• 제목/요약/키워드: Sensor Validation

검색결과 243건 처리시간 0.025초

수중 영상 소나의 번들 조정과 3차원 복원을 위한 운동 추정의 모호성에 관한 연구 (Bundle Adjustment and 3D Reconstruction Method for Underwater Sonar Image)

  • 신영식;이영준;최현택;김아영
    • 로봇학회논문지
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    • 제11권2호
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    • pp.51-59
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    • 2016
  • In this paper we present (1) analysis of imaging sonar measurement for two-view relative pose estimation of an autonomous vehicle and (2) bundle adjustment and 3D reconstruction method using imaging sonar. Sonar has been a popular sensor for underwater application due to its robustness to water turbidity and visibility in water medium. While vision based motion estimation has been applied to many ground vehicles for motion estimation and 3D reconstruction, imaging sonar addresses challenges in relative sensor frame motion. We focus on the fact that the sonar measurement inherently poses ambiguity in its measurement. This paper illustrates the source of the ambiguity in sonar measurements and summarizes assumptions for sonar based robot navigation. For validation, we synthetically generated underwater seafloor with varying complexity to analyze the error in the motion estimation.

Deep-learning-based system-scale diagnosis of a nuclear power plant with multiple infrared cameras

  • Ik Jae Jin;Do Yeong Lim;In Cheol Bang
    • Nuclear Engineering and Technology
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    • 제55권2호
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    • pp.493-505
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    • 2023
  • Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

Parametric study on multichannel analysis of surface waves-based nondestructive debonding detection for steel-concrete composite structures

  • Hongbing Chen;Shiyu Gan;Yuanyuan Li;Jiajin Zeng;Xin Nie
    • Steel and Composite Structures
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    • 제50권1호
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    • pp.89-105
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    • 2024
  • Multichannel analysis of surface waves (MASW) method has exhibited broad application prospects in the nondestructive detection of interfacial debonding in steel-concrete composite structures (SCCS). However, due to the structural diversity of SCCS and the high stealthiness of interfacial debonding defects, the feasibility of MASW method needs to be investigated in depth. In this study, synthetic parametric study on MASW nondestructive debonding detection for SCCSs is performed. The aim is to quantitatively analyze influential factors with respect to structural composition of SCCS and MASW measurement mode. First, stress wave composition and propagation process in SCCS are studied utilizing 2D numerical simulation. For structural composition in SCCS, the thickness variation of steel plate, concrete core, and debonding defects are discussed. To determine the most appropriate sensor arrangement for MASW measurement, the effects of spacing and number of observation points, along with distances between excitation points, nearest boundary, as well as the first observation point, are analyzed individually. The influence of signal type and frequency of transient excitation on dispersion figures from forwarding analysis is studied to determine the most suitable excitation signal. The findings from this study can provide important theoretical guidance for MASW-based interfacial debonding detection for SCCS. Furthermore, they can be instrumental in optimizing both the sensor layout design and signal choice for experimental validation.

UAV 기반 열적외선 센서를 이용한 태양광 셀의 발열 검출 (The Detection of Heat Emission to Solar Cell using UAV-based Thermal Infrared Sensor)

  • 이근상;이종조
    • 대한공간정보학회지
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    • 제25권1호
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    • pp.71-78
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    • 2017
  • 최근 널리 보급되고 있는 태양광 발전소의 유지관리를 위해 다양한 연구들이 시도되고 있다. 본 연구에서는 unmanned aerial vehicle(UAV)기반 열적외선 센서를 이용하여 태양광 셀의 발열을 분석하는 것으로서 주요 결론은 다음과 같다. 먼저 UAV 기반 RGB 센서를 이용하여 정사영상과 digital surface model(DSM) 자료를 구축하였으며, 이를 통해 태양광 셀의 발열 분석에 필요한 태양광 모듈 레이어를 생성하였다. 또한 태양광 모듈 레이어의 위치정확도를 평가하기 위해 virtual reference service(VRS) 측량을 이용하여 검정점에 대한 수평오차를 분석한 결과, 표준오차가 $dx={\pm}2.4cm$, $dy={\pm}3.2cm$로 높은 위치정확도를 확보할 수 있었다. 그리고 태양광 셀의 발열 실험을 위해 고무패치를 설치한 후 UAV 열적외선 센서를 이용하여 발열이 생기는 고무패치의 위치를 효과적으로 분석할 수 있었다. 또한 고무패치 셀 비율과 UAV 열적외선 센서에 의한 셀 비율의 표준오차는 ${\pm}3.5%$로 나타났으며, 따라서 UAV 기반 열적외선 센서를 이용하여 태양광 셀의 발열을 효과적으로 분석할 수 있었다. 아울러 발열이 생기는 셀이 위치하고 있는 태양광 모듈의 코드를 자동으로 추출함으로서 효과적인 태양광발전소 유지보수가 가능하게 되었다.

