• Earthquakes and Structures
• /
• 제22권5호
• /
• pp.503-515
• /
• 2022

This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.

• Earthquakes and Structures
• /
• 제12권6호
• /
• pp.673-687
• /
• 2017

A three-dimensional; structural health monitoring; vertical; planar; cross-sample entropy; multiscaleA three-dimensional structural health monitoring (SHM) system based on multiscale entropy (MSE) and multiscale cross-sample entropy (MSCE) is proposed in this paper. The damage condition of a structure is rapidly screened through MSE analysis by measuring the ambient vibration signal on the roof of the structure. Subsequently, the vertical damage location is evaluated by analyzing individual signals on different floors through vertical MSCE analysis. The results are quantified using the vertical damage index (DI). Planar MSCE analysis is applied to detect the damage orientation of damaged floors by analyzing the biaxial signals in four directions on each damaged floor. The results are physically quantified using the planar DI. With progressive vertical and planar analysis methods, the damaged floors and damage locations can be accurately and efficiently diagnosed. To demonstrate the performance of the proposed system, performance evaluation was conducted on a three-dimensional seven-story steel structure. According to the results, the damage condition and elevation were reliably detected. Moreover, the damage location was efficiently quantified by the DI. Average accuracy rates of 93% (vertical) and 91% (planar) were achieved through the proposed DI method. A reference measurement of the current stage can initially launch the SHM system; therefore, structural damage can be reliably detected after major earthquakes.

• Smart Structures and Systems
• /
• 제5권4호
• /
• pp.469-482
• /
• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.

• Wind and Structures
• /
• 제21권6호
• /
• pp.693-707
• /
• 2015

The efficiency of wind turbines (WT) is primarily reflected in their ability to generate electricity at any time. Downtimes of WTs due to "conventional" inspections are cost-intensive and undesirable for investors. For this reason, there is a need for structural health monitoring (SHM) systems, to enable service and maintenance on demand and to increase the inspection intervals. In general, monitoring increases the cost effectiveness of WTs. This publication concentrates on the application of two vibration-based SHM algorithms for stability and structural change monitoring of offshore WTs. Only data driven, output-only algorithms based on stochastic subspace identification (SSI) in time domain are considered. The centerpiece of this paper deals with the rough mathematical description of the dynamic behavior of offshore WTs and with the basic presentation of stochastic subspace-based algorithms and their application to these structures. Due to the early stage of the industrial application of SHM on offshore WT on the one side and the required confidentiality to the plant manufacturer and operator on the other side, up to now it is not possible to analyze different isolated structural damages resp. changes in a systematic manner, directly by means of in-situ measurement and to make these "acknowledgements" publicly available. For this reason, the sensitivity of the methods for monitoring purposes are demonstrated through their application on long time measurements from a 1:10 large scale test rig of an offshore WT under different conditions: undamaged, different levels of loosened bolt connections between tower parts, different levels of fouling, scouring and structure inclination. The limitation and further requirements for the approaches and their applicability on real foundations are discussed along the paper.

• International journal of advanced smart convergence
• /
• 제7권4호
• /
• pp.197-205
• /
• 2018

Nowadays, wireless sensor networks (WSNs) have been widely adopted in structural health monitoring (SHM) systems for social overhead capital (SOC) public infrastructures. Structural health information, environmental disturbances and sudden changes of weather conditions, damage detections, and external load quantizing are among the capabilities required of SHM systems. These information requires an efficient transmission with which an efficient mobility management support for wireless networks can provide. This paper deals with the analysis of mobility management schemes in order to address the real-time requirement of data traffic delivery for critical SHM information. The host-based and network-based mobility management protocols have been identified and the advantages of network mobility (NEMO) enabled Proxy Mobile Internet Protocol version 6 (PMIPv6) have been leveraged in order to address the SHM information transmission needs. The scheme allows an efficient information transmission as it improves the handover performance due to shortened handover latency as well as reduced signaling overhead.

