineering
Civil Building Management and Services | Road Infrastructure and Networks |
Publisher: Informa UK Limited
Date: 20-02-2021
Publisher: Springer Singapore
Date: 04-09-2020
Publisher: SAGE Publications
Date: 11-2013
DOI: 10.1155/2013/254785
Abstract: Structural health monitoring of the cable-anchorage system is very important to secure the integrity of the cable-stayed bridge. The cable-anchorage system carries most of the self-weight, so that any damage in the system may significantly reduce the load carrying capacity of the bridge. This study presents a multiscale structural health monitoring of the cable-anchorage system using piezoelectric PZT sensors. Firstly, the electromechanical impedance response is utilized for alerting the change in anchorage zone caused by the loss of cable force or local anchorage damage. Secondly, the dynamic strain of cable is utilized for classifying the damage type. Thirdly, the loss of cable force and the anchorage damage are quantified by a frequency-based cable force model and an impedance-based damage estimation model, respectively. The feasibility of the approach is evaluated from the experiment on a lab-scale cable-anchorage model for which several damage scenarios are simulated about cable damage and anchorage damage.
Publisher: Nova Science Publishers
Date: 2022
DOI: 10.52305/QHVI3457
Publisher: SAGE Publications
Date: 10-09-2012
DOI: 10.1155/2012/167120
Abstract: Temperature-compensated damage monitoring in steel girder connections by using wireless acceleration-impedance sensor nodes is experimentally examined. To achieve the objective, the following approaches are implemented. Firstly, wireless acceleration-impedance sensor nodes are described on the design of hardware components to operate. Secondly, temperature-compensated damage monitoring scheme for steel girder connections is designed by using the temperature compensation model and acceleration-impedance-based structural health monitoring methods. Finally, the feasibility of temperature-compensated damage monitoring scheme by using wireless acceleration-impedance sensor nodes is experimentally evaluated from damage monitoring in a lab-scaled steel girder with bolted connection joints.
Publisher: SPIE
Date: 24-03-2011
DOI: 10.1117/12.879613
Publisher: SPIE
Date: 24-03-2011
DOI: 10.1117/12.879614
Publisher: SAGE Publications
Date: 06-2012
DOI: 10.1260/1369-4332.15.6.871
Abstract: In this study, a technique using wireless impedance sensor node and interface washer is proposed for monitoring damage in structural connections of bridges. In order to achieve the objective, the following approaches are implemented. First, a wireless impedance sensor node is designed for automated and cost-efficient monitoring in structural connections. Second, impedance-based algorithms are embedded in the wireless impedance sensor node for autonomous monitoring of structural connections. Third, a tensile-force monitoring technique using an interface washer is proposed to overcome limitations of the wireless impedance sensor node such as measureable ranges with narrow frequency band, and the proposed technique is numerically validated. Finally, the performance of the wireless impedance sensor node and the interface washer is experimentally evaluated in cable-anchor connection and bolted connection models.
Publisher: Informa UK Limited
Date: 02-2022
Publisher: SAGE Publications
Date: 11-2013
DOI: 10.1155/2013/804516
Abstract: Wireless sensor networks provide a lot of advantages for vibration monitoring of bridges. The installation time and implementation cost of the monitoring system are greatly reduced by the adoption of this innovative technology. This paper presents a long-term vibration monitoring of the Hwamyung cable-stayed bridge in Korea using an Imote2-platformed wireless sensor network. First, the wireless vibration monitoring system of the bridge is briefly described by outlining the test history, the design of wireless sensor system, and the sensor deployment. Next, the vibration behaviors of the bridge are experimentally examined with respect to the variation of temperature, the wind loads induced by typhoons, and the change of bridge deck mass caused by pavement.
