• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.69-72
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• 2013

본 논문은 TPSN 알고리즘의 시각 동기화 오차를 개선하기 위하여 Imote2 센서 노드의 클럭 드리프트 특성을 적용하는 개선된 TPSN 알고리즘을 제안한다. 클럭 드리프트의 원인은 주로 수정발진기에 기인한다. 본 연구에서는 온도 및 습도 등 환경 조건이 비슷할 경우에 드리프트가 크게 차이나지 않는다는 실험 결과에 따라 드리프트의 평균값을 구하고 이를 TPSN 동기화 오차 보정에 사용한다. 이때 적용되는 드리프트 특성 값은 센서 노드 설치 이전에 미리 측정하여야 한다. 실험을 통하여 본 논문에서 제안한 개선된 TPSN 알고리즘이 동기화 오차 개선에 효과적임을 확인하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.830-834
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• 2013

This study presents a method to monitor cable force of a long-span cable-stayed bridge using a smart piezoelectric sensor system. The following approaches are implemented in order to achieve the objective. Firstly, the method to utilize piezoelectric materials for the health monitoring of stay cables is presented. For strain measurement of a stay cable, a PZT-embedded smart skin is designed to overcome the difficulties of bonding PZT sensors directly on stay cables. Secondly, a piezoelectric strain monitoring system for stay cables is designed. For the operation of the sensor board, the Imote2 sensor platform is used to provide the computation, wireless communication and power supply units. The feasibility of the proposed monitoring system is then evaluated on a full-scale cable of a cable-stayed bridge.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.381-397
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• 2013

In this paper, wireless health monitoring of stay cables using piezoelectric strain sensors and a smart skin technique is presented. For the cables, tension forces are estimated to examine their health status from vibration features with consideration of temperature effects. The following approaches are implemented to achieve the objective. Firstly, the tension force estimation utilizing the piezoelectric sensor-embedded smart skin is presented. A temperature correlation model to recalculate the tension force at a temperature of interest is designed by correlating the change in cable's dynamic features and temperature variation. Secondly, the wireless health monitoring system for stay cables is described. A piezoelectric strain sensor node and a tension force monitoring software which is embedded in the sensor are designed. Finally, the feasibility of the proposed monitoring technique is evaluated on stay cables of the Hwamyung Grand Bridge in Busan, Korea.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.399-414
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• 2013

The smart sensor technology has opened new horizons for assessing and monitoring structural health of civil infrastructure. Smart sensor's unique features such as onboard computation, wireless communication, and cost effectiveness can enable a dense network of sensors that is essential for accurate assessment of structural health in large-scale civil structures. While most research efforts to date have been focused on realizing wireless smart sensor networks (WSSN) on bridge structures, relatively less attention is paid to applying this technology to buildings. This paper presents a decentralized damage detection using the WSSN for building structures. An existing flexibility-based damage detection method is extended to be used in the decentralized computing environment offered by the WSSN and implemented on MEMSIC's Imote2 smart sensor platform. Numerical simulation and laboratory experiment are conducted to validate the WSSN for decentralized damage detection of building structures.

• 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.11 no.5
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• pp.477-496
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• 2013

Due to their cost-effectiveness and ease of installation, wireless smart sensors (WSS) have received considerable recent attention for structural health monitoring of civil infrastructure. Though various wireless smart sensor networks (WSSN) have been successfully implemented for full-scale structural health monitoring (SHM) applications, monitoring of low-level ambient strain still remains a challenging problem for WSS due to A/D converter (ADC) resolution, inherent circuit noise, and the need for automatic operation. In this paper, the design and validation of high-precision strain sensor board for the Imote2 WSS platform and its application to SHM of a cable-stayed bridge are presented. By accurate and automated balancing of the Wheatstone bridge, signal amplification of up to 2507-times can be obtained, while keeping signal mean close to the center of the ADC span, which allows utilization of the full span of the ADC. For better applicability to SHM for real-world structures, temperature compensation and shunt calibration are also implemented. Moreover, the sensor board has been designed to accommodate a friction-type magnet strain sensor, in addition to traditional foil-type strain gages, facilitating fast and easy deployment. The wireless strain sensor board performance is verified through both laboratory-scale tests and deployment on a full-scale cable-stayed bridge.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.998-1013
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• 2013

Wireless wearable sensor networks have emerged as a promising technique for human motion tracking due to the flexibility and scalability. In such system several wireless sensor nodes being attached to human limb construct a wearable sensor network, where each sensor node including MEMS sensors (such as 3-axis accelerometer, 3-axis magnetometer and 3-axis gyroscope) monitors the limb orientation and transmits these information to the base station for reconstruction via low-power wireless communication technique. Due to the energy constraint, the high fidelity requirement for real time rendering of human motion and tiny operating system embedded in each sensor node adds more challenges for the system implementation. In this paper, we discuss such challenges and experiences in detail during the implementation of such system with wireless wearable sensor network which includes COTS wireless sensor nodes (Imote 2) and uses TinyOS 1.x in each sensor node. Since our system uses the COTS sensor nodes and popular tiny operating system, it might be helpful for further exploration in such field.

• Smart Structures and Systems
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• v.18 no.3
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• pp.541-568
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• 2016

The goal of this study is to investigate the effect of non-synchronous sensing when using wireless sensors on structural identification and to attempt correcting such errors in order to obtain a better identification result. The sources causing non-synchronous sensing are discussed first and the magnitudes of such synchronization errors are estimated based on time stamps of data samples collected from Imote2 sensors; next the impact of synchronization errors on power spectral densities (PSDs) and correlation functions of output responses are derived analytically; finally a new method is proposed to correct such errors. In this correction method, the corrected PSDs of output responses are estimated using non-synchronous samples based on a modified FFT. The effect of synchronization errors in the measured output responses on structural identification and the application of this correction method are demonstrated using simulation examples. The simulation results show that even small synchronization errors in the output responses can distort the identified modal and stiffness parameters remarkably while the parameters identified using the proposed correction method can achieve high accuracy.

• Smart Structures and Systems
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• v.9 no.6
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• pp.489-504
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• 2012

For the safety of prestressed structures such as cable-stayed bridges and prestressed concrete bridges, it is very important to ensure the prestress force of cable or tendon. The loss of prestress force could significantly reduce load carrying capacity of the structure and even result in structural collapse. The objective of this study is to present a smart PZT-interface for wireless impedance-based prestress-loss monitoring in tendon-anchorage connection. Firstly, a smart PZT-interface is newly designed for sensitively monitoring of electro-mechanical impedance changes in tendon-anchorage subsystem. To analyze the effect of prestress force, an analytical model of tendon-anchorage is described regarding to the relationship between prestress force and structural parameters of the anchorage contact region. Based on the analytical model, an impedance-based method for monitoring of prestress-loss is conducted using the impedance-sensitive PZT-interface. Secondly, wireless impedance sensor node working on Imote2 platforms, which is interacted with the smart PZT-interface, is outlined. Finally, experiment on a lab-scale tendon-anchorage of a prestressed concrete girder is conducted to evaluate the performance of the smart PZT-interface along with the wireless impedance sensor node on prestress-loss detection. Frequency shift and cross correlation deviation of impedance signature are utilized to estimate impedance variation due to prestress-loss.

• Smart Structures and Systems
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• v.18 no.5
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• pp.885-909
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• 2016

Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve $50{\mu}s$ synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.