• 제목/요약/키워드: smart composite

검색결과 461건 처리시간 0.025초

Development and testing of a composite system for bridge health monitoring utilising computer vision and deep learning

  • Lydon, Darragh;Taylor, S.E.;Lydon, Myra;Martinez del Rincon, Jesus;Hester, David
    • Smart Structures and Systems
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    • 제24권6호
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    • pp.723-732
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    • 2019
  • Globally road transport networks are subjected to continuous levels of stress from increasing loading and environmental effects. As the most popular mean of transport in the UK the condition of this civil infrastructure is a key indicator of economic growth and productivity. Structural Health Monitoring (SHM) systems can provide a valuable insight to the true condition of our aging infrastructure. In particular, monitoring of the displacement of a bridge structure under live loading can provide an accurate descriptor of bridge condition. In the past B-WIM systems have been used to collect traffic data and hence provide an indicator of bridge condition, however the use of such systems can be restricted by bridge type, assess issues and cost limitations. This research provides a non-contact low cost AI based solution for vehicle classification and associated bridge displacement using computer vision methods. Convolutional neural networks (CNNs) have been adapted to develop the QUBYOLO vehicle classification method from recorded traffic images. This vehicle classification was then accurately related to the corresponding bridge response obtained under live loading using non-contact methods. The successful identification of multiple vehicle types during field testing has shown that QUBYOLO is suitable for the fine-grained vehicle classification required to identify applied load to a bridge structure. The process of displacement analysis and vehicle classification for the purposes of load identification which was used in this research adds to the body of knowledge on the monitoring of existing bridge structures, particularly long span bridges, and establishes the significant potential of computer vision and Deep Learning to provide dependable results on the real response of our infrastructure to existing and potential increased loading.

Structural health rating (SHR)-oriented 3D multi-scale finite element modeling and analysis of Stonecutters Bridge

  • Li, X.F.;Ni, Y.Q.;Wong, K.Y.;Chan, K.W.Y.
    • Smart Structures and Systems
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    • 제15권1호
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    • pp.99-117
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    • 2015
  • The Stonecutters Bridge (SCB) in Hong Kong is the third-longest cable-stayed bridge in the world with a main span stretching 1,018 m between two 298 m high single-leg tapering composite towers. A Wind and Structural Health Monitoring System (WASHMS) is being implemented on SCB by the Highways Department of The Hong Kong SAR Government, and the SCB-WASHMS is composed of more than 1,300 sensors in 15 types. In order to establish a linkage between structural health monitoring and maintenance management, a Structural Health Rating System (SHRS) with relevant rating tools and indices is devised. On the basis of a 3D space frame finite element model (FEM) of SCB and model updating, this paper presents the development of an SHR-oriented 3D multi-scale FEM for the purpose of load-resistance analysis and damage evaluation in structural element level, including modeling, refinement and validation of the multi-scale FEM. The refined 3D structural segments at deck and towers are established in critical segment positions corresponding to maximum cable forces. The components in the critical segment region are modeled as a full 3D FEM and fitted into the 3D space frame FEM. The boundary conditions between beam and shell elements are performed conforming to equivalent stiffness, effective mass and compatibility of deformation. The 3D multi-scale FEM is verified by the in-situ measured dynamic characteristics and static response. A good agreement between the FEM and measurement results indicates that the 3D multi-scale FEM is precise and efficient for WASHMS and SHRS of SCB. In addition, stress distribution and concentration of the critical segments in the 3D multi-scale FEM under temperature loads, static wind loads and equivalent seismic loads are investigated. Stress concentration elements under equivalent seismic loads exist in the anchor zone in steel/concrete beam and the anchor plate edge in steel anchor box of the towers.

Design, calibration and application of wireless sensors for structural global and local monitoring of civil infrastructures

  • Yu, Yan;Ou, Jinping;Li, Hui
    • Smart Structures and Systems
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    • 제6권5_6호
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    • pp.641-659
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    • 2010
  • Structural Health Monitoring (SHM) gradually becomes a technique for ensuring the health and safety of civil infrastructures and is also an important approach for the research of the damage accumulation and disaster evolving characteristics of civil infrastructures. It is attracting prodigious research interests and the active development interests of scientists and engineers because a great number of civil infrastructures are planned and built every year in mainland China. In a SHM system the sheer number of accompanying wires, fiber optic cables, and other physical transmission medium is usually prohibitive, particularly for such structures as offshore platforms and long-span structures. Fortunately, with recent advances in technologies in sensing, wireless communication, and micro electro mechanical systems (MEMS), wireless sensor technique has been developing rapidly and is being used gradually in the SHM of civil engineering structures. In this paper, some recent advances in the research, development, and implementation of wireless sensors for the SHM of civil infrastructures in mainland China, especially in Dalian University of Technology (DUT) and Harbin Institute of Technology (HIT), are introduced. Firstly, a kind of wireless digital acceleration sensors for structural global monitoring is designed and validated in an offshore structure model. Secondly, wireless inclination sensor systems based on Frequency-hopping techniques are developed and applied successfully to swing monitoring of large-scale hook structures. Thirdly, wireless acquisition systems integrating with different sensing materials, such as Polyvinylidene Fluoride(PVDF), strain gauge, piezoresistive stress/strain sensors fabricated by using the nickel powder-filled cement-based composite, are proposed for structural local monitoring, and validating the characteristics of the above materials. Finally, solutions to the key problem of finite energy for wireless sensors networks are discussed, with future works also being introduced, for example, the wireless sensor networks powered by corrosion signal for corrosion monitoring and rapid diagnosis for large structures.

