• Structural Engineering and Mechanics
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• v.8 no.5
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• pp.453-464
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• 1999

Safety monitoring systems of structures generally resort to detecting possible changes of dynamic system parameters. Sensitivity analysis of these dynamic system parameters may implement these techniques. Conventional structural eigenvalue problems are discussed in the scope of those systems with deterministic parameters. Large and flexible structures, such as suspension bridges, actually possess stochastic material properties and these random properties unavoidably affect the dynamic system parameters. The sensitivity matrix of structural modal parameters to basic design variables has been established in this paper. Moreover, second order statistics of natural frequencies due to the randomness of material properties have been discussed. It is concluded from numerical analysis of a modem suspension bridge that although the second order statistics of frequencies are small relatively to the change of basic design variables, such as density of mass and modulus of elasticity, the sensitivities of modal parameters to these variables at different locations change in magnitude.

• Journal of the Korea institute for structural maintenance and inspection
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• v.13 no.1 s.53
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• pp.145-151
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• 2009

The span deflection among the monitoring items of bridge measurement system in real time is representative behaviour and important index of superstructure condition. the limit of span deflection in Standard Specifications for Highway Bridge in Korea has been applied to the method that is making the management-criteria for span deflection in bridge measurement system. But the limit concern mainly serviceability of divers. So it is difficult to find the safety factor of the limit from the viewpoint of bridge safety. This study estimated the safety factor of the limit of span-deflection in Standard Specifications for Highway Bridge in Korea from the viewpoint of bridge safety by the indoor structural test.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.4
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• pp.9-16
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• 2008

Ubiquitous technology is proposed which is used wireless sensor network for deflection management at casting and after casting of FCM bridge. Proposed method are analyzed which are sensor experiment and existing FCM bridge using ubiquitous sensor network. Wireless sensor network enables low-cost sensing of environment. As a results, the field application shows that USN is useful method for structural health monitoring system which long distance away.

• IEMEK Journal of Embedded Systems and Applications
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• v.1 no.2
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• pp.43-55
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• 2006

A home network is a typical ubiquitous computing network that consists of various consumer devices and service environments. Home networks are requiring increasingly more complicated services, such as multimedia home theater and the monitoring and controlling of heterogeneous devices. Accordingly, a mutually connecting mechanism is needed among heterogeneous devices and services redundant. The current paper presents a Multimedia Room Bridge Adapter (MRBA) system that is designed to manage heterogeneous devices and support various services. In addition, a hardware and software prototype is implemented based on the proposed architecture.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.322-327
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• 2006

Banwol bridge with steel plate girder and Pyongtaek bridge with PSC bos girder have been operated maintenance measuring system by the Seoul-Chonan of Kyongbu express railway. By analyzing the theoretical and experimental values of design load for these two bridge, the establishment of reference maintenance for measuring items was deduced from research. Two materials, steel and concrete plates, were considered as the upper structure. Actual measurement data for the behavior under speed, structural analysis results, and the presented references were analyzed and used to set up the reference establishment. The measuring items are stress(strain), displacement, dynamic acceleration, expansion movement, and dynamic frequency. The maintenance reference was established by comparing analytical and measuring values of the five items with respect to structural state class.

• Journal of Sensor Science and Technology
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• v.19 no.2
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• pp.124-129
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• 2010

For the industrial printing applications, the stability of the piezo-driven inkjet printhead is a major requirement. In this paper, we focused on the failure modes of the inkjet printhead and realized a method to detect and repair them at high speed. The printhead monitoring is performed by detecting the residual vibration of the actuating plate using the self- sensing capability of the piezoelectric material. To measure the channel acoustics and to identify the malfunctioning nozzle, we devised the bridge sensing circuitry and failure detection algorithm. The residual vibration signals can be affected by the boundary conditions of the channel acoustics, so it is possible to identify the failure causes by analyzing the monitoring signals. Therefore it is also possible to apply a proper restoring process to the defective printhead. The experimental results show that this method is effective in improving the reliability of the industrial printing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1423-1432
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• 2011

Since the marine accidents increase with the increased volume of traffic, preventive surveillance technology for safety navigation of the ships before the accident is being emphasized to secure the safety at sea along with post-accident measures. This paper aims to suggest a design based on an integrated safety management platform systems to support nautical safety, implements of bridge operation terminal equipments and alarm system for bridge watch monitoring and abnormal state of navigation/propulsion/machinery/power, and performs a quality evaluation for the actual boarding on the ship based on the classification standards.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.761-765
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• 2008

This study presents an effective methodology on integrated monitoring system for a maglev guideway using WDM-based FBG sensors. The measuring quantities include both local and global quantities of the guideway response, such as stains, curvatures, and vertical deflections. The strains are directly measured from multiplexed FBG sensors at various locations of the test bridge followed by curvature calculations based on the plane section assumption. Vertical deflections are then estimated using the Bernoulli beam theory and regression analysis. Frequency contents obtained from the proposed method are compared with those from a conventional accelerometer. Verification tests were conducted on the newly-developed Korean Maglev test track. It has been shown that good agreement between the measured deflection and the estimated deflection is achieved. The difference between the two peak displacements was only 3.5% in maximum and the correlations between data from two sensing systems are overall very good. This confirms that the proposed technique is capable of tracing the dynamic behavior of the maglev guideway with an acceptable accuracy. Furthermore, it is expected that the proposed scheme provides an effective tool for monitoring the behavior of the maglev guideway structures without electro magnetic interference.

• Smart Structures and Systems
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• v.17 no.6
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• pp.995-1015
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• 2016

In the design and condition assessment of bridges, it is usually necessary to take into consideration the extreme conditions which are not expected to occur within a short time period and thus require an extrapolation from observations of limited duration. Long-term structural health monitoring (SHM) provides a rich database to evaluate the extreme conditions. This paper focuses on the extrapolation of extreme traffic load effects on bridges using long-term monitoring data of structural strain. The suspension Tsing Ma Bridge (TMB), which carries both highway and railway traffic and is instrumented with a long-term SHM system, is taken as a testbed for the present study. Two popular extreme value extrapolation methods: the block maxima approach and the peaks-over-threshold approach, are employed to extrapolate the extreme stresses induced by highway traffic and railway traffic, respectively. Characteristic values of the extreme stresses with a return period of 120 years (the design life of the bridge) obtained by the two methods are compared. It is found that the extrapolated extreme stresses are robust to the extrapolation technique. It may owe to the richness and good quality of the long-term strain data acquired. These characteristic extremes are also compared with the design values and found to be much smaller than the design values, indicating conservative design values of traffic loading and a safe traffic-loading condition of the bridge. The results of this study can be used as a reference for the design and condition assessment of similar bridges carrying heavy traffic, analogous to the TMB.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.