• Title/Summary/Keyword: Structural Health Monitoring System

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Performance Analysis of Bridge using Structural Health Monitoring: Seong-Su Bridge Case-study

  • Kaloop, Mosbeh R.;Ban, Woo Hyun;Hu, Jong Wan
    • Journal of Urban Science
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    • v.8 no.1
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    • pp.1-6
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    • 2019
  • The performance evaluation of existing structures is important to study the safety of those structures with changing the loads over the lifetime of structures. Therefore, this study aims at evaluating the Seong-Su bridge, Seoul, Korea, using structural health monitoring (SHM) system. The static and dynamic tests are used to assess the behavior of the bridge. The statistical and wavelet analyses are used to demonstrate the behavior of the bridge in the time and frequency domains. The previous SHM results are used to assess the bridge performance. The results of this study show that the bridge performance under static and dynamic loads is safe in time and frequency domains.

Sensor enriched infrastructure system

  • Wang, Ming L.;Yim, Jinsuk
    • Smart Structures and Systems
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    • v.6 no.3
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    • pp.309-333
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    • 2010
  • Civil infrastructure, in both its construction and maintenance, represents the largest societal investment in this country, outside of the health care industry. Despite being the lifeline of US commerce, civil infrastructure has scarcely benefited from the latest sensor technological advances. Our future should focus on harnessing these technologies to enhance the robustness, longevity and economic viability of this vast, societal investment, in light of inherent uncertainties and their exposure to service and even extreme loadings. One of the principal means of insuring the robustness and longevity of infrastructure is to strategically deploy smart sensors in them. Therefore, the objective is to develop novel, durable, smart sensors that are especially applicable to major infrastructure and the facilities to validate their reliability and long-term functionality. In some cases, this implies the development of new sensing elements themselves, while in other cases involves innovative packaging and use of existing sensor technologies. In either case, a parallel focus will be the integration and networking of these smart sensing elements for reliable data acquisition, transmission, and fusion, within a decision-making framework targeting efficient management and maintenance of infrastructure systems. In this paper, prudent and viable sensor and health monitoring technologies have been developed and used in several large structural systems. Discussion will also include several practical bridge health monitoring applications including their design, construction, and operation of the systems.

Analysis and probabilistic modeling of wind characteristics of an arch bridge using structural health monitoring data during typhoons

  • Ye, X.W.;Xi, P.S.;Su, Y.H.;Chen, B.
    • Structural Engineering and Mechanics
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    • v.63 no.6
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    • pp.809-824
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    • 2017
  • The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

An Energy-Dissipation-Ratio Based Structural Health Monitoring System (에너지소산률을 이용한 구조물의 건전도 모니터링에 관한 연구)

  • Heo, Gwang-Hee;Shin, Heung-Chul;Shin, Jae-Chul
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.8 no.1
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    • pp.165-174
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    • 2004
  • This research develops a technique which uses energy dissipation ratio in order to monitor the structural health on real time basis. For real-time monitoring, we employ the NExT and the ERA which enable us to obtain real-time data. Energy dissipation ratio is calculated from those data only with the damping and natural frequency of the structure, and from the calculated values we develop an algorithm (Energy dissipation method) which decides the damage degree of structure. The Energy dissipation method developed in this research is proved to be valid by comparison with other methods like the eigenparameter method and the MAC. Especially this method enables us to save measuring time and data which are the most important in real-time monitoring, and its use of the ambient vibration also makes it easy to monitor the whole structure and its damage points.

Network vision of disaster prevention management for seashore reclaimed u-City (해안매립 신도시의 재해 예방관리 네트워크 비젼)

  • Ahn, Sang-Ro
    • Proceedings of the Korean Geotechical Society Conference
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    • 2009.09a
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    • pp.117-129
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    • 2009
  • This paper studied the safety management network system of infrastructure which constructed smart sensors, closed-circuit television(CCTV) and monitoring system. This safety management of infrastructure applied to bridge, cut slop and tunnel, embankment etc. The system applied to technologies of standardization guidelines, data acquirement technologies, data analysis and judgment technologies, system integration setup technology, and IT technologies. It was constructed safety management network system of various infrastructure to improve efficient management and operation for many infrastructure. Integrated safety management network system of infrastructure consisted of the real-time structural health monitoring system of each infrastructure, integrated control center, measured data transmission using i of tet web-based, collecting data using sf ver, early alarm system which the dangerous event of infrastructure occurred. Integrated control center consisted of conference room, control room to manage and analysis the data, server room to present the measured data and to collect the raw data. Early alarm system proposed realization of warning and response within 5 minute or less through development of sensor-based progress report and propagation automation system using the media such as MMS, VMS, EMS, FMS, SMS and web services of report and propagation. Based on this, the most effective u-Infrastructure Safety Management System is expected to be stably established at a less cost, thus making people's life more comfortable. Information obtained from such systems could be useful for maintenance or structural safety evaluation of existing structures, rapid evaluation of conditions of damaged structures after an earthquake, estimation of residual life of structures, repair and retrofitting of structures, maintenance, management or rehabilitation of historical structures.