신축성 접착 필름 위에 놓인 그래핀 종이의 주름 생성 (Wrinkling of Graphene Papers Placed on Stretchable Adhesive Films)

  • 김상윤;정명희;석지원
    • Composites Research
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    • 제34권2호
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    • pp.108-114
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    • 2021
  • 일반적으로 그래핀 플레이크는 산화그래핀을 화학적 또는 열적 환원 공정을 통해 환원그래핀으로 변환하여 대량 생산하고 있다. 그래핀 플레이크는 다양한 형태로 응용되는데, 그 중 진공여과를 이용한 적층 공정을 통해 종이형 필름으로 제작이 가능하다. 그래핀 종이는 신축성이 부족한 단점이 있어 신축성 소자 응용에 제약이 있다. 본 연구에서는 신축성이 있는 그래핀 종이를 제작하기 위하여, 그래핀 종이에 주름을 만들었다. 신축성이 뛰어난 접착 필름을 미리 늘린 후, 그 위에 그래핀 종이를 붙이고, 접착 필름을 원래 상태로 놓아 주어 그래핀 종이에 주름을 만들었다. 이 때, 접착 필름에 가하는 당김 정도 및 젖은 상태에 따라 주름의 형상이 변하는 것을 실험적으로 관찰하였다. 특히, 그래핀 종이와 접착 필름의 전단 탄성 계수 차에 의하여 주름의 주기가 바뀌는 현상을 관찰하였다.

Analytical and experimental investigation of stepped piezoelectric energy harvester

  • Deepesh, Upadrashta;Li, Xiangyang;Yang, Yaowen
    • Smart Structures and Systems
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    • 제26권6호
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    • pp.681-692
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    • 2020
  • Conventional Piezoelectric Energy Harvesters (CPEH) have been extensively studied for maximizing their electrical output through material selection, geometric and structural optimization, and adoption of efficient interface circuits. In this paper, the performance of Stepped Piezoelectric Energy Harvester (SPEH) under harmonic base excitation is studied analytically, numerically and experimentally. The motivation is to compare the energy harvesting performance of CPEH and SPEHs with the same characteristics (resonant frequency). The results of this study challenge the notion of achieving higher voltage and power output through incorporation of geometric discontinuities such as step sections in the harvester beams. A CPEH consists of substrate material with a patch of piezoelectric material bonded over it and a tip mass at the free end to tune the resonant frequency. A SPEH is designed by introducing a step section near the root of substrate beam to induce higher dynamic strain for maximizing the electrical output. The incorporation of step section reduces the stiffness and consequently, a lower tip mass is used with SPEH to match the resonant frequency to that of CPEH. Moreover, the electromechanical coupling coefficient, forcing function and damping are significantly influenced because of the inclusion of step section, which consequently affects harvester's output. Three different configurations of SPEHs characterized by the same resonant frequency as that of CPEH are designed and analyzed using linear electromechanical model and their performances are compared. The variation of strain on the harvester beams is obtained using finite element analysis. The prototypes of CPEH and SPEHs are fabricated and experimentally tested. It is shown that the power output from SPEHs is lower than the CPEH. When the prototypes with resonant frequencies in the range of 56-56.5 Hz are tested at 1 m/s2, three SPEHs generate power output of 482 μW, 424 μW and 228 μW when compared with 674 μW from CPEH. It is concluded that the advantage of increasing dynamic strain using step section is negated by increase in damping and decrease in forcing function. However, SPEHs show slightly better performance in terms of specific power and thus making them suitable for practical scenarios where the ratio of power to system mass is critical.

자원 공유기법을 이용한 AES-ARIA 연산기의 효율적인 설계 (Design of an Efficient AES-ARIA Processor using Resource Sharing Technique)

  • 구본석;유권호;장태주;이상진
    • 정보보호학회논문지
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    • 제18권6A호
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    • pp.39-49
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    • 2008
  • AES와 ARIA 블록암호 알고리즘은 각각 미국과 한국의 차세대 표준 블록암호 알고리즘으로 각광받고 있으며, 스마트 카드, 전자여권 등 기밀성이 요구되는 다양한 정보보호 분야에서 활용되고 있다. 본 논문에서는 최초로 AES와 ARIA의 효율적인 통합 하드웨어 연산기를 제안하고 0.25um CMOS 공정으로 구현한 결과를 제시한다. AES와 ARIA에 적용할 수 있는 확장 유한체 방식의 공통 S-box를 설계하고, 두 알고리즘의 확산 함수에서 공통항을 축출하여, 19,056 게이트 카운트의 소형 크기를 가지는 연산기를 설계하였다. 본 논문에서 제안하는 연산기는 AES와 ARIA의 개별 소형 연산기를 설계하는 방식에 비해 32% 감소된 크기를 가진다. 또한 제안하는 연산기는 128비트 한 블록에 대한 AES 암호화에는 11 클록 사이클, ARIA 암호화에는 16 클록 사이클을 사용하며, 이는 각각 1,047Mbps와 720Mbps의 성능을 나타난다.

