• 센서학회지
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• 제32권1호
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• pp.31-38
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• 2023

Three-dimensional (3D) micro/nanostructures based on soft elastomers have received extensive attention in recent years, owing to their potential and advanced applicability. Designing and fabricating 3D micro/nanostructures are crucial for applications in diverse engineering fields, such as sensors, harvesting devices, functional surfaces, and adhesive patches. However, because of their structural complexity, fabricating soft-elastomer-based 3D micro/nanostructures with a low cost and simple process remains a challenge. Bio-inspired designs that mimic natural structures, or replicate their micro/nanostructure surfaces, have greatly benefited in terms of low-cost fabrication, scalability, and easy control of geometrical parameters. This review highlights recent advances in 3D micro/nanostructures inspired by nature for diverse potential and advanced applications, including flexible pressure sensors, energy-harvesting devices based on triboelectricity, superhydrophobic/-philic surfaces, and dry/wet adhesive patches.

• Corrosion Science and Technology
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• 제3권3호
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• pp.118-126
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• 2004

The correlation between sensor output and corrosion rate of reinforcing steel was evaluated by laboratory electrochemical tests in saturated $Ca(OH)_2$ with 3.5 wt.% NaCl and confirmed in concrete environment. In this paper, two types of electrochemical probes were developed: galvanic cells containing of steel/copper and steel/stainless steel couples. Potentiodynamic test, weight loss measurement, monitoring of open-circuit potential, linear polarization resistance (LPR) measurement and electrochemical impedance spectroscopy (EIS) were used to evaluate the corrosion behavior of steel bar embedded in concrete. Also, galvanic current measurements were conducted to obtain the charge of sensor embedded in concrete. In this study, steel/copper and steel/stainless steel sensors showed a good correlation in simulated concrete solution between sensor output and corrosion rate of steel bar. However, there was no linear relationship between steel/stainless steel sensor output and corrosion rate of steel bar in concrete environment due to the low galvanic current output. Thus, steel/copper sensor is a reliable corrosion monitoring sensor system which can detect corrosion rate of reinforcing steel in concrete structures.

• 센서학회지
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• 제10권1호
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• pp.9-15
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• 2001

외인성 패브리-페롯 간섭계(EFPI) 광섬유 센서는 민감도와 분해능이 우수하며, 다른 종류의 광섬유 센서에 비해 많은 장점을 가지고 있다. 하지만 EFPI 광섬유 센서는 단지 프린지 개수만을 계산하여 측정량을 얻기 때문에 측정 방향을 구별하기 어렵다. 본 논문에서는 측정방향의 구분을 위한 추가적인 기능과 기존의 EFPI 광섬유 센서와는 다른 측정 시스템을 갖는 투과형 외인성 패브리-페롯 간섭계(TEFPI) 광섬유 센서를 개발하였다. 그리고 이를 이용하여 변형률 및 온도를 측정하였다.

• 센서학회지
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• 제32권6호
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• pp.378-385
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• 2023

Human biosignals provide essential information for diagnosing diseases such as dementia and Parkinson's disease. Owing to the shortcomings of current clinical assessments, noninvasive solutions are required. Machine learning (ML) on wearable sensor data is a promising method for the real-time monitoring and early detection of abnormalities. ML facilitates disease identification, severity measurement, and remote rehabilitation by providing continuous feedback. In the context of wearable sensor technology, ML involves training on observed data for tasks such as classification and regression with applications in clinical metrics. Although supervised ML presents challenges in clinical settings, unsupervised learning, which focuses on tasks such as cluster identification and anomaly detection, has emerged as a useful alternative. This review examines and discusses a variety of ML algorithms such as Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Neural Networks (NN), and Deep Learning for the analysis of complex clinical data.

• Journal of electromagnetic engineering and science
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• 제12권1호
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• pp.85-93
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• 2012

We propose a new expression of the near-field gain correction to calculate the on-axis far-field gain from the onaxis near-field gain for a directive antenna. The new expression is represented by transversal vectorial transmitting characteristics of two antennas that are measured by planar near-field equipment. Due to the advantages of the photonic sensor, the utilization of the new expression realizes the measurements of the on-axis far-field gains for two kinds of double ridged waveguide horn antennas within 0.1 dB deviation from 1 GHz to 6 GHz without calibrating the photonic sensor system.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 추계학술대회 논문집 Vol.15
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• pp.456-459
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• 2002

This paper describes fabrication and characteristics of ceramic pressure sensor for working at high temperature. The proposed pressure sensor consists of a Ta-N thin-film, patterned on a Wheatstone bridge configuration, sputter deposited onto thermally oxidized Si membranes with an aluminium interconnection layer. The fabricated pressure sensor presents a low temperature coefficient of resistance, high sensitivity, low non-linearity and excellent temperature stability. The sensitivity is 1.097~1.21mV/$V{\cdot}kgf/cm^2$ in the temperature range of $25{\sim}200^{\circ}C$ and the maximum non-linearity is 0.43 %FS.

• 제어로봇시스템학회논문지
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• 제1권1호
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• pp.43-49
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• 1995

본 논문에서는 초음파 센서와 시각 센서에서 얻은 전방향 센서 데이타를 이용하여 실내 이동 로봇용 국부 유도 항법을 위한 새로운 환경 모델링 방법을 제안한다. 그리고 이 두 종류의 센서 데이타에 포함된 불확실성을 주관적 지식과 퍼지 연산법을 사용하여 정량적으로 다룰 수 있는 센서 융합법을 제안한다. 이 방법을 사용하여, 로봇의 현재 위치와 목표 위치간의 기하학적 관계를 더욱 정확하게 얻을 수 있다. 실험 결과를 통하여 제안된 모델링과 센서 융합법이 실내 이동 로봇 항법에 효과적임을 보였다.

• 센서학회지
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• 제33권5호
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• pp.326-337
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• 2024

The thermal runaway phenomenon in lithium-ion batteries hinders their large-scale application and leads to safety issues, including smoke, fire, and explosion. Therefore, early warning systems must be employed rapidly and reliably to ensure user safety, with methods for detecting gases such as hydrogen, carbon monoxide, and hydrocarbons-all indicators of the thermal runaway process-considered a promising approach. In particular, metal-oxide-semiconductor-based gas sensors can be used to monitor target gases owing to their high response, fast response, and facile integration. In this paper, we review various strategies for enhancing the performance of metal-oxide-semiconductor-based gas sensors, including nanostructure design, catalyst loading, and composite design. Future perspectives on employing metal-oxide-semiconductor-based gas sensors to monitor thermal runaway in lithium-ion batteries are also discussed.

• International Journal of Aeronautical and Space Sciences
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• 제6권1호
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• pp.17-26
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• 2005

An optical phase tracking technique for an extrinsic Fabry-Perot interferometer (EFPI) is proposed in order to overcome interferometric non-linearity. Basic idea is utilizing strain-rate information, which cannot be easily obtained from an EFPI sensor itself. The proposed phase tracking system consists of a patch-type EFPI sensor and a simple on-line phase tracking logic. The patch-type EFPI sensor comprises an EFPI and a piezoelectric patch. An EFPI sensor itself has non-linear behavior due to the interferometric characteristics, and a piezoelectric material has hysteresis. However, the composed patch-type EFPI sensor system overcomes the problems that can arise when they are used individually. The dynamic characteristics of the proposed phase tracking system were investigated, and then the patch-type EFPI sensor system was applied to the active suppression of flutter, dynamic aeroelastic instability, of a swept-back composite plate structure. The proposed system has effectively reduced the amplitude of the flutter mode, and increased flutter speed.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.