• 한국산학기술학회논문지
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• 제11권8호
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• pp.2975-2982
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• 2010

본 논문에서는 모델기반 설계를 이용한 이륜 도립진자 로봇의 설계방법에 대해 제시한다. 임베디드 시스템의 제어 프로그램 설계는 MATLAB/SIMULINK를 사용한 모델기반 설계에 의해 간편하고 손쉽게 구현되었으며, 로봇은 NXT 마인드스톰, 서보 직류전동기, 초음파센서, 자이로센서, 광센서로 구성되었다. 이 로봇은 불안정한 비선형시스템이며 몸체 경사각 제어문제를 가지고 있는데, 제어기 설계는 상태궤환 LQR 제어를 이용하였다. 타겟이 되는 프로세서에 종속적이지 않은 모델기반 설계는 문서기반 설계보다 프로그램 개발, 오류 발견 및 수정, 소프트웨어 구조 파악의 측면에서 장점을 가지고 있음을 제어기 설계와 실험을 통해서 확인할 수 있었다.

• 한국산학기술학회논문지
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• 제15권1호
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• pp.441-448
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• 2014

USN(Ubiquitous Sensor Network) 응용 소프트웨어는 다양한 대상 운영체제의 핵심모듈들을 기반으로, 다양한 종류의 센서 노드들을 유기적으로 제어하는 복잡한 특징을 가진다. 이에 따라, 현재 USN 응용 분야에서는 효율적으로 소프트웨어를 개발하기 위한 다양한 연구가 진행되고 있다. 본 논문에서는 센서 네트워크 환경에서 하나의 모델로 부터 여러 플랫폼에 맞는 노드 소프트웨어를 효율적으로 개발하기 위한 속성 기반 개발을 지원하는 속성 설계 기법을 제시한다. 제시된 기법에서는 Platform Independent Model과 Platform Specific Model을 만들기 위한 속성을 설계하는 방법을 기술한다. 본 논문에서 제시하는 기법을 사용하면, 속성 값의 선택을 통하여 멀티 플랫폼을 위한 노드 소프트웨어를 손쉽게 디자인함으로써 소프트웨어 개발 생산성은 증대된다. 또한 운영체제의 변화에 따라 속성 변경을 통하여 노드 소프트웨어를 쉽게 재생성할 수 있으므로, 소프트웨어의 유지보수성이 향상된다.

• 한국정밀공학회지
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• 제28권12호
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• pp.1372-1378
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• 2011

The smart air condition system is superior to conventional air condition system in the aspect of control accuracy, environmental preservation and it is foundation for intelligent vehicle such as electric vehicle, fuel cell vehicle. In this paper, failure analyses of smart air condition system will be performed and then sensor fusion technique will be proposed for fail safety of smart air condition system. A sensor fusion logic of air condition system by using CO sensor, $CO_2$ sensor and VOC, $NO_x$ sensor will be developed and simulated by fault injection simulation. The fusion technology of smart air condition system is generated in an experiment and a performance analysis is conducted with fusion algorithms. The proposed algorithm adds the error characteristic of each sensor as a conditional probability value, and ensures greater accuracy by performing the track fusion with the sensors with the most reliable performance.

• Journal of Biosystems Engineering
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• 제34권6호
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• pp.434-438
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• 2009

This study was conducted to design an cone penetrometer type impedance sensor that can measure soil water content in realtime. The best width between electrical probe was determined by 5 mm. For optimization about realtime application device, linear regression analysis was applied between soil water content and impedance signal. It was concluded that proper combination of excitation frequency, impedance parameter, and model would provide acceptible performance of a soil waler content sensoe. Best model was obatained at a 36.5 MHz with |Z| as a predictor variable, with a coefficient of determination of 0.96 (RMSE=1.35, RPD=4.98).