SHM benchmark for high-rise structures: a reduced-order finite element model and field measurement data

  • Ni, Y.Q.;Xia, Y.;Lin, W.;Chen, W.H.;Ko, J.M.
    • Smart Structures and Systems
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    • 제10권4_5호
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    • pp.411-426
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    • 2012
  • The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of over 700 sensors of sixteen types. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), an SHM benchmark problem for high-rise structures has been developed by taking the instrumented Canton Tower as a host structure. This benchmark problem aims to provide an international platform for direct comparison of various SHM-related methodologies and algorithms with the use of real-world monitoring data from a large-scale structure, and to narrow the gap that currently exists between the research and the practice of SHM. This paper first briefs the SHM system deployed on the Canton Tower, and the development of an elaborate three-dimensional (3D) full-scale finite element model (FEM) and the validation of the model using the measured modal data of the structure. In succession comes the formulation of an equivalent reduced-order FEM which is developed specifically for the benchmark study. The reduced-order FEM, which comprises 37 beam elements and a total of 185 degrees-of-freedom (DOFs), has been elaborately tuned to coincide well with the full-scale FEM in terms of both modal frequencies and mode shapes. The field measurement data (including those obtained from 20 accelerometers, one anemometer and one temperature sensor) from the Canton Tower, which are available for the benchmark study, are subsequently presented together with a description of the sensor deployment locations and the sensor specifications.

수박 내부결함판정을 위한 휴대형 압전형 장갑 센서시스템 (Portable Piezoelectric Film-based Glove Sensor System for Detecting Internal Defects of Watermelon)

  • 최동수;이영희;최승렬;김학진;박종민
    • Journal of Biosystems Engineering
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    • 제33권1호
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    • pp.30-37
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    • 2008
  • Dynamic excitation and response analysis is an acceptable method to determine some of physical properties of agricultural product for quality evaluation. There is a difference in the internal viscoelasticity between sound and defective fruits due to the difference of geometric structures, thereby showing different vibration characteristics. This study was carried out to develop a portable piezoelectric film-based glove sensor system that can separate internally damaged watermelons from sound ones using an acoustic impulse response technique. Two piezoelectric sensors based on polyvinylidene fluoride (PVDF) films to measure an impact force and vibration response were separately mounted on each glove. Various signal parameters including number of peaks, energy ratio, standard deviation of peak to peak distance, zero-crossing rate, and integral value of peaks were examined to develop a regression-estimated model. When using SMLR (Stepwise Multiple Linear Regression) analysis in SAS, three parameters, i.e., zeros value, number of peaks, and standard deviation of peaks were selected as usable factors with a coefficient of determination ($r^2$) of 0.92 and a standard error of calibration (SEC) of 0.15. In the validation tests using twenty watermelon samples (sound 9, defective 11), the developed model provided good capability showing a classification accuracy of 95%.

An Accurate Radio Channel Model for Wireless Sensor Networks Simulation

  • Alejandro Martfnez-Sala;Jose-Maria Molina-Garcia-Pardo;Esteban Egea-Lopez;Javier Vales-Alonso;Leandro Juan-Llacer;Joan Garcia-Haro
    • Journal of Communications and Networks
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    • 제7권4호
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    • pp.401-407
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    • 2005
  • Simulations are currently an essential tool to develop and test wireless sensor networks (WSNs) protocols and to analyze future WSNs applications performance. Researchers often simulate their proposals rather than deploying high-cost test-beds or develop complex mathematical analysis. However, simulation results rely on physical layer assumptions, which are not usually accurate enough to capture the real behavior of a WSN. Such an issue can lead to mistaken or questionable results. Besides, most of the envisioned applications for WSNs consider the nodes to be at the ground level. However, there is a lack of radio propagation characterization and validation by measurements with nodes at ground level for actual sensor hardware. In this paper, we propose to use a low-computational cost, two slope, log-normal path­loss near ground outdoor channel model at 868 MHz in WSN simulations. The model is validated by extensive real hardware measurements obtained in different scenarios. In addition, accurate model parameters are provided. This model is compared with the well-known one slope path-loss model. We demonstrate that the two slope log-normal model provides more accurate WSN simulations at almost the same computational cost as the single slope one. It is also shown that the radio propagation characterization heavily depends on the adjusted model parameters for a target deployment scenario: The model parameters have a considerable impact on the average number of neighbors and on the network connectivity.

