978 research outputs found

    Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

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    INE/AUTC 10.0

    STR-991: ENERGY HARVESTING METHODS FOR STRUCTURAL HEALTH MONITORING USING WIRELESS SENSORS: A REVIEW

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    Structural Health Monitoring (SHM) implies monitoring the performance of structures using sensors to get an advance warning of the loss of structural capacity or potential collapse. Wireless-sensor based monitoring system is found to be advantageous over traditional wire-based system because of their ease of implementation and maintenance. However, power supply is an important concern for wireless sensors used in monitoring of civil engineering structures. While there are different efficient power usage methods and power supply solutions available for wireless sensors, their applications to SHM systems for civil infrastructure are not standardized. Energy harvesting by means of converting energy from the surrounding environment provides a desirable solution to address the issue of finite power source for wireless sensors. There are several sources of renewable energy that can be harnessed to generate electrical energy for the sensors. This paper reviews some of these energy harvesting sources and provides their working concept, brief idea about related research and a current state-of-art of their applications for structural health monitoring of civil engineering structures. Solar and mechanical energy harvesters have the most implemented applications for monitoring structures currently

    Damage identification in bridge structures : review of available methods and case studies

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    Bridges are integral parts of the infrastructure and play a major role in civil engineering. Bridge health monitoring is necessary to extend the life of a bridge and retain safety. Periodic monitoring contributes significantly in keeping these structures operational and extends structural integrity. Different researchers have proposed different methods for identifying bridge damages based on different theories and laboratory tests. Several review papers have been published in the literature on the identification of damage and crack in bridge structures in the last few decades. In this paper, a review of literature on damage identification in bridge structures based on different methods and theories is carried out. The aim of this paper is to critically evaluate different methods that have been proposed to detect damages in different bridges. Different papers have been carefully reviewed, and the gaps, limitations, and superiority of the methods used are identified. Furthermore, in most of the reviews, future applications and several sustainable methods which are necessary for bridge monitoring are covered. This study significantly contributes to the literature by critically examining different methods, giving guidelines on the methods that identify the damages in bridge structures more accurately, and serving as a good reference for other researchers and future works

    Decentralized identification and multimetric monitoring of civil infrastructure using smart sensors

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    Wireless Smart Sensor Networks (WSSNs) facilitates a new paradigm to structural identification and monitoring for civil infrastructure. Conventionally, wired sensors and central data acquisition systems have been used to characterize the state of the structure, which is quite challenging due to difficulties in cabling, long setup time, and high equipment and maintenance costs. WSSNs offer a unique opportunity to overcome such difficulties. Recent advances in sensor technology have realized low-cost, smart sensors with on-board computation and wireless communication capabilities, making deployment of a dense array of sensors on large civil structures both feasible and economical. However, as opposed to wired sensor networks in which centralized data acquisition and processing are common practice, WSSNs require decentralized algorithms due to the limitation associated with wireless communication; to date such algorithms are limited. This research develops new decentralized algorithms for structural identification and monitoring of civil infrastructure. To increase performance, flexibility, and versatility of the WSSN, the following issues are considered specifically: (1) decentralized modal analysis, (2) efficient decentralized system identification in the WSSN, and (3) multimetric sensing. Numerical simulation and laboratory testing are conducted to verify the efficacy of the proposed approaches. The performance of the decentralized approaches and their software implementations are validated through full-scale applications at the Irwin Indoor Practice Field in the University of Illinois at Urbana-Champaign and the Jindo Bridge, a 484 meter-long cable-stayed bridge located in South Korea. This research provides a strong foundation on which to further develop long-term monitoring employing a dense array of smart sensors. The software developed in this research is opensource and is available at: http://shm.cs.uiuc.edu/.NSF Grant No. CMS-060043NSF Grant No. CMMI-0724172NSF Grant No. CMMI-0928886NSF Grant No. CNS-1035573Ope