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.191-193
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• 2002

Insulation aging diagnosis system provides early warning in regard to electrical equipment defects. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. For solving this problem, many researchers proposed a method that diagnose power plant by using partial discharge. In this paper, we design the intelligent sensor to diagnose insulation degradation state that uses a Microprocessor and Al. Proposed sensor has MCU that is used to diagnose insulation degradation and communicate with main IDD system. And we use a fuzzy model to diagnose insulation degradation.

• 산업경영시스템학회지
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• 제34권4호
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• pp.57-65
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• 2011

Monitoring auto correlated processes is prevalent in recent manufacturing environments. As a proactive control for manufacturing processes is emphasized especially in the semiconductor industry, it is natural to monitor real-time status of equipment through sensor rather than resultant output status of the processes. Equipment's sensor data show various forms of correlation features. Among them, considerable amount of sensor data, statistically autocorrelated, is well represented by Box-Jenkins autoregressive moving average (ARMA) model. In this paper, we present a design method of statistical process control (SPC) used for monitoring processes represented by the ARMA model. The proposed method shows benefits in the power of detecting process changes, and considers robustness to ARMA modeling errors simultaneously. We prove benefits through Monte carlo simulation-based investigations.

• 한국기계가공학회지
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• 제16권2호
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• pp.7-15
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• 2017

Recently, an electricity sensor system has been installed and operated to prevent failures and accidents by identifying whether a transformer is normal in advance of failure. This electricity sensor system is able to both measure and monitor the transformer's power and voltage remotely and send information to a manager when unusual operation is discovered. However, a battery is required to operate power detection devices, and battery systems need ongoing management such as regular replacement. In addition, at a maintenance cost, occasional human resources and worker safety problems arise. Accordingly, we apply a linear electromagnetic generator using vibration energy from a transformer for an electric sensor system's drive in this research and we conduct optimal design to maximize the linear electromagnetic generator's power. We consider design variables using the provided design method from Process Integration, Automation, and Optimization (PIAnO), which is common tool from process integration and design optimization (PIDO). In addition, we analyze the experiment point from the design of the experiments using "MAXWELL," which is a common electromagnet analysis program. We then create an approximate model and conduct accuracy verification. Finally, we determine the optimal model that generates the maximum power using the proven approximate kriging model and evolutionary optimization algorithm, which we then confirm via simulation.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1999년도 가을 학술발표회 논문집
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• pp.397-404
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• 1999

It is essential to measure load transfer mechanism of pile to check the appropriateness of assumptions made for design purpose and to continuously monitor the behavior of pile foundation. Through many attempts to monitor the behavior of super-structure in civil engineering area using several optical fiber sensors have been made, application of optical fiber sensor technology on pile foundation has not been tried up to now. Load transfer of model piles during compression loading was measured by optical fiber sensors and compared with the measurement by strain gauges. Fiber Bragg Grating(FBG) sensor system was used since it has many advantages, such as easy multiplexing, high sensitivity, and simple fabrication. Besides the model pile tests, uniaxial tension test of steel bar and compression tests of mortar specimen were carried out to evaluate the performance of FBG sensors in embedded environments. The shift of refilming wavelength due to the strain in FBG sensor is converted to the strain at sensor location and the dependence between them is 1.28 pm/${\mu}$ strain. FBG sensors embedded in model pile showed a better survivability than strain gauges. Measured results of load transfer by both FBG sensors and strain gauges were similar, but FBG sensors showed a smoother trend than those by strain gauge. Based on the results of model pile test, it was concluded that the use of FBG sensor for strain measurement in pile has a great potential for the analysis of pile load transfer.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.95-101
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• 2020

We studied the Implementation and design of inertial sensor that enables to improve performance by reduce the noise of rotor which Angle of inclination. Analyze model equation including motion equation and error, signal processing filter algorithm on high frequency bandwidth with eliminates error using estimation of error coefficient method is was designed and the prototype inertial sensor showed the pick off noise up to 0.2 mV and bias error performance of about 0.06 deg/hr by the experiments. Accordingly, we confirmed that the design of inertial sensor was valid for high rotation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권4호
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.