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Stress variation analysis based on temperature measurements at Zhuhai Opera House

  • Lu, Wei;Teng, Jun;Qiu, Lihang;Huang, Kai
    • Structural Monitoring and Maintenance
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    • v.5 no.1
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    • pp.1-13
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    • 2018
  • The Zhuhai Opera House has an external structure consisting of a type of spatial steel, where the stress of steel elements varies with the ambient temperature. A structural health monitoring system was implemented at Zhuhai Opera House, and the temperatures and stresses of the structures were monitored in real time. The relationship between the stress distribution and temperature variations was analysed by measuring the temperature and stresses of the steel elements. In addition to measurements of the structure stresses and temperatures, further simulation analysis was carried out to provide the detailed relationship between the stress distributions and temperature variations. The limited temperature measurements were used to simulate the structure temperature distribution, and the stress distributions of all steel elements of the structure were analysed by building a finite element model of the Zhuhai Opera House spatial steel structure. This study aims to reveal the stress distributions of steel elements in a real-world project based on temperature variations, and to supply a basic database for the optimal construction time of a spatial steel structure. This will not only provide convenient, rapid and safe early warnings and decision-making for the spatial steel structure construction and operation processes, but also improve the structural safety and construction accuracy of steel space structures.

Simulation combined transfer learning model for missing data recovery of nonstationary wind speed

  • Qiushuang Lin;Xuming Bao;Ying Lei;Chunxiang Li
    • Wind and Structures
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    • v.37 no.5
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    • pp.383-397
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    • 2023
  • In the Structural Health Monitoring (SHM) system of civil engineering, data missing inevitably occurs during the data acquisition and transmission process, which brings great difficulties to data analysis and poses challenges to structural health monitoring. In this paper, Convolution Neural Network (CNN) is used to recover the nonstationary wind speed data missing randomly at sampling points. Given the technical constraints and financial implications, field monitoring data samples are often insufficient to train a deep learning model for the task at hand. Thus, simulation combined transfer learning strategy is proposed to address issues of overfitting and instability of the deep learning model caused by the paucity of training samples. According to a portion of target data samples, a substantial quantity of simulated data consistent with the characteristics of target data can be obtained by nonstationary wind-field simulation and are subsequently deployed for training an auxiliary CNN model. Afterwards, parameters of the pretrained auxiliary model are transferred to the target model as initial parameters, greatly enhancing training efficiency for the target task. Simulation synergy strategy effectively promotes the accuracy and stability of the target model to a great extent. Finally, the structural dynamic response analysis verifies the efficiency of the simulation synergy strategy.

System identification of steel framed structures with semi-rigid connections

  • Katkhuda, Hasan N.;Dwairi, Hazim M.;Shatarat, Nasim
    • Structural Engineering and Mechanics
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    • v.34 no.3
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    • pp.351-366
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    • 2010
  • A novel system identification and structural health assessment procedure of steel framed structures with semi-rigid connections is presented in this paper. It is capable of detecting damages at the local element level under normal operating conditions; i.e., serviceability limit state. The procedure is a linear time-domain system identification technique in which the structure responses are required, whereas the dynamic excitation force is not required to identify the structural parameters. The procedure tracks changes in the stiffness properties of all the elements in a structure. It can identify damage-free and damaged structural elements very accurately when excited by different types of dynamic loadings. The method is elaborated with the help of several numerical examples. The results indicate that the proposed algorithm identified the structures correctly and detected the pre-imposed damages in the frames when excited by earthquake, impact, and harmonic loadings. The algorithm can potentially be used for structural health assessment and monitoring of existing structures with minimum disruption of operations. Since the procedure requires only a few time points of response information, it is expected to be economic and efficient.

Magnetic Resonance-Based Wireless Power Transmission through Concrete Structures

  • Kim, Ji-Min;Han, Minseok;Sohn, Hoon
    • Journal of electromagnetic engineering and science
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    • v.15 no.2
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    • pp.104-110
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    • 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.

Application of Strcutral Health Monitoring in Structual Engineering for Buildings

  • Ji Young, Kim;Hobeom, Song;Kanghyun, Park;Kwangryang, Chung
    • International Journal of High-Rise Buildings
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    • v.11 no.3
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    • pp.221-226
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    • 2022
  • Installation of Structural Health Monitoring (SHM) system is a legal obligation for high-rise buildings over 200 m or 50-floor high in South Korea. CNP Dongyang has developed key technologies for SHM system design, installation, and data analyzing. Also, CNP Dongyang has applied SHM technology to a plenty of South Korea's representative high-rise buildings. The SHM technology, also, could be used in safety management of construction phase, evaluation of structural performance, etc. In this paper, state of the art SHM technologies and their application examples are introduced to give insight for future research and practical use of SHM.