    Advances in Smart Technologies for Structural Health Monitoring of Cable-stayed Bridges

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    This study deals with the general problem of developing smart technologies for vibration and impedance-based structural health monitoring (SHM) of cable-stayed bridges. The following approaches are implemented to achieve the objective. Firstly, vibration- and impedance-based SHM methods suitable for cable-stayed bridge are briefly outlined. Secondly, smart sensors are designed for vibration- and impedance-based SHM. Thirdly, the practicality of the smart sensor system is evaluated on a real cable-stayed bridge, Hwamyung Bridge in Korea. The system's performance is experimentally analyzed under various cable forces and weather conditions. Finally, the experimental modal parameters are identified by numerical modal analyses of the target bridge. Also, its structural parameters are estimated from the vibration-based structural identification using experimental modal parameters

    Vibration testing of a steel girder bridge using cabled and wireless sensors

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    Author's manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s11709-011-0113-y© Higher Education Press and Springer-Verlag Berlin Heidelberg 2011Being able to significantly reduce system installation time and cost, wireless sensing technology has attracted much interest in the structural health monitoring (SHM) community. This paper reports the field application of a wireless sensing system on a 4-span highway bridge located in Wayne, New Jersey in the US. Bridge vibration due to traffic and ambient excitation is measured. To enhance the signal-to-noise ratio, a low-noise high-gain signal conditioning module is developed for the wireless sensing system. Nineteen wireless and nineteen cabled accelerometers are first installed along the sidewalk of two neighboring bridge spans. The performance of the wireless sensing system is compared with the high-precision cabled sensing system. In the next series of testing, sixteen wireless accelerometers are installed under the deck of another bridge span, forming a 4 × 4 array. Operating deflection analysis is successfully conducted using the wireless measurement of traffic and ambient vibrations.National Science Foundatio

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    Structural health monitoring (SHM) is a technique to diagnose an accurate and reliable condition of civil infrastructure by collecting and analyzing responses from distributed sensors. In recent years, aging civil structures have been increasing and they require further developed SHM technology for development of sustainable society. Wireless smart sensor and network technology, which is one of the recently emerging SHM techniques, enables more effective and economic SHM system in comparison to the existing wired systems. Researchers continue on development of the capability and extension of wireless smart sensors, and implement performance validation in various in-laboratory and outdoor full-scale experiments. This paper presents a summary of recent (mostly after 2010) researches on smart sensors, focused on the newly developed hardware, software, and validation examples of the developed smart sensors.ope

    Optimal sensor placement in structural health monitoring (SHM) with a field application on a RC bridge

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    Structural health monitoring (SHM) is a research field that targets detecting and locating damage in structures. The main objective of SHM is to detect damage at its onset and inform authorities about the type, nature and location of the damage in the structure. Successful SHM requires deploying optimal sensor networks. We present a probabilistic approach to identify optimal location of sensors based on a priori knowledge on damage locations while considering the need for redundancy in sensor networks. The optimal number of sensors is identified using a multi-objective optimization approach incorporating information entropy and cost of the sensor network. As the size of the structure grows, the advantage of the optimal sensor network in damage detection becomes obvious. We also present an innovative field application of SHM using Field Programmable Gate Array (FPGA) and wireless communication technologies. The new SHM system was installed to monitor a reinforced concrete (RC) bridge on interstate I-40 in Tucumcari, New Mexico. The new monitoring system is powered with renewable solar energy. The integration of FPGA and photovoltaic technologies make it possible to remotely monitor infrastructure with limited access to power. Using calibrated finite element (FE) model of the bridge with real data collected from the sensors installed on the bridge, we establish fuzzy sets describing different damage states of the bridge. Unknown states of the bridge performance are then identified using degree of similarity between these fuzzy sets. The proposed SHM system will reduce human intervention significantly and can save millions of dollars currently spent on prescheduled inspection by enabling performance based monitoring
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