• Smart Structures and Systems
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• v.5 no.1
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• pp.43-54
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• 2009

This study introduces a novel approach for locating damage in a structure using wireless sensor system with local level computational capability to alleviate data traffic load on the centralized computation. Smart wireless sensor systems, capable of iterative damage-searching, mimic an optimization process in a decentralized way. The proposed algorithm tries to detect damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides a reasonably effective sensor placement within a structure. Sensor clustering also assigns a certain number of master sensors in each cluster so that they can constantly monitor the structural health of a structure. By adopting a voting system, a group of wireless sensors iteratively forages for a damage location as they can be activated as needed. Since all of the damage searching process occurs within a small group of wireless sensors, no global control or data traffic to a central system is required. Numerical simulation demonstrates that the newly developed searching algorithm implemented on wireless sensors successfully localizes stiffness damage in a plate through the local level reconfigurable function of smart sensors.

• Smart Structures and Systems
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• v.16 no.6
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• pp.1147-1167
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• 2015

Wireless smart sensors, which have become popular for monitoring applications, are an attractive option for implementing structural control systems, due to their onboard sensing, processing, and communication capabilities. However, wireless smart sensors pose inherent challenges for control, including delays from communication, acquisition hardware, and processing time. Previous research in wireless control, which focused on semi-active systems, has found that sampling rate along with time delays can significantly impact control performance. However, because semi-active systems are guaranteed stable, these issues are typically neglected in the control design. This work achieves active control with smart sensors in an experimental setting. Because active systems are not inherently stable, all the elements of the control loop must be addressed, including data acquisition hardware, processing performance, and control design at slow sampling rates. The sensing hardware is shown to have a significant impact on the control design and performance. Ultimately, the smart sensor active control system achieves comparable performance to the traditional tethered system.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.505-524
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• 2010

Wireless structural monitoring systems consist of networks of wireless sensors installed to record the loading environment and corresponding response of large-scale civil structures. Wireless monitoring systems are desirable because they eliminate the need for costly and labor intensive installation of coaxial wiring in a structure. However, another advantageous characteristic of wireless sensors is their installation modularity. For example, wireless sensors can be easily and rapidly removed and reinstalled in new locations on a structure if the need arises. In this study, the reconfiguration of a rapid-to-deploy wireless structural monitoring system is proposed for monitoring short- and medium-span highway bridges. Narada wireless sensor nodes using power amplified radios are adopted to achieve long communication ranges. A network of twenty Narada wireless sensors is installed on the Yeondae Bridge (Korea) to measure the global response of the bridge to controlled truck loadings. To attain acceleration measurements in a large number of locations on the bridge, the wireless monitoring system is installed three times, with each installation concentrating sensors in one localized area of the bridge. Analysis of measurement data after installation of the three monitoring system configurations leads to reliable estimation of the bridge modal properties, including mode shapes.

• Structural Monitoring and Maintenance
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• v.3 no.1
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• pp.91-114
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• 2016

In this paper, recent research trends and activities on structural health monitoring (SHM) of civil infrastructure in Korea are reviewed. Recently, there has been increasing need for adopting smart sensing technologies to SHM, so this review focuses on smart sensing, monitoring, and assessment for civil infrastructure. Firstly, the research activities on smart sensor technology is reviewed including optical fiber sensors, piezoelectric sensors, wireless smart sensors, and vision-based sensing system. Then, a brief overview is given to the recent advances in smart monitoring and assessment techniques such as vibration-based global monitoring techniques, local monitoring with piezoelectric materials, decentralized monitoring techniques for wireless sensors, wireless power supply and energy harvest. Finally, recent joint SHM activities on several test beds in Korea are discussed to share the up-to-date information and to promote the smart sensors and monitoring technologies for applications to civil infrastructure. It includes a Korea-US joint research on test bridges of the Korea Expressway Corporation (KEC), a Korea-US-Japan joint research on Jindo cable-stayed bridge, and a comparative study for cable tension measurement techniques on Hwamyung cable-stayed bridge, and a campaign test for displacement measurement techniques on Sorok suspension bridge.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.32-38
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• 2020