2축 아날로그 태양센서 극성시험장치 개발 및 검증 (The Development and Validation of BASS(Bi-axis Analogue Sun Sensor) Stimuli Equipment for FM Polarity Test)

  • 박영웅;이상섭
    • 한국항공우주학회지
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    • 제45권7호
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    • pp.594-599
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    • 2017
  • 본 논문에서는 GK2 위성의 최종 조립시험단계의 극성시험 과정에서 태양센서에 전기자극을 주어 자세오차를 다양하게 모사하는 지상시험장치(Test-aid)의 개발과 검증에 관한 내용을 정리한다. 본 논문에서 GK2 위성에 사용되는 태양센서 Test-aid는 2축 아날로그 태양센서를 대상으로 시험하는 것으로 고장으로 인한 백업을 고려하여 Test-aid의 국산화를 진행하였다. 또한, 시험을 통해 천리안위성에 사용되었던 Test-aid 특성과 국내업체를 통해 제작된 Test-aid의 특성이 기존 장비를 대체할 수 있음을 확인하였다. 본 논문에서 소개하는 국내 제작된 Test-aid는 기존의 천리안위성에 사용되었던 Test-aid와 달리 차이점이 생길시 제어기의 튜닝 기능을 이용하여 기존장비와 동일한 성능을 구사할 수 있음을 보였다.

SeaWiFS 밴드역에 의한 연안해역의 엽록소 밴드비율 알고리듬 검증 (The Validation of chlorophyll-a band ratio algorithm of coastal area using SeaWiFS wavelength)

  • 정종철;유신재
    • 대한원격탐사학회지
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    • 제16권1호
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    • pp.37-45
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    • 2000
  • 해양관측위성으로 1997년에 발사된 SeaWiFS 센서는 해양의 엽록소 분포와 대기환경 등 다양한 지구관측 자료를 제공하고 있고, 현재까지 수신된 많은 자료는 해양뿐만 아니라 육상관측에도 이용되고 있다. 하지만, SeaWIFS 센서는 1 km의 공간해상력으로 인해 연안해역의 관측이 어렵고, 연안역에서의 대기보정 문제가 아직 정립되지 않아 연안해역의 관측에는 아직 활발히 적용되지못하다. 특히, 서.남해 연안해역은 부유사 농도가 높고, 육상에서 비롯되는 용존유기물의 흡광으로 엽록소 분포를 분석하기에 적합한 알고리듬이 개발되지 못하고 있는 실정이다. 본 연구에서는 해양의 엽록소 농도분포를 분석하는데 활용되어온 경험적인 알고리듬을 바탕으로 연안해역의 엽록소 분포를 분석하기에 적합한 경험식을 도출하였으며, 이러한 경험식을 도출하는 과정에서 연안해역의 엽록소 농도 관측을 위해서는 레드영역의 밴드 (665nm)가 활용되어야 한다는 결론을 얻었다.

Autonomous evaluation of ambient vibration of underground spaces induced by adjacent subway trains using high-sensitivity wireless smart sensors

  • Sun, Ke;Zhang, Wei;Ding, Huaping;Kim, Robin E.;Spencer, Billie F. Jr.
    • Smart Structures and Systems
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    • 제19권1호
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    • pp.1-10
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    • 2017
  • The operation of subway trains induces secondary structure-borne vibrations in the nearby underground spaces. The vibration, along with the associated noise, can cause annoyance and adverse physical, physiological, and psychological effects on humans in dense urban environments. Traditional tethered instruments restrict the rapid measurement and assessment on such vibration effect. This paper presents a novel approach for Wireless Smart Sensor (WSS)-based autonomous evaluation system for the subway train-induced vibrations. The system was implemented on a MEMSIC's Imote2 platform, using a SHM-H high-sensitivity accelerometer board stacked on top. A new embedded application VibrationLevelCalculation, which determines the International Organization for Standardization defined weighted acceleration level, was added into the Illinois Structural Health Monitoring Project Service Toolsuite. The system was verified in a large underground space, where a nearby subway station is a good source of ground excitation caused by the running subway trains. Using an on-board processor, each sensor calculated the distribution of vibration levels within the testing zone, and sent the distribution of vibration level by radio to display it on the central server. Also, the raw time-histories and frequency spectrum were retrieved from the WSS leaf nodes. Subsequently, spectral vibration levels in the one-third octave band, characterizing the vibrating influence of different frequency components on human bodies, was also calculated from each sensor node. Experimental validation demonstrates that the proposed system is efficient for autonomously evaluating the subway train-induced ambient vibration of underground spaces, and the system holds the potential of greatly reducing the laboring of dynamic field testing.