나노 첨가제에 따른 Sn-Ag-Cu계 솔더페이스트의 젖음성 및 금속간화합물 (Wettability and Intermetallic Compounds of Sn-Ag-Cu-based Solder Pastes with Addition of Nano-additives)

  • 서성민;스리 하리니 라젠드란;정재필
    • 마이크로전자및패키징학회지
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    • 제29권1호
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    • pp.35-41
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    • 2022
  • 5G 시대를 맞아, 인공지능, 클라우드 컴퓨팅, 자율주행 차량, 스마트 제조 등의 기술 소요가 증가하고 있다. 전자기기의 고효율을 위해 고집적회로 및 패키징 연구는 중요하다. 전해도금된 솔더는 범프 조성의 균일성에 한계가 있다. 작은 크기의 솔더 파우더로 구성된 솔더 페이스트는 고집적 패키징에 일반적으로 사용되는 솔더 중 하나이다. 솔더 페이스트에 나노 입자를 첨가하거나 기판 표면 마감 처리를 하여 젖음성을 향상시키고, 금속 패드 계면에서 금속간화합물의 성장을 억제하는 연구가 진행중이다. 본 논문은 나노 입자 첨가를 통한 솔더 페이스트의 젖음성 향상과 계면 금속간화합물의 성장을 억제하는 원리에 대하여 설명한다.

그래핀/탄소나노섬유 코팅된 3D 프린팅 고분자 구조를 이용한 신축성 스트레인 센서 (Stretchable Strain Sensors Using 3D Printed Polymer Structures Coated with Graphene/Carbon Nanofiber Hybrids)

  • 나승찬;이현종;임태경;윤정민;석지원
    • Composites Research
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    • 제35권4호
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    • pp.283-287
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    • 2022
  • 신축성 스트레인 센서는 웨어러블 기기나 건강 모니터링과 같은 미래 응용 분야에 적용하기 위하여 개발되고 있는데, 센서의 신뢰성을 높이기 위해 안정성과 반복성이 고려되어야 한다. 본 연구에서는 3D 프린팅을 통해 키리가미 패턴이 있는 고분자 구조를 제작하여 센서의 신축성과 히스테리시스를 개선하였다. 견고한 전도성 네트워크를 구현하기 위하여 그래핀과 탄소나노섬유를 혼합한 하이브리드 소재를 고분자 구조에 코팅하였다. 제작한 신축성 스트레인 센서는 32%의 스트레인에 대해 게이지팩터가 36을 보였으며, 1%부터 30%까지의 다양한 스트레인에 대해서 안정적인 저항 변화 응답을 나타냈다.

A machine learning-based model for the estimation of the critical thermo-electrical responses of the sandwich structure with magneto-electro-elastic face sheet

  • Zhou, Xiao;Wang, Pinyi;Al-Dhaifallah, Mujahed;Rawa, Muhyaddin;Khadimallah, Mohamed Amine
    • Advances in nano research
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    • 제12권1호
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    • pp.81-99
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    • 2022
  • The aim of current work is to evaluate thermo-electrical characteristics of graphene nanoplatelets Reinforced Composite (GNPRC) coupled with magneto-electro-elastic (MEE) face sheet. In this regard, a cylindrical smart nanocomposite made of GNPRC with an external MEE layer is considered. The bonding between the layers are assumed to be perfect. Because of the layer nature of the structure, the material characteristics of the whole structure is regarded as graded. Both mechanical and thermal boundary conditions are applied to this structure. The main objective of this work is to determine critical temperature and critical voltage as a function of thermal condition, support type, GNP weight fraction, and MEE thickness. The governing equation of the multilayer nanocomposites cylindrical shell is derived. The generalized differential quadrature method (GDQM) is employed to numerically solve the differential equations. This method is integrated with Deep Learning Network (DNN) with ADADELTA optimizer to determine the critical conditions of the current sandwich structure. This the first time that effects of several conditions including surrounding temperature, MEE layer thickness, and pattern of the layers of the GNPRC is investigated on two main parameters critical temperature and critical voltage of the nanostructure. Furthermore, Maxwell equation is derived for modeling of the MEE. The outcome reveals that MEE layer, temperature change, GNP weight function, and GNP distribution patterns GNP weight function have significant influence on the critical temperature and voltage of cylindrical shell made from GNP nanocomposites core with MEE face sheet on outer of the shell.

Optimised neural network prediction of interface bond strength for GFRP tendon reinforced cemented soil

  • Zhang, Genbao;Chen, Changfu;Zhang, Yuhao;Zhao, Hongchao;Wang, Yufei;Wang, Xiangyu
    • Geomechanics and Engineering
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    • 제28권6호
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    • pp.599-611
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    • 2022
  • Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.