• Structural Monitoring and Maintenance
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• 제5권1호
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• pp.111-127
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• 2018

Horizontal displacement of high-rise building is an essential index for assessing the structural performance and safety. In this paper, a novel inclinometer-based method is proposed to address this issue and an algorithm based on three spline interpolation principle is presented to estimate the horizontal displacement of high-rise buildings. In this method, the whole structure is divided into different elements by different measured points. The story drift angle curve of each element is modeled as a three spline curve. The horizontal displacement can be estimated after integration of the story drift angle curve. A numerical example is designed to verify the proposed method and the result shows this method can effectively estimate the horizontal displacement with high accuracy. After that, this method is applied to a practical slender structure - Shanghai Tower. Nature frequencies identification and deformation monitoring are conducted from the signal of inclinometers. It is concluded that inclinometer-based technology can not only be used for spectrum analysis and modal identification, but also for monitoring deformation of the whole structure. This inclinometer-based technology provides a novel method for future structural health monitoring.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.995-996
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• 2013

• Smart Structures and Systems
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• 제10권3호
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• pp.271-298
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• 2012

Researchers have made significant progress in recent years towards realizing effective structural health monitoring (SHM) utilizing wireless smart sensor networks (WSSNs). These efforts have focused on improving the performance and robustness of such networks to achieve high quality data acquisition and distributed, in-network processing. One of the primary challenges still facing the use of smart sensors for long-term monitoring deployments is their limited power resources. Periodically accessing the sensor nodes to change batteries is not feasible or economical in many deployment cases. While energy harvesting techniques show promise for prolonging unattended network life, low power design and operation are still critically important. This research presents the WiSeMote: a new, fully integrated ultra-low power wireless smart sensor node and a flexible base station, both designed for long-term SHM deployments. The power consumption of the sensor nodes and base station has been minimized through careful hardware selection and the implementation of power-aware network software, without sacrificing flexibility and functionality.

• Journal of Communications and Networks
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• 제11권4호
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• pp.350-358
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• 2009

In a wireless sensor network (WSN) setting, this paper presents a distributed decision-making framework and illustrates its application in an online structural health monitoring (SHM) system. The objective is to recover a damage severity vector, which identifies, localizes, and quantifies damages in a structure, via distributive and collaborative decision-making among wireless sensors. Observing the fact that damages are generally scarce in a structure, this paper develops a nonlinear 0-norm minimization formulation to recover the sparse damage severity vector, then relaxes it to a linear and distributively tractable one. An optimal algorithm based on the alternating direction method of multipliers (ADMM) and a heuristic distributed linear programming (DLP) algorithm are proposed to estimate the damage severity vector distributively. By limiting sensors to exchange information among neighboring sensors, the distributed decision-making algorithms reduce communication costs, thus alleviate the channel interference and prolong the network lifetime. Simulation results in monitoring a steel frame structure prove the effectiveness of the proposed algorithms.

• 비파괴검사학회지
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• 제30권3호
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• pp.244-256
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• 2010

Radio frequency identification(RFID) combined with wireless technology has good potential for structural health monitoring(SHM). We describe several advantages of RFID and wireless technologies for SHM, and review SHM examples with working principles, design and technical details for damage detection, heat exposure monitoring, force/strain sensing, and corrosion detection in concrete, steel, carbon fiber reinforced polymer(CFRP), and other materials. Various sensors combined with wireless communication are also discussed. These methodologies can be readily developed, implemented, and customized. There are some technical difficulties, but solutions are being addressed. Lastly, a surface acoustic wave-based RFID system is presented, and possible future trends of SHM based on RFID and wireless technology are presented.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 추계학술대회 논문집
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• pp.1545-1561
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• 2008

Among all transportations, railway transports have been promisingly offering excellent energy conservation and travelling time. Inevitably, they become a main role in not only transport goods but also passengers. With leap in development of technology, trains have tremendously enhanced their services in terms of speed, accessibility and comfort. However, the safety and ride quality have become a main issue as the train speed increased. The higher speeds have led the structural dynamics and health must be monitored from time to time to ensure that they are in good condition to provide reliable ride. Among all monitoring systems, the structural health monitoring (SHM) systems are imperative important due to its capability of in-situ monitoring and inherently reduce the maintenance frequencies and the huge associated cost. In this paper, SHM systems and the related non-destructive test and evaluation methods were discussed. The types of damages related to train vehicles as well as the damage hot spots are also included in this paper.

