• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.1-7
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• 2015

In this paper, a new capacitive pressure sensor has been proposed for a displacement measurement. The new sensor is mainly composed of a gap of $5{\mu}m$ and a notch of $1{\mu}m$. And the sensor has the performance as the high sensitivity and capacitance compared with a commercial capacitive sensor. Therefore, the advantages of the new capacitive pressure sensor are good sensitivity in normal range, mechanically robust and large overload protection. The analytical model is induced for confirming the performance of the proposed sensor. In addition, FEM (finite elements method) simulation has been performed to verify the analytical model. Firstly, the displacement characteristics of diaphragm membrane were simulated by the analytical model and FEM in the case of different structure and materials. At last, through this analysis, these simulation results can be predicted the change of the performance when the device parameters are varied. And it is used as a design tool to achieve at a set of performance we desired.

• Smart Structures and Systems
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• v.26 no.5
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• pp.591-603
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• 2020

Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.103-109
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• 2022

This significance of the infant care system has emerged due to sudden infant death during sleeping. This paper presented a design and implementation of a prototype model, which is a infant care device controlled by a smartphone using Bluetooth technology. Prototype Device Model consists of MCU(microcontroller unit), Accelerometer Sensor, Temperature Measuring Sensor, Sound Measuring Sensor, Bluetooth Module, and Camera Module. The proposed application transfers the information to the parent's smartphone and computers, such as infant's falling, crying, and fever detection. A test verified the availability of a prototype infant care system model using Bluetooth Low Energy with operating the low power driving.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.9
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• pp.414-419
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• 2006

This paper presents a design of a multi-sensor data fusion filter for a Flight Test System. The multi-sensor data consist of positional information of the target from radars and a telemetry system. The data fusion filter has a structure of a federated Kalman filter and is based on the Singer dynamic target model. It consists of dedicated local filter for each sensor, generally operating in parallel, plus a master fusion filter. A fault detection and correction algorithms are included in the local filter for treating bad measurements and sensor faults. The data fusion is carried out in the fusion filter by using maximum likelihood estimation algorithm. The performance of the designed fusion filter is verified by using both simulation data and real data.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.122-125
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• 2008

Sensors used in many USN (Ubiquitous Sensor Network) domain applications generate a large amount of sensor stream data. The volume of sensor stream data is too huge to store the whole data and data speed is too fast to control each of them. In order to provide rapid and reliable context analysis service over sensor stream data, we propose a WHEN-DO context analysis model that supports the functionality of sliding window. This model is designed to be used as follows: If the sensor stream data satisfies condition in 'WHEN' clause, then it will execute actions in 'DO' clause in WHEN-DO context analysis model. The proposed WHEN-DO context analysis model can be applied to many other USN environment applications such as monitoring the status of a building and then taking actions in corresponding context condition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.506-513
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• 2007

This paper proposes a rotary magnetic position sensor which has a sinusoidally magnetized permanent magnet with a small number of poles. To make the sinusoidal magnetic flux density distribution from the permanent magnet, a magnetizing future is optimized by the DOE(Design of Experiments) method. The magnetization process is analyzed using the Preisach model and 2 dimensional finite element method. The magnetic flux density distribution from the magnetized permanent magnet is very similar to ideal sine wave. The simulation result of the magnetic flux density distribution is compared with the experimental one. Also the availability of the proposed rotary type magnetic position sensor is confirmed by position calculation technique.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.51-58
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• 2014

As WSNs(Wireless Sensor Networks) are being deployed widely in diverse application areas, their management and maintenance become more important. Recent sensor node software takes modular software architectures in pursuit of flexible software management and energy efficient reprogramming. To realize an flexible and efficient modular architecture particularly on resource constrained mote-class sensor nodes that are implemented with MCUs(Micro-Controller Units) of a single address space. an appropriate module linking model is essential to resolve and bind the inter-module global symbols. This paper identifies a design space of module linking model and respectively their implementation frameworks. We then establish a taxonomy for module linking models by exploring the design space of module linking models. Finally, we suggest an implementation framework respectively for each module linking model in the taxonomy. We expect that this work lays the foundations for systematic innovation toward more flexible and efficient modular software architectures for WSNs.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.131-138
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• 2022

Soft sensors are used to anticipate complicated model parameters using data from classifiers that are comparatively easy to gather. The goal of this study is to use artificial intelligence techniques to design and build soft sensors. The combination of a Long Short-Term Memory (LSTM) network and Grey Wolf Optimization (GWO) is used to create a unique soft sensor. LSTM is developed to tackle linear model with strong nonlinearity and unpredictability of manufacturing applications in the learning approach. GWO is used to accomplish input optimization technique for LSTM in order to reduce the model's inappropriate complication. The newly designed soft sensor originally brought LSTM's superior dynamic modeling with GWO's exact variable selection. The performance of our proposal is demonstrated using simulations on real-world datasets.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.207-211
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• 2004

The performance of an inductive position sensor has approved by previous research papers. In this paper, magnetic circuit model of a ring-type multi-pole insuctive position sensor is described. The magnetic circuit model is required to design in ductive position sensor as well as draw a fault tolerance algorithm. Using the magnetic circuit theory, we derived the relationship between voltage applied and flux density in the normal air-gap. By idealizing the modulation/demodulation processes of signal processing circuit, sensor gain with respect to change of displacement is theoretically calculation using the magnetic circuit model, which validate the theoretical derivation.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.42-49
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• 2005

Our purpose is to develop a precision magnetic displacement sensor that has sub-micron resolution and small size probe. To achieve this, we first have tried to establish mathematical models of a magnetic sensor in this paper. The inductance model that presents basic measuring principle of a magnetic sensor is based on equivalent magnetic circuit method. Especially we have concentrated on modeling of magnetic flux leakage and magnetic flux fringing. The induced model is verified by experimental results. The model, including the magnetic flux leakage and flux fringing effects, is in good agreement with the experimental data. Subsequently, based on the augmented model, we will design magnetic sensor probe in order to obtain high performances and to scale down the probe.