• 제목/요약/키워드: Multi-sensors

검색결과 986건 처리시간 0.022초

유전 알고리듬을 이용한 압전센서의 전극형상 최적화 (Electrode Shape Optimization of Piezo Sensors Using Genetic Algorithm)

  • 이기문;박현철;박철휴
    • 대한기계학회논문집A
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    • 제30권6호
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    • pp.698-704
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    • 2006
  • This paper presents an electrode shape design method for the multi-mode sensors that could deteict the selected structural multiple modes. The structure used for this study is an isotropic cantilever beam type with a PVDF (polyvinylidene fluoride) which is bonded onto the structure as a sensor. The shape optimization problem is solved by using Genetic Algorithm (GA) with an appropriate objective function. The performance of analytical optimal shape sensor is compared with that of experimental work. The results show that the, obtained electrode shape sensors have good performance to detect the multiple vibration modes simultaneously.

광학 어드미턴스 기법과 진화 알고리즘 기법을 이용한 다층 표면 플라즈몬 공명 센서의 설계 (Design of multi-layered surface plasmon resonance sensors using optical admittance method and evolution algorithm)

  • 정재훈;이승기
    • 센서학회지
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    • 제14권6호
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    • pp.402-408
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    • 2005
  • This paper describes the optimal design of a multi-layered surface plasmon resonance sensors to meet various specifications and improve some physical parameters. Dip 3 dB bandwidth and depth were chosen as design parameters and the objective function was the norm of the difference between design parameters and target values. The design variables are thicknesses of each layer and to obtain the design parameters, the optical admittance method was employed. The (1+1) evolution strategy was employed as an optimization tool. By applying the proposed optimization procedure to a 3-layered sensor, the optimized design variables considerably improved the 3 dB bandwidth by 4.8 nm and the dip depth by 1.1 dB.

탄소나노튜브 스마트 복합소재의 전기적 임피던스 변화를 이용한 나노센서의 센싱 특성 연구 (A Study on Sensing Characteristics of Carbon Nanotube Smart Composite Nano Sensors Based on Electrical Impedance Measurement)

  • 강인필
    • 동력기계공학회지
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    • 제13권1호
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    • pp.65-71
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    • 2009
  • To address the need for new intelligent sensing, this paper introduces nano sensors made of carbon nanotube (CNT) composites and presents their preliminary experiments. Having smart material properties such as piezoresistivity, chemical and bio selectivity, the nano composite can be used as smart electrodes of the nano sensors. The nano composite sensor can detect structural deterioration, chemical contamination and bio signal by means of its impedance measurement (resistance and capacitance). For a structural application, the change of impedance shows specific patterns depending on the structural deterioration and this characteristic is available for an in-situ multi-functional sensor, which can simultaneously detect multi symptoms of the structure. This study is anticipated to develop a new nano sensor detecting multiple symptoms in structural, chemical and bio applications with simple electric circuits.

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IMFP 장착각도가 T-50 초음속 고도정보에 미치는 영향 (The Effect of an Installation Angle of IMFP sensors on Estimation of Altitude of T-50 Aircraft in the Transonic Region)

  • 남용석;김윤희;송석봉;김성준
    • 항공우주시스템공학회지
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    • 제3권1호
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    • pp.1-5
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    • 2009
  • The flight control of the T-50 advanced trainer is conducted by the digital FBW (Flight-by-Wire) control system. The system input data consist of flight conditions such as altitude, airspeed, and angle of attack. And the flight conditions of the aircraft are obtained from IMFP (Integrated Multi-Function Probe). The T-50 aircraft equip three IMFP sensors. To ensure reliability in flight condition data obtained from each IMFP sensor, the mean value of flight conditions is used as the input of the control system. In this study, the effect of an installation angle of IMFP sensors on estimation of flight altitude was investigated by flight test results in the supersonic region.

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다중 센서 데이터 분석을 이용한 동적보정점 결정 기법 (A Dynamic Configuration of Calibration Points using Multidimensional Sensor Data Analysis)

  • 김병섭;김재훈
    • 경영과학
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    • 제33권1호
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    • pp.49-58
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    • 2016
  • Focusing on the drastic increase of smart devices, machine generated data expansion is a general phenomenon in network services and IoT (Internet of Things). Especially, built-in multi sensors in a smart device are used for collection of user status and moving data. Combining the internal sensor data and environmental information, we can determine landmarks that decide a pedestrian's locations. We use an ANOVA method to analyze data acquired from multi sensors and propose a landmark classification algorithm. We expect that the proposed algorithm can achieve higher accuracy of indoor-outdoor positioning system for pedestrians.

