• Smart Structures and Systems
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• 제14권4호
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• pp.679-697
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• 2014

The strain data acquired from structural health monitoring (SHM) systems play an important role in the state monitoring and damage identification of bridges. Due to the environmental complexity of civil structures, a better understanding of the actual strain data will help filling the gap between theoretical/laboratorial results and practical application. In the study, the multi-scale features of strain response are first revealed after abundant investigations on the actual data from two typical long-span bridges. Results show that, strain types at the three typical temporal scales of $10^5$, $10^2$ and $10^0$ sec are caused by temperature change, trains and heavy trucks, and have their respective cut-off frequency in the order of $10^{-2}$, $10^{-1}$ and $10^0$ Hz. Multi-resolution analysis and wavelet shrinkage are applied for separating and extracting these strain types. During the above process, two methods for determining thresholds are introduced. The excellent ability of wavelet transform on simultaneously time-frequency analysis leads to an effective information extraction. After extraction, the strain data will be compressed at an attractive ratio. This research may contribute to a further understanding of actual strain data of long-span bridges; also, the proposed extracting methodology is applicable on actual SHM systems.

• Smart Structures and Systems
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• 제20권2호
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• pp.139-150
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• 2017

The structural strain plays a significant role in structural condition assessment of in-service bridges in terms of structural bearing capacity, structural reliability level and entire safety redundancy. Therefore, it has been one of the most important parameters concerned by researchers and engineers engaged in structural health monitoring (SHM) practices. In this paper, an SHM system instrumented on the Jiubao Bridge located in Hangzhou, China is firstly introduced. This system involves nine subsystems and has been continuously operated for five years since 2012. As part of the SHM system, a total of 166 fiber Bragg grating (FBG) strain sensors are installed on the bridge to measure the dynamic strain responses of key structural components. Based on the strain monitoring data acquired in recent two years, the strain-based structural condition assessment of the Jiubao Bridge is carried out. The wavelet multi-resolution algorithm is applied to separate the temperature effect from the raw strain data. The obtained strain data under the normal traffic and wind condition and under the typhoon condition are examined for structural safety evaluation. The structural condition rating of the bridge in accordance with the AASHTO specification for condition evaluation and load and resistance factor rating of highway bridges is performed by use of the processed strain data in combination with finite element analysis. The analysis framework presented in this study can be used as a reference for facilitating the assessment, inspection and maintenance activities of in-service bridges instrumented with long-term SHM system.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2016년도 추계 학술논문 발표대회
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• pp.130-131
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• 2016

This study was performed for application of Structural Health Monitoring system of large structures. In order to evaluate damage of a structure, strain data of truss members that are changing with damage are gained by FEM analysis program. These data are used to train Artificial Neural Network(ANN), and this ANN algorithm can be used to analysis strain data for evaluating damage of the truss members.

• Earthquakes and Structures
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• 제8권3호
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• pp.541-553
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• 2015

Structural Health Monitoring (SHM) systems can provide valuable information regarding the safety of structures during and after ground motions which can be used by authorities to reduce post-earthquake hazards. Strain gages as a key element play an important role in the success of SHM systems. Reducing the number of required strain gages while keeping the efficiency of SHM system not only can reduce the cost of structural health monitoring but also avoids storage and process of uninformative data. In this study, a method based on performance based seismic design of structures is proposed for ideal placement of stain gages in structures. The robustness and efficiency of the proposed method is demonstrated through installation of strain gages on an Airport Traffic Control (ATC) Tower. The obtained results show that the number of required strain gages decrease significantly.

• Smart Structures and Systems
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• 제31권6호
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• pp.585-599
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• 2023

Field monitoring techniques offer an attractive approach for understanding bridge behavior under in-service loads. However, the investigations on bridge behavior under high-speed train load using field monitoring data are limited. The focus of this study is to explore the structural behavior of an in-service long-span steel truss arch bridge based on field monitoring data. First, the natural frequencies of the structure, as well as the train driving frequencies, are extracted. Then, the train-induced bearing displacement and structural strain are explored to identify the effects of train loads and bearings. Subsequently, a sensitivity analysis is performed for the impact factor of strain responses with respect to the train speed, train weight, and temperature to identify the fundamental issues affecting these responses. Additionally, a similar sensitivity analysis is conducted for the peak acceleration. The results indicate that the friction force in bearings provides residual deformations when two consecutive trains are in opposite directions. In addition, the impact factor and peak acceleration are primarily affected by train speed, particularly near train speeds that result in the resonance of the bridge response. The results can provide additional insight into the behavior of the long-span steel truss bridges under in-service high-speed train loads.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2007년도 정기총회 및 학술발표대회
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• pp.429-432
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• 2007

For smart structure technologies, the interests in wireless sensor networks for structural health monitoring are growing. The wireless sensor networks reduce the installation of the wire embedded in the whole structure and save the costs. But the wireless sensor networks have lots of limits and there are lots of researches and developments of wireless sensor and the network for data process. Most of the researches of wireless sensor network is applying to the civil engineering structure and the researches for the highrise building are required. And strain-based SHM gives the local damage information of the structures which acceleration-based SHM can not. In this paper, concept of wireless sensor network for structural health monitoring of highrise building is suggested. And verifying the feasibility of the strain-based SHM a strain sensor board has developed and tested by experiments.