• 한국구조물진단유지관리공학회 논문집
• /
• 제19권3호
• /
• pp.10-21
• /
• 2015

구조물 건전성 모니터링은 센서로부터 구조물의 응답을 수집하고 분석하여 구조물의 정확한 상태를 진단하는 기술이다. 최근 노후화된 구조물의 증가로 인하여, 지속가능한 사회 발전을 위해 더욱 발달된 구조물 건전성 모니터링 기술이 요구되고 있다. 최신 구조물 건전성 모니터링 기술 중 하나인 무선 스마트 센서와 센서 네트워크 기술은 기존의 유선 방식의 모니터링 시스템과 비교하여 더욱 효율적이며 경제적인 모니터링 시스템의 구축을 가능하게 하는 기술이다. 최근까지도 관련 연구자들은 스마트 센서의 성능 및 확장성 향상을 위하여 연구개발을 진행하고, 다양한 실내, 실외 실험을 통한 성능 테스트를 진행하였다. 본 논문에서는 최근 (2010년 이후를 중심으로)에 개발된 스마트 센서의 하드웨어, 소프트웨어, 그리고 응용 사례들을 정리함으로써, 구조물 건전성 모니터링을 위한 스마트 센서의 최신 연구동향에 대해 소개하고자 한다.

• 비파괴검사학회지
• /
• 제29권4호
• /
• pp.269-282
• /
• 2009

This paper presents a novel approach for Lamb wave based structural health monitoring(SHM) in honeycomb aluminum panels. In this study, a suite of three signal processing algorithms are employed to improve the damage detection capability. The signal processing algorithms used include wavelet attenuation, correlation coefficients of power density spectra, and triangulation of reflected waves. Piezoelectric transducers are utilized as both sensors and actuators for Lamb wave propagation. These SHM algorithms are built into a MatLab interface that integrates and automates the hardware and software operations and displays the results for each algorithm to the analyst for side by side comparison. The effectiveness of each of these signal processing algorithms for SHM in honeycomb aluminum panels under a variety of damage conditions is then demonstrated.

• Journal of electromagnetic engineering and science
• /
• 제15권2호
• /
• pp.104-110
• /
• 2015

As civil infrastructures continue to deteriorate, the demand for structural health monitoring (SHM) has increased. Despite its outstanding capability for damage identification, many conventional SHM techniques are restricted to huge structures because of their wired system for data and power transmission. Although wireless data transmission using radio-frequency techniques has emerged vis-$\grave{a}$-vis wireless sensors in SHM, the power supply issue is still unsolved. Normal batteries cannot support civil infrastructure for no longer than a few decades. In this study, we develop a magnetic resonance-based wireless power transmission system, and its performance is validated in three different mediums: air, unreinforced concrete, and reinforced concrete. The effect of concrete and steel rebars is analyzed.

• 한국산학기술학회논문지
• /
• 제18권1호
• /
• pp.709-714
• /
• 2017

다리 혹은 건물과 같은 구조물들은 그들의 안전상태를 진단하기 위하여 지속적으로 점검할 필요가 있다. 그러나 사람이 이러한 구조물의 모든 지점을 직접적으로 접근하여 점검해야 하는 치명적인 어려움이 있다. 이러한 어려움을 극복하기 위하여 오늘날에는 WSN(Wireless Sensor Node)를 이용한 SHM(Structural Health Monitoring)에 대한 많은 연구가 활발히 이루어지고 있다. 본 논문에서는 WSN을 이용한 SHM에서 보다 정밀한 점검을 위하여 실시간 처리를 제공하는 Xenomai의 성능을 기존 리눅스 커널과 실험적으로 비교 평가하였다. 이를 위하여 상용 임베디드 보드인 라즈베리 파이(Raspberry Pi) 보드의 기존 리눅스 커널에 Xenomai를 패치 시키고, 캔틸레버 빔(cantilever beam)의 고유 주파수(natural frequency)를 분석하기 위하여 가속도 센서로부터 z-축 진동 데이터를 주기적으로 읽어 들이는 태스크를 구현하였다. 동일한 방법으로 기존 리눅스 커널에서 데이터를 측정한 후, Smart Office Analyzer를 이용하여 캔틸레버 빔의 고유 주파수를 분석하였다. 마지막으로, WSN을 위한 Xenomai의 타당성을 검토하기 위하여 가속도 센서의 z-축 진동 데이터를 유선으로 측정하여 동일한 방법으로 비교 분석하였다.

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