간단한 블루투스 무선다중가스센서 계측시스템 (Simple Bluetooth Wireless Multi-gas Measurement System)

  • 김철민;김도윤;김연수;김규태
    • 반도체디스플레이기술학회지
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    • 제19권2호
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    • pp.51-54
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    • 2020
  • To develop gas-distinguishing sensor system, it is highly required to integrate multiple sensors for effective detection of a single targeted gas or mixture of gases. In addition, it is important to collect the reliable data from individual sensors into one integrated measuring device. Collecting the data of toxic gases on the spot should be done without inhalation. We suggest simple wirelessly running system for data collection that guarantees both reliability of data sources and safety. Here, we made a multi-gas measuring instrument(device) combined with Bluetooth module which provides a safe and precise big data accumulation system.

IoT 네트워크에서 다중 스케일 PCA 를 사용한 트렌드 적응형 이상 탐지 (Trend-adaptive Anomaly Detection with Multi-Scale PCA in IoT Networks)

  • Dang, Thien-Binh;Tran, Manh-Hung;Le, Duc-Tai;Choo, Hyunseung
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2018년도 춘계학술발표대회
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    • pp.562-565
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    • 2018
  • A wide range of IoT applications use information collected from networks of sensors for monitoring and controlling purposes. However, the frequent appearance of fault data makes it difficult to extract correct information, thereby sending incorrect commands to actuators that can threaten human privacy and safety. For this reason, it is necessary to have a mechanism to detect fault data collected from sensors. In this paper, we present a trend-adaptive multi-scale principal component analysis (Trend-adaptive MS-PCA) model for data fault detection. The proposed model inherits advantages of Discrete Wavelet Transform (DWT) in capturing time-frequency information and advantages of PCA in extracting correlation among sensors' data. Experimental results on a real dataset show the high effectiveness of the proposed model in data fault detection.

LSTM-based Early Fire Detection System using Small Amount Data

  • Seonhwa Kim;Kwangjae Lee
    • 반도체디스플레이기술학회지
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    • 제23권1호
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    • pp.110-116
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    • 2024
  • Despite the continuous advancement of science and technology, fire accidents continue to occur without decreasing over time, so there is a constant need for a system that can accurately detect fires at an early stage. However, because most existing fire detection systems detect fire in the early stage of combustion when smoke is generated, rapid fire prevention actions may be delayed. Therefore we propose an early fire detection system that can perform early fire detection at a reasonable cost using LSTM, a deep learning model based on multi-gas sensors with high selectivity in the early stage of decomposition rather than the smoke generation stage. This system combines multiple gas sensors to achieve faster detection speeds than traditional sensors. In addition, through window sliding techniques and model light-weighting, the false alarm rate is low while maintaining the same high accuracy as existing deep learning. This shows that the proposed fire early detection system is a meaningful research in the disaster and engineering fields.

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A study on aerial triangulation from multi-sensor imagery

  • Lee, Young-ran;Habib, Ayman;Kim, Kyung-Ok
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.400-406
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    • 2002
  • Recently, the enormous increase in the volume of remotely sensed data is being acquired by an ever-growing number of earth observation satellites. The combining of diversely sourced imagery together is an important requirement in many applications such as data fusion, city modeling and object recognition. Aerial triangulation is a procedure to reconstruct object space from imagery. However, since the different kinds of imagery have their own sensor model, characteristics, and resolution, the previous approach in aerial triangulation (or georeferencing) is performed on a sensor model separately. This study evaluated the advantages of aerial triangulation of large number of images from multi-sensors simultaneously. The incorporated multi-sensors are frame, push broom, and whisky broom cameras. The limits and problems of push-broom or whisky broom sensor models can be compensated by combined triangulation with frame imagery and vise versa. The reconstructed object space from multi-sensor triangulation is more accurate than that from a single model. Experiments conducted in this study show the more accurately reconstructed object space from multi-sensor triangulation.

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다중센서를 적용한 자동배변처리기용 제어기 설계 (Controller Design for Automatic Evacuation Disposal System with Multi-sensors)

  • 문인혁
    • 재활복지공학회논문지
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    • 제5권1호
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    • pp.71-77
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    • 2011
  • 이 논문은 장기요양환자의 배변 간병에 사용하는, 흡입, 수집, 세정 그리고 건조가 가능한 자동배변처리기용 제어기의 설계를 제안한다. 자동배변처리기는 소변과 대변을 구분하고, 간병인의 최소 노력만으로도 배설물을 처리하는 것이 바람직하다. 따라서 본 연구에서는 다중센서를 채택하여 대변과 소변의 분리 능력을 향상시키고, 분리된 배설물은 각각 정해진 방법으로 처리함으로써 효율적 배변처리가 가능하도록 하였다. 인공 대변과 소변을 이용한 일련의 실험을 통하여 제안된 자동배변처리기와 제어기가 효율적인 배변 간병을 실현할 수 있음을 보인다.