The deployment of geographically distributed wireless sensors has greatly elevated the capability of monitoring structural health in social-overhead capital (SOC) public infrastructures. This paper deals with the utilization of a distributed mobility management (DMM) approach for the deployment of wireless sensing devices in a structural health monitoring system (SHM). Then, a wireless sensing mechanism utilizing low-energy adaptive clustering hierarchy (LEACH)-based clustering algorithm for smart sensors has been analyzed to support the seamless data transmission of structural health information which is essentially important to guarantee public safety. The clustering of smart sensors will be able to provide real-time monitoring of structural health and a filtering algorithm to boost the transmission of critical information over heterogeneous wireless and mobile networks.

• Smart Structures and Systems
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• v.10 no.3
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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.

• Smart Structures and Systems
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• v.12 no.1
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• pp.23-39
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• 2013

In this article, a smart multifunctional optical system-on-a-chip (SOC) sensor platform is presented and its application for fiber Bragg grating (FBG) sensor interrogation in optical sensor networks is investigated. The smart SOC sensor platform consists of a superluminescent diode as a broadband source, a tunable microelectromechanical system (MEMS) based Fabry-P$\acute{e}$rot filter, photodetectors, and an integrated microcontroller for data acquisition, processing, and communication. Integrated with a wireless sensor network (WSN) module in a compact package, a smart optical sensor node is developed. The smart multifunctional sensor platform has the capability of interrogating different types of optical fiber sensors, including Fabry-P$\acute{e}$rot sensors and Bragg grating sensors. As a case study, the smart optical sensor platform is demonstrated to interrogate multiplexed FBG strain sensors. A time domain signal processing method is used to obtain the Bragg wavelength shift of two FBG strain sensors through sweeping the MEMS tunable Fabry-P$\acute{e}$rot filter. A tuning range of 46 nm and a tuning speed of 10 Hz are achieved. The smart optical sensor platform will open doors to many applications that require high performance optical WSNs.

• Smart Structures and Systems
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• v.5 no.2
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• pp.119-137
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• 2009

Smart sensors densely distributed over structures can use their computational and wireless communication capabilities to provide rich information for structural health monitoring (SHM). Though smart sensor technology has seen substantial advances during recent years, implementation of smart sensors on full-scale structures has been limited. Hardware resources available on smart sensors restrict data acquisition capabilities; intrinsic to these wireless systems are packet loss, data synchronization errors, and relatively slow communication speeds. This paper addresses these issues under the hardware limitation by developing corresponding middleware services. The reliable communication service requires only a few acknowledgement packets to compensate for packet loss. The synchronized sensing service employs a resampling approach leaving the need for strict control of sensing timing. The data aggregation service makes use of application specific knowledge and distributed computing to suppress data transfer requirements. These middleware services are implemented on the Imote2 smart sensor platform, and their efficacy demonstrated experimentally.

• Smart Structures and Systems
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• v.30 no.6
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• pp.583-599
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• 2022

In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.264-266
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• 2005

Recently, on-line diagnosis methods through wired and wireless networks are widely adopted in the diagnosis of industrial Electric Facilities, such as generators, transformers and motors. Also smart sensors which includes sensors, signal conditioning circuits and micro-controller in one board are widely studied in the field of condition monitoring. This paper suggests an self-powered system suitable for condition-monitoring smart sensors, which uses parasitic vibrations of the facilities as energy source. First, vibration-driven noise patterns of the electric facilities are presented. And then, an electromagnetic generator which uses mechanical mass-spring vibration resonance are suggested and designed. Finally energy consumption of the presented smart sensor, which consists of MEMS vibration sensors, signal conditioning circuits, a low-power consumption micro-controller, and a ZIGBEE wireless tranceiver, are presented. The usefulness and limits of the presented electromagnetic generators in the field of electric facility monitoring are also suggested.