• 전기전자학회논문지
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• 제22권4호
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• pp.907-915
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• 2018

본 논문에서는 저가형 적외선 거리 센서의 성능을 개선하는 방법을 제안한다. 적외선 거리 센서는 반사광의 강도를 측정하여 거리로 환산한다. 제안하는 방법은 센서의 감지 거리를 개선하고 다양한 조명환경에서도 강인하게 동작하도록 한다. 이는 센서의 특성곡선을 추출하고 이를 바탕으로 HDR(High Dynamic Range) 기법을 적용함으로써 가능해졌다. 적외선 입력의 세기와 노출 시간을 다양하게 변화시켜서 센서의 출력값을 획득하였고 이로부터 센서의 특성곡선을 추출하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4492-4507
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• 2021

In camera sensor networks (CSNs), in order to better identify the point, full-view problem requires capture any facing direction of target (point or intruder), and its coverage prediction and sensor density issues are more complicated. At present, a lot of research supposes that a large number of homogeneous camera sensors are randomly distributed in a bounded square monitoring region to obtain full-view rate which is close to 1. In this paper, we deduce the sensor density prediction model in heterogeneous deployed CSNs with arbitrary full-view rate. Aiming to reduce the influence of boundary effect, we introduce the concepts of expanded monitoring region and maximum detection area. Besides, in order to verify the performance of the proposed sensor density model, we carried out different scenarios in simulation experiments to verify the theoretical results. The simulation results indicate that the proposed model can effectively predict the sensor density with arbitrary full-view rate.

• 센서학회지
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• 제32권6호
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• pp.475-480
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• 2023

When modeling a sensor system mathematically, we assume that the sensor noise is Gaussian and white to simplify the model. If this assumption fails, the performance of the sensor model-based controller or estimator degrades due to incorrect modeling. In practice, non-Gaussian or non-white noise sources often arise in many digital sensor systems. Additionally, the noise parameters of the sensor model are not known in advance without additional noise statistical information. Moreover, disturbances or high nonlinearities often cause unknown sensor modeling errors. To estimate the uncertain noise and model parameters of a sensor system, this paper proposes an iterative batch calibration method using data-driven machine learning. Our simulation results validate the calibration performance of the proposed approach.

• Smart Structures and Systems
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• 제8권1호
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• pp.93-105
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• 2011

This paper presents a flexible low-profile antenna sensor for fatigue crack detection and monitoring. The sensor was inspired by the sense of pain in bio-systems as a protection mechanism. Because the antenna sensor does not need wiring for power supply or data transmission, it is an ideal candidate as sensing elements for the implementation of engineering sensor skins with a dense sensor distribution. Based on the principle of microstrip patch antenna, the antenna sensor is essentially an electromagnetic cavity that radiates at certain resonant frequencies. By implementing a metallic structure as the ground plane of the antenna sensor, crack development in the metallic structure due to fatigue loading can be detected from the resonant frequency shift of the antenna sensor. A monostatic microwave radar system was developed to interrogate the antenna sensor remotely. Fabrication and characterization of the antenna sensor for crack monitoring as well as the implementation of the remote interrogation system are presented.

• Journal of Communications and Networks
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• 제7권4호
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• pp.438-449
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• 2005

In this paper, we describes the information-theoretic approaches to sensor selection and sensor placement in sensor net­works for target localization and tracking. We have developed a sensor selection heuristic to activate the most informative candidate sensor for collaborative target localization and tracking. The fusion of the observation by the selected sensor with the prior target location distribution yields nearly the greatest reduction of the entropy of the expected posterior target location distribution. Our sensor selection heuristic is computationally less complex and thus more suitable to sensor networks with moderate computing power than the mutual information sensor selection criteria. We have also developed a method to compute the posterior target location distribution with the minimum entropy that could be achieved by the fusion of observations of the sensor network with a given deployment geometry. We have found that the covariance matrix of the posterior target location distribution with the minimum entropy is consistent with the Cramer-Rao lower bound (CRB) of the target location estimate. Using the minimum entropy of the posterior target location distribution, we have characterized the effect of the sensor placement geometry on the localization accuracy.

