• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.938-942
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• 2007

The proposed algorithm tries to localize damage in a structure by monitoring abnormal increases in strain measurements from a group of wireless sensors. Initially, this clustering technique provides an 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. 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.

• Journal of information and communication convergence engineering
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• 제12권1호
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• pp.8-13
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• 2014

We consider the sensor selection problem in large sensor networks where the goal is to find the best set of sensors that maximizes application objectives. Since sensor selection typically involves a large number of sensors, a low complexity should be maintained for practical applications. We propose a geometry-based sensor selection algorithm that utilizes only the information of sensor locations. In particular, by observing that sensors clustered together tend to have redundant information, we theorize that the redundancy is inversely proportional to the distance between sensors and seek to minimize this redundancy by searching for a set of sensors with the maximum average distance. To further reduce the computational complexity, we perform an iterative sequential search without losing optimality. We apply the proposed algorithm to an acoustic sensor network for source localization, and demonstrate using simulations that the proposed algorithm yields significant improvements in the localization performance with respect to the randomly generated sets of sensors.

• Composites Research
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• 제18권5호
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• pp.1-8
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• 2005

Among many fabrication methods of composite materials, filament winding is the most effective method for fabricating axis-symmetric structures such as pressure tanks and pipes. Filament wound pressure tanks are under high internal pressure during the operation and it has the complexity in damage mechanisms and failure modes. For this reason, it is necessary to monitor the tank through its operation as well as whole fabrication process. A large number of sensors must be embedded into multi points of the tank from its fabrication step for monitoring the whole tank. Fiber optic sensors, especially fiber Bragg grating(FBG) sensors are widely used for various applications because of good multiplexing capabilities. However, we need to develop the embedding technique of FBG sensors into harsh inner environment of the tank far the successful embedment. In this paper, we studied the embedding technique of a number of FBG sensors into filament wound pressure tanks considering multiplexing.

• Progress in Superconductivity and Cryogenics
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• 제20권1호
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• pp.11-14
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• 2018

High Temperature Superconducting (HTS) power cables are capable of transmitting bulk power without any loss compared to conventional copper cables. The major challenge in the design of such HTS cables is the high stresses (electro-thermal/electro-mechanical) developed at high voltages, high currents and cryogenic temperatures. The safe and reliable operation of HTS cables involves lots of instrumentation for monitoring, measurement, control and safe operation. In principle, a four probe method for resistance (RTD PT-100) is used for temperature measurements at various locations of HTS cable. The number of connecting leads required for this is four times that of the number of sensors. The present paper discusses a novel way of connecting 128 RTD sensors with the help of only 14 leads using a cold electronics based multiplexer board. LabVIEW 11.0 software was used for interfacing and displaying the readings of all the sensors on computer screen.

• Smart Structures and Systems
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• 제5권4호
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• pp.369-379
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• 2009

The sudden collapse of Interstate 35 Bridge in Minneapolis gave a wake-up call to US municipalities to re-evaluate aging bridges. In this situation, structural health monitoring (SHM) technology can provide the essential help needed for monitoring and maintaining the nation's infrastructure. Monitoring long span bridges such as cable-stayed bridges effectively requires the use of a large number of sensors. In this article, we introduce a probabilistic approach to identify optimal locations of sensors to enhance damage detection. Probability distribution functions are established using an artificial neural network trained using a priori knowledge of damage locations. The optimal number of sensors is identified using multi-objective optimization that simultaneously considers information entropy and sensor cost-objective functions. Luling Bridge, a cable-stayed bridge over the Mississippi River, is selected as a case study to demonstrate the efficiency of the proposed approach.

• Smart Structures and Systems
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• 제15권2호
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• pp.355-373
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• 2015

An optimal sensor placement (OSP) method based on structural subsection technique (SST) and model reduction technique was proposed for modal identification of truss structures, which was conducted using genetic algorithm (GA). The constraints of GA variables were determined by SST in advance. Subsequently, according to model reduction technique, the optimal group of master degrees of freedom and the optimal objective function value were obtained using GA in a case of the given number of sensors. Correspondingly, the optimal number of sensors was determined according to optimal objective function values in cases of the different number of sensors. The proposed method was applied on a scaled jacket offshore platform to get its optimal number of sensors and the corresponding optimal sensor layout. Then modal kinetic energy and modal assurance criterion were adopted to evaluate vibration energy and mode independence property. The experiment was also conducted to verify the effectiveness of the selected optimal sensor layout. The results showed that experimental modes agreed reasonably well with numerical results. Moreover the influence of the proposed method using different optimal algorithms and model reduction technique on optimal results was also compared. The results showed that the influence was very little.

• Journal of Korean Institute of Industrial Engineers
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• 제24권4호
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• pp.613-625
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• 1998

This paper addresses a fundamental and theoretical model for the shape of a cucumber and its human-oriented proper definition of length and curvature in order to sort cucumbers electronically. In addition, we design a T-shaped array of sensors to minimize the number of sensors and the processing number of A/D(Analog/Digital) conversions, and we analyze regular patterns of a series of 1's and 0's which are converted from an A/D module. Finally we suggest an algorithm for measuring the length and curvature providing a rule from the regular patterns. The methodology suggested in this paper could be applied to electronical classification of some crops and fruits such as tomatoes, apples, and so on, and can be a basis for developing other sorting machines.

• Interaction and multiscale mechanics
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• 제3권2호
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• pp.111-121
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• 2010

Dynamic analysis of nano/micro bio-sensors based on a multiscale atomistic/continuum theory is introduced. We use a generalized atomistic finite element method (GAFEM) to analyze a bio-sensor which has $3{\times}N_a{\times}N_p$ degrees of freedom, where $N_p$ is the number of representative unit cells and $N_a$ is the number of atoms per unit cell. The stiffness matrix is derived from interatomic potential between pairs of atoms. This work contains two studies: (1) the resonance analysis of nano bio-sensors with different amount of target analyte and (2) the dependence of resonance frequency on finite element mesh. We also examine the Courant-Friedrichs-Lewy (CFL) condition based on the highest resonance frequency. The CFL condition is the criterion for the time step used in the dynamic analysis by GAFEM. Our studies can be utilized to predict the performance of micro/nano bio-sensors from atomistic perspective.

• Journal of Sensor Science and Technology
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• 제25권3호
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• pp.178-183
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• 2016

Semiconductor gas sensors based on metal oxide are widely used in a number of applications, from health and safety to energy efficiency and emission control. Nanomaterials including nanowires, nanorods, and nanoparticles have dominated the research focus in this field owing to their large number of surface sites that facilitate surface reactions. Recently, metal oxide hollow structures using soft templates have been developed owing to their high sensing properties with large-area uniformity. Here, we provide a brief overview of metal oxide hollow structures and their gas-sensing properties from the aspects of template size, morphology, and additives. In addition, a gas-sensing mechanism and perspectives are presented.

• Smart Structures and Systems
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• 제5권4호
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• pp.469-482
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• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.