• Smart Structures and Systems
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• 제26권1호
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• pp.11-21
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• 2020

The hinge joint is the key to the overall cooperative working performance of the assembled beam bridge, and it is also the weakest part during the service period. This paper proposes a method for monitoring and evaluating the lateral cooperative working performance of fabricated beam bridges based on dynamic strain correlation coefficient indicator. This method is suitable for monitoring and evaluation of hinge joints status between prefabricated girders and overall cooperative working performance of bridge, without interruption of traffic and easy implementation. The remote cloud monitoring and diagnosis system was designed and implemented on a real assembled beam bridge. The algorithms of data preprocessing, online indicator extraction and status diagnosis were given, and the corresponding software platform and scientific computing environment for cloud operation were developed. Through the analysis of real bridge monitoring data, the effectiveness and accuracy of the method are proved and it can be used in the health monitoring system of such bridges.

• Smart Structures and Systems
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• 제11권4호
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• pp.365-386
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• 2013

Monitoring systems currently applied to concrete bridges include strain gauges, inclinometers, accelerometers and displacement transducers. In general, vertical displacements are one of the parameters that more often need to be assessed because their information reflects the overall response of the bridge span. However, the implementation of systems to continuously and directly observe vertical displacements is known to be difficult. On the other hand, strain gauges and inclinometers are easier to install, but their measurements provide no more than indirect information regarding the bridge deflection. In this context, taking advantage of the information collected through strain gauges and inclinometers, and the processing capabilities of current computers, a procedure to evaluate bridge girder deflections based on polynomial functions is presented. The procedure has been implemented in an existing software system - MENSUSMONITOR -, improving the flexibility in the data handling and enabling faster data processing by means of real time visualization capabilities. Benefiting from these features, a comprehensive analysis aiming at assessing the suitability of polynomial functions as an approximate solution for deflection curves, is presented. The effect of boundary conditions and the influence of the order of the polynomial functions on the accuracy of results are discussed. Some recommendations for further instrumentation plans are provided based on the results of the present analysis. This work is supported throughout by monitoring data collected from a laboratory beam model and two full-scale bridges.

• 비파괴검사학회지
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• 제32권6호
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• pp.669-677
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• 2012

This study presents a method to monitor cable force using wireless sensor nodes and piezoelectric sensors. The following approaches are carried out to achieve the objective. Firstly, the principle of piezoelectric materials (e.g., PZT) as strain sensors is reviewed. A cable force estimation method using dynamic features of cables measured by piezoelectric materials is presented. Secondly, the design of an automated cable force monitoring system using the data acquisition sensor-node Imote2/SHM-DAQ is described. The sensor node is originally developed by University of Illinois at Urbana-Champaign and is adopted in this study to monitor strain-induced voltage from PZT sensors. The advantages of the system are cheap, and eligible for wireless communication and automated operation. Finally, the feasibility of the proposed monitoring system is evaluated on a lab-scaled cable.

• Smart Structures and Systems
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• 제23권3호
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• pp.263-278
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• 2019

Moving train load parameters, including train speed, axle spacing, gross train weight and axle weights, are identified based on strain-monitoring data. In this paper, according to influence line theory, the classic moving force identification method is enhanced to handle time-varying velocity of the train. First, the moments that the axles move through a set of fixed points are identified from a series of pulses extracted from the second derivative of the structural strain response. Subsequently, the train speed and axle spacing are identified. In addition, based on the fact that the integral area of the structural strain response is a constant under a unit force at a unit speed, the gross train weight can be obtained from the integral area of the measured strain response. Meanwhile, the corrected second derivative peak values, in which the effect of time-varying velocity is eliminated, are selected to distribute the gross train weight. Hence the axle weights could be identified. Afterwards, numerical simulations are employed to verify the proposed method and investigate the effect of the sampling frequency on the identification accuracy. Eventually, the method is verified using the real-time strain data of a continuous steel truss railway bridge. Results show that train speed, axle spacing and gross train weight can be accurately identified in the time domain. However, only the approximate values of the axle weights could be obtained with the updated method. The identified results can provide reliable reference for determining fatigue deterioration and predicting the remaining service life of railway bridges.