• Structural Monitoring and Maintenance
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• 제2권4호
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• pp.357-382
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• 2015

This paper provides an overview of the use of different Distributed Optical Fiber Sensor systems (DOFSs) to perform Structural Health Monitoring (SHM) in the specific case of civil engineering structures. Nowadays, there are several methods available for extracting distributed measurements from optical fiber, and their use have to be according with the aims of the SHM performance. The continuous-in-space data is the common advantage of the different DOFSs over other conventional health monitoring systems and, depending on the particular characteristics of each DOFS, a global and/or local health structural evaluation is possible with different accuracy. Firstly, the fundamentals of different DOFSs and their principal advantages and disadvantages are presented. Then, laboratory and field tests using different DOFSs systems to measure strain in structural elements and civil structures are presented and discussed. Finally, based on the current applications, conclusions and future trends of DOFSs in SHM in civil structures are proposed.

• 한국정밀공학회지
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• 제27권6호
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• pp.64-74
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• 2010

This paper proposes a new TR-based baseline-free SHM technique in which the time-reversal (TR) property of the guided Lamb waves is utilized. The new TR-based SHM technique has two distinct features when compared with the other TR-based SHM techniques: (1) The backward TR process commonly conducted by the measurement is replaced by the computation-based process; (2) In place of the comparison method, the TOF information of the damage signal extracted from the reconstructed signal is used for the damage diagnosis in conjunction with the imaging method which enables us to represent the damage as an image. The proposed TR-based SHM technique is then validated through the damage diagnosis experiment for an aluminum plate with a damage at different locations.

• 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.

• 한국구조물진단유지관리공학회지
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• 제18권1호
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• pp.69-73
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• 2014

• 전산구조공학
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• 제35권2호
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• pp.26-33
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• 2022

• 대한기계학회논문집A
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• 제39권1호
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• pp.37-43
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• 2015

압전소자(Piezoelectric transducer, PZT)는 구조물의 안정성 평가를 목적으로 하는 구조 건전성 모니터링 기법(Structural Health Monitoring, SHM)의 센서(sensor) 및 구동기(actuator)로 많이 활용되고 있다. 사용되는 센서 및 구동기의 성능을 사전에 파악하고, 잔존수명 및 결함을 탐지하는 센서 자가 진단법은 안정적인 SHM의 결과를 얻기 위해 매우 중요한 절차이다. 본 연구에서는 Admittance 값을 기반으로 한 센서 자가 진단절차를 통하여 압전체 센서의 결함을 탐지하였으며, 센서 진단과정에 영향을 줄 수 있는 접합층 및 온도 등의 영향인자에 대해 실험적 분석을 실시하였다. 분석 결과 Admittance와 온도 및 접착제의 상관관계를 파악할 수 있었으며, admittance를 기반으로 한 센서 자가 진단 절차를 통해 센서의 접착상태와 접착제의 성능평가가 가능함을 검증하였다.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.411-426
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• 2012

The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of over 700 sensors of sixteen types. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), an SHM benchmark problem for high-rise structures has been developed by taking the instrumented Canton Tower as a host structure. This benchmark problem aims to provide an international platform for direct comparison of various SHM-related methodologies and algorithms with the use of real-world monitoring data from a large-scale structure, and to narrow the gap that currently exists between the research and the practice of SHM. This paper first briefs the SHM system deployed on the Canton Tower, and the development of an elaborate three-dimensional (3D) full-scale finite element model (FEM) and the validation of the model using the measured modal data of the structure. In succession comes the formulation of an equivalent reduced-order FEM which is developed specifically for the benchmark study. The reduced-order FEM, which comprises 37 beam elements and a total of 185 degrees-of-freedom (DOFs), has been elaborately tuned to coincide well with the full-scale FEM in terms of both modal frequencies and mode shapes. The field measurement data (including those obtained from 20 accelerometers, one anemometer and one temperature sensor) from the Canton Tower, which are available for the benchmark study, are subsequently presented together with a description of the sensor deployment locations and the sensor specifications.

• Smart Structures and Systems
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• 제9권2호
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• pp.145-164
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• 2012

In this paper, solar-powered, multi-scale, vibration-impedance sensor node on Imote2 platform is presented for hybrid structural health monitoring (SHM) in cable-stayed bridge. In order to achieve the objective, the following approaches are proposed. Firstly, vibration- and impedance-based hybrid SHM methods are briefly described. Secondly, the multi-scale vibration and impedance sensor node on Imote2-platform is presented on the design of hardware components and embedded software for vibration- and impedance-based SHM. In this approach, a solar-powered energy harvesting is implemented for autonomous operation of the smart sensor nodes. Finally, the feasibility and practicality of the smart sensor-based SHM system is evaluated on a full-scale cable-stayed bridge, Hwamyung Bridge in Korea. Successful level of wireless communication and solar-power supply for smart sensor nodes are verified. Also, vibration and impedance responses measured from the target bridge which experiences various weather conditions are examined for the robust long-term monitoring capability of the smart sensor system.

• 한국정보통신학회논문지
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• 제12권2호
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• pp.391-400
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• 2008

최근 센서 네트워크의 발전으로 구조물 안전 시스템에 관한 관심이 증대되고 있다. 구조물 안전 감시 시스템이란 교량이나 도로 등의 구조물이 받는 진동, 외부의 충격, 하중 등의 환경 정보를 감지하는 시스템이다. 구조물 안전 감시 시스템은 이벤트를 감지 및 처리하고, 구조물의 안전 상태를 예상하는 것을 목적으로 하여 운영된다. 현재 구조물 안전 감시 시스템은 아날로그 센서를 이용하여 데이터를 수집하고, 유선망을 사용하여 분석 프로그램으로 전송하고 있다. 이러한 유선 시스템은 높은 정확성을 가지지만, 무선 시스템에 비해 초기 설치비용이 비싸고 연결이 복잡하며 연결선이 유실되는 등의 문제가 있다. 또한 센서 노드의 추가, 삭제가 어렵다. 이러한 유선 구조물 안전 감시 시스템의 문제점을 해결하기 위해 무선 센서 네트워크 기술을 적용한 구조물 안전 관리 시스템을 설계 및 구현하였다.

• Smart Structures and Systems
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• 제29권1호
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.