Publisher: SPIE
Date: 26-04-2012
DOI: 10.1117/12.917541
Publisher: World Scientific Pub Co Pte Lt
Date: 09-2020
DOI: 10.1142/S0219455420420079
Abstract: Many existing damage identification or quantification methods can be employed only if the internal and external mass changes are negligible when tested at two different states of a structure. This paper presents a new Modal Kinetic Energy (MKE)-based method to detect and quantify damage using modal properties of structures, which can be employed even in situations when mass change is not more than a certain extent. A new damage sensitivity parameter has been developed using measured modal characteristics of baseline structure. The MKE change (MKEC) concept is then employed to locate damage and to estimate relative perturbation at each element. The relative damage extent vector is estimated by searching the best correlation between the analytical and experimental MKEC vectors with the help of genetic algorithm optimization tool. The extent of damage is calculated after computing damage scaling coefficient using measured eigenvalue change vector. A numerical study is carried out on a simply supported single span beam to confirm its performance under various test conditions. The robustness of the proposed MKE method and the significance of mass variation in the damage detection approach are evaluated by comparing the damage quantification results with a traditional approach. Finally, the proposed damage detection method is applied on a two-span simply supported beam for single and multiple damage scenarios by extracting the modal properties experimentally. The results revealed that the proposed approach is capable of detecting and estimating single and multiple damages with reasonable accuracy even in moderate noise contaminated and mass change environments.
Publisher: World Scientific Pub Co Pte Ltd
Date: 09-2020
DOI: 10.1142/S0219455420420134
Abstract: Irrespective to how well structures were built, they all deteriorate. Herein, deterioration is defined as a slow and continuous reduction of structural performance, which if prolonged can lead to damage. Deterioration occurs due to different factors such as ageing, environmental and operational (E& O) variations including those due to service loads. Structural performance can be defined as load-carrying capacity, deformation capacity, service life and so on. This paper aims to develop an effective method to detect and locate deterioration in the presence of E& O variations and high measurement noise content. For this reason, a novel vibration-based deterioration assessment method is developed. Since deterioration alters the unique vibration characteristics of a structure, it can be identified by tracking the changes in the vibration characteristics. This study uses enhanced autoregressive (AR) time-series models to fit the vibration response data of a structure. Then, the statistical hypotheses of chi-square variance test and two-s le [Formula: see text]-test are applied to the model residuals. To precisely evaluate changes in the vibration characteristics, an integrated deterioration identification (DI) is defined using the calculated statistical hypotheses and a H el filter is used to detect and remove false positive and negative results. Model residual is the difference between the predicted signal from the time series model and the actual measured response data at each time interval. The response data of two numerically simulated case studies of 3-storey and 20-storey reinforced concrete (RC) shear frames contaminated with different noise contents demonstrate the efficacy of the proposed method. Multiple deterioration and damage locations, as well as preventive maintenance actions, are also considered in these case studies. Furthermore, the method was successfully verified utilizing measured data from an experiment carried out on a box-girder bridge (BGB) structure.
Publisher: Queensland University of Technology
Publisher: IOP Publishing
Date: 14-06-2016
Publisher: SAGE Publications
Date: 03-11-2019
Abstract: Damage identification for complex structures is a challenging task due to the large amount of structural elements, limited number of measured modes and uncertainties in referenced numerical models. This article presents a study on enhancing the effectiveness of modal characteristics correlation methods for damage identification of complex structures. First, a correlation method using change in the ratio of modal strain energy to eigenvalue is introduced. Damage information is determined via a forward approach by optimizing the correlation level between the patterns of the analytical and measured changes in the ratio of modal strain energy to eigenvalue. Different from traditional optimization-based forward methods that require accurate numerical models, damage sensitivity coefficients of the ratio of modal strain energy to eigenvalue are directly estimated from the experimental modal information. To enhance the damage identification capability, both the elemental modal strain energy–eigenvalue ratio and the total modal strain energy–eigenvalue ratio components are examined in the correlation function. Second, a sensitivity-weighted search space scheme incorporated with genetic algorithm is developed to overcome the ill-posed problem that causes false detection errors. Finally, the correlation method and the enhanced technique are experimentally tested on a complex truss model with nearly 100 elements. To deal with the huge number of degrees of freedom in this structure, a multi-layout roving test with the adoption of redundant channels is designed, and a three-criterion strategy is used for the selection of modes. Results demonstrate the effectiveness of the proposed damage assessment framework to locate and estimate damage in complex truss structures.