• Wind and Structures
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• 제12권6호
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• pp.479-504
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• 2009

Structural health monitoring (SHM) systems have been recently embraced in long span cable-supported bridges, in which buffeting-induced stress monitoring is one of the tasks to ensure the safety of the bridge under strong winds. In line with this task, this paper presents a SHM-oriented finite element model (FEM) for the Tsing Ma suspension bridge in Hong Kong so that stresses/strains in important bridge components can be directly computed and compared with measured ones. A numerical procedure for buffeting induced stress analysis of the bridge based on the established FEM is then presented. Significant improvements of the present procedure are that the effects of the spatial distribution of both buffeting forces and self-excited forces on the bridge deck structure are taken into account and the local structural behaviour linked to strain/stress, which is prone to cause local damage, are estimated directly. The field measurement data including wind, acceleration and stress recorded by the wind and structural health monitoring system (WASHMS) installed on the bridge during Typhoon York are analyzed and compared with the numerical results. The results show that the proposed procedure has advantages over the typical equivalent beam finite element models.

• 한국구조물진단유지관리공학회 논문집
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• 제14권1호
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• pp.165-174
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• 2010

본 논문에서는 실물 콘크리트 거더 교량의 가속도 응답 신호를 이용하여 구조물의 상태변화를 경보한 후 그 위치 변화를 검색하는 2단계 구조건전성 모니터링 체계를 제시하였다. 먼저, 2경간 연속 콘크리트 거더 교량인 미호천교를 대상교량으로 선정하였으며, 볼링공을 이용한 강제진동 실험으로부터 동특성을 추출하였다. 다음으로, 미호천교의 2단계 구조건전성 모니터링 체계 구축을 위한 손상 발생 경보 및 손상 위치 검색 기법들을 선정하였다. 손상 경보 기법으로는 시간영역 특징을 이용하는 자기회귀모델과 주파수응답함수의 상관계수, 주파수응답비보증지수를 선정하였다. 손상 위치 검색 기법으로는 모드변형에너지기반 손상지수법을 선정하였다. 마지막으로, 덤프트럭을 이용한 정적 재하 실험을 통해 2단계 손상 모니터링 체계의 적합성을 검증하였다.

• Smart Structures and Systems
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• 제6권5_6호
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• pp.731-748
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• 2010

Impact detection and health monitoring are very important tasks for civil infrastructures, such as bridges. Piezoceramic based transducers are widely researched for these tasks due to the piezoceramic material's inherent advantages of dual sensing and actuation ability, which enables the active sensing method for structural health monitoring with a network of piezoceramic transducers. Wireless sensor networks, which are easy for deployment, have great potential in health monitoring systems for large civil infrastructures to identify early-age damages. However, most commercial wireless sensor networks are general purpose and may not be optimized for a network of piezoceramic based transducers. Wireless networks of piezoceramic transducers for active sensing have special requirements, such as relatively high sampling rate (at a few-thousand Hz), incorporation of an amplifier for the piezoceramic element for actuation, and low energy consumption for actuation. In this paper, a wireless network is specially designed for piezoceramic transducers to implement impact detection and active sensing for structural health monitoring. A power efficient embedded system is designed to form the wireless sensor network that is capable of high sampling rate. A 32 bit RISC wireless microcontroller is chosen as the main processor. Detailed design of the hardware system and software system of the wireless sensor network is presented in this paper. To verify the functionality of the wireless sensor network, it is deployed on a two-story concrete frame with embedded piezoceramic transducers, and the active sensing property of piezoceramic material is used to detect the damage in the structure. Experimental results show that the wireless sensor network can effectively implement active sensing and impact detection with high sampling rate while maintaining low power consumption by performing offline data processing and minimizing wireless communication.

• Smart Structures and Systems
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• 제20권1호
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• pp.43-52
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• 2017

Structural health monitoring has drawn great attention in the field of civil engineering in past two decades. These structural health monitoring methods evaluate structural integrity through high-quality sensor measurements of structures. Due to electronic deterioration or aging problems, sensors may yield biased signals. Therefore, the objective of this study is to develop a fault detection method that identifies malfunctioning sensors in a sensor network. This method exploits the autoregressive modeling technique to generate a bank of Kalman estimators, and the faulty sensors are then recognized by comparing the measurements with these estimated signals. Three types of faults are considered in this study including the additive, multiplicative, and slowly drifting faults. To assess the effectiveness of detecting faulty sensors, a numerical example is provided, while an experimental investigation with faults added artificially is studied. As a result, the proposed method is capable of determining the faulty occurrences and types.