• 센서학회지
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• 제25권2호
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• pp.148-154
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• 2016

This paper describes the design and fabrication of a two-axis force/torque sensor and an one-axis force sensor with parallel plate beams(PPSs) for measuring forces and torque in an ankle rehabilitation exercise using by a lower rehabilitation robot. The two-axis force/torque sensor is composed of a Fy force sensor and Tz torque sensor and the force sensor detects x direction force. The two-axis force/torque sensor and one-axis force sensor were designed using by FEM(Finite Element Method), and manufactured using strain-gages. The characteristics experiment of the two-axis force/torque sensor and one-axis force sensor were carried out respectively. As a test results, the interference error of the two-axis force/torque sensor was less than 1.56%, the repeatability error and the non-linearity of the two-axis force/torque sensor were less than 0.03% respectively, and the repeatability error and the non-linearity of the one-axis force sensor were less than 0.03% and 0.02% respectively.

• 제어로봇시스템학회논문지
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• 제17권6호
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• pp.546-551
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• 2011

Tilt sensor is required to control the attitude of the biped robot when it walks on an uneven terrain. Vision sensor, which is used for recognizing human or detecting obstacles, can be used as a tilt angle sensor by comparing current image and reference image. However, vision sensor alone has a lot of technological limitations to control biped robot such as low sampling frequency and estimation time delay. In order to verify limitations of vision sensor, experimental setup of an inverted pendulum, which represents pitch motion of the walking or running robot, is used and it is proved that only vision sensor cannot control an inverted pendulum mainly because of the time delay. In this paper, to overcome limitations of vision sensor, Kalman filter for the multi-rate sensor fusion algorithm is applied with low-quality gyro sensor. It solves limitations of the vision sensor as well as eliminates drift of gyro sensor. Through the experiment of an inverted pendulum control, it is found that the tilt estimation performance of fusion sensor is greatly improved enough to control the attitude of an inverted pendulum.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 한국컴퓨터종합학술대회논문집 Vol.34 No.1 (D)
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• pp.105-108
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• 2007

Bayesian 학습 네트워크는 여러 가지의 다양한 응용 분야에 적용된다. 본 논문은 다양한 무선 센서 네트워크 환경에 적용될 수 있는 온라인 Bayesian 학습 네트워크의 추론 알고리즘 구조에 대하여 논의한다. 첫째, 논문은 Bayesian 파라메타 학습과 Bayesian DAG 구조 학습을 논의하고, 다음에 무선 센서 네트워크의 특징과 무선 환경에서의 데이터 수집에 대하여 논의한다. 둘째, 논문은 온라인 Bayesian 학습 네트워크에서의 중요한 고려 사항과 네트워크 학습 알고리즘의 개념적 구조에 대하여 논의한다.

• International journal of advanced smart convergence
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• 제6권3호
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• pp.38-44
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• 2017

Currently, wired gables have been installed or portable storage devices have been installed for data acquisition of flying drone. In this paper, we propose a technology to transmit data wirelessly by sensing information such as battery discharge value, acceleration, and temperature by attaching RF sensor to a drone. The purpose of this paper is to design and develop the monitoring technology of agriculture drone battery usage in real time using RF sensor. In this paper, we propose a monitoring system that can check real time data of battery changed value, temperature, and acceleration during pesticide control activity of agricultural drone.

• 소음진동
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• 제10권6호
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• pp.941-948
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• 2000

Active noise control is an approach to reduce the noise by utilizing a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and an adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Oppenheim assumed that transfer function characteristics from the canceling source to the error sensor is only a propagation delay. This paper proposes a modified Oppenheim algorithm by considering transfer characteristics of speaker-path-sensor This transfer characteristics is adaptively cancelled by the proposed adaptive modeling technique. Feasibility of the proposed method is proved by computer simulations with artificially generated random noises and sine wave noise. The details of the proposed architecture. and theoretical simulation of the noise cancellation system for three dimension enclosure are presented in the Paper.