Publisher: SAGE Publications
Date: 07-2019
Abstract: Structural health monitoring plays a significant role in providing information regarding the performance of structures throughout their life spans. However, information that is directly extracted from monitored data is usually susceptible to uncertainties and not reliable enough to be used for structural investigations. Finite element model updating is an accredited framework that reliably identifies structural behavior. Recently, the modular Bayesian approach has emerged as a probabilistic technique in calibrating the finite element model of structures and comprehensively addressing uncertainties. However, few studies have investigated its performance on real structures. In this article, modular Bayesian approach is applied to calibrate the finite element model of a lab-scaled concrete box girder bridge. This study is the first to use the modular Bayesian approach to update the initial finite element model of a real structure for two states—undamaged and damaged conditions—in which the damaged state represents changes in structural parameters as a result of aging or overloading. The application of the modular Bayesian approach in the two states provides an opportunity to examine the performance of the approach with observed evidence. A discrepancy function is used to identify the deviation between the outputs of the experimental and numerical models. To alleviate computational burden, the numerical model and the model discrepancy function are replaced by Gaussian processes. Results indicate a significant reduction in the stiffness of concrete in the damaged state, which is identical to cracks observed on the body of the structure. The discrepancy function reaches satisfying ranges in both states, which implies that the properties of the structure are predicted accurately. Consequently, the proposed methodology contributes to a more reliable judgment about structural safety.
Publisher: SAGE Publications
Date: 10-2012
DOI: 10.1155/2012/709208
Abstract: A multiscale wireless sensor system is designed for vibration- and impedance-based structural health monitoring. In order to achieve the objective, the following approaches are implemented. Firstly, smart sensor nodes for vibration and impedance monitoring are designed. In the design, Imote2 platform which has high performance microcontroller, large amount of memory, and flexible radio communication is implemented to acceleration and impedance sensor nodes. Acceleration sensor node is modified to measure PZT's dynamic strain along with acceleration. A solar-power harvesting unit is implemented for power supply to the sensor system. Secondly, operation logics of the multi-scale sensor nodes are programmed based on the concept of the decentralized sensor network. Finally, the performance of the multi-scale sensor system is evaluated on a lab-scale beam to examine the long-term monitoring capacities under various weather conditions.
Publisher: American Scientific Publishers
Date: 07-2012
Publisher: SPIE
Date: 26-04-2012
DOI: 10.1117/12.917538
Publisher: SPIE
Date: 26-04-2012
DOI: 10.1117/12.917539
Publisher: SPIE
Date: 26-04-2012
DOI: 10.1117/12.917543
Publisher: World Scientific Pub Co Pte Lt
Date: 09-2020
DOI: 10.1142/S0219455420420031
Abstract: Structural health monitoring data has been widely acknowledged as a significant source for evaluating the performance and health conditions of structures. However, a holistic framework that efficiently incorporates monitored data into structural identification and, in turn, provides a realistic life-cycle performance assessment of structures is yet to be established. There are different sources of uncertainty, such as structural parameters, computer model bias and measurement errors. Neglecting to account for these factors results in unreliable structural identifications, consequent financial losses, and a threat to the safety of structures and human lives. This paper proposes a new framework for structural performance assessment that integrates a comprehensive probabilistic finite element model updating approach, which deals with various structural identification uncertainties and structural reliability analysis. In this framework, Gaussian process surrogate models are replaced with a finite element model and its associate discrepancy function to provide a computationally efficient and all-round uncertainty quantification. Herein, the structural parameters that are most sensitive to measured structural dynamic characteristics are investigated and used to update the numerical model. Sequentially, the updated model is applied to compute the structural capacity with respect to loading demand to evaluate its as-is performance. The proposed framework’s feasibility is investigated and validated on a large lab-scale box girder bridge in two different health states, undamaged and damaged, with the latter state representing changes in structural parameters resulted from overloading actions. The results from the box girder bridge indicate a reduced structural performance evidenced by a significant drop in the structural reliability index and an increased probability of failure in the damaged state. The results also demonstrate that the proposed methodology contributes to more reliable judgment about structural safety, which in turn enables more informed maintenance decisions to be made.
Publisher: Elsevier BV
Date: 03-2021
Start Date: 2022
End Date: 2024
Funder: Australian Research Council
View Funded ActivityStart Date: 2022
End Date: 12-2024
Amount: $350,000.00
Funder: Australian Research Council
View Funded Activity