• 제목/요약/키워드: Time-series monitoring

검색결과 505건 처리시간 0.027초

A study on analysis to time series data by using vegetation surface roughness index

  • Konda, Asako;Kajiwara, Koji;Honda, Yoshiaki
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.706-708
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    • 2003
  • Index for difference of vegetation surface roughness (BSI: Bi-directional reflectance factor structure Index) was proposed in our laboratory (Konda et al., 2000). It is thought that BSI is useful vegetation index for vegetation monitoring. If it can be applied for global covered satellite data, detailed monitoring of global vegetation can be expected. However, in order to apply BSI to global satellite data, there are some problems to be solved. In this study, in order to make global data set of BSI, it arranged about processing of the global satellite data for making BSI data sets.

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Damage assessment of shear-type structures under varying mass effects

  • Do, Ngoan T.;Mei, Qipei;Gul, Mustafa
    • Structural Monitoring and Maintenance
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    • 제6권3호
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    • pp.237-254
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    • 2019
  • This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

태양광발전 단기예측모델 개발 (The Development of the Short-Term Predict Model for Solar Power Generation)

  • 김광득
    • 한국태양에너지학회 논문집
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    • 제33권6호
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    • pp.62-69
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    • 2013
  • In this paper, Korea Institute of Energy Research, building integrated renewable energy monitoring system that utilizes solar power generation forecast data forecast model is proposed. Renewable energy integration of real-time monitoring system based on monitoring data were building a database and the database of the weather conditions and to study the correlation structure was tailoring. The weather forecast cloud cover data, generation data, and solar radiation data, a data mining and time series analysis using the method developed models to forecast solar power. The development of solar power in order to forecast model of weather forecast data it is important to secure. To this end, in three hours, including a three-day forecast today Meteorological data were used from the KMA(korea Meteorological Administration) site offers. In order to verify the accuracy of the predicted solar circle for each prediction and the actual environment can be applied to generation and were analyzed.

TFNM, ANN, ANFIS를 이용한 국가지하수관측망 지하수위 변동 예측 비교 연구 (A Comparative Study on Forecasting Groundwater Level Fluctuations of National Groundwater Monitoring Networks using TFNM, ANN, and ANFIS)

  • 윤필선;윤희성;김용철;김규범
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제19권3호
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    • pp.123-133
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    • 2014
  • It is important to predict the groundwater level fluctuation for effective management of groundwater monitoring system and groundwater resources. In the present study, three different time series models for the prediction of groundwater level in response to rainfall were built, those are transfer function noise model (TFNM), artificial neural network (ANN), and adaptive neuro fuzzy interference system (ANFIS). The models were applied to time series data of Boen, Cheolsan, and Hongcheon stations in National Groundwater Monitoring Network. The result shows that the model performance of ANN and ANFIS was higher than that of TFNM for the present case study. As lead time increased, prediction accuracy decreased with underestimation of peak values. The performance of the three models at Boen station was worst especially for TFNM, where the correlation between rainfall and groundwater data was lowest and the groundwater extraction is expected on account of agricultural activities. The sensitivity analysis for the input structure showed that ANFIS was most sensitive to input data combinations. It is expected that the time series model approach and results of the present study are meaningful and useful for the effective management of monitoring stations and groundwater resources.

Zigbee 무선통신을 이용한 UPS DC링크 커패시터의 고장 모니터링 시스템 개발 (A development of Diagnosis Monitoring System for UPS DC Link Capacitors using Zigbee Wireless Communication)

  • 김동준;손진근;전희종
    • 전기학회논문지P
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    • 제61권1호
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    • pp.41-46
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    • 2012
  • Electrolytic power capacitors have been widely used in power conversion system such as inverter or UPS because of characteristics of large capacitance, high-voltage and low-cost. The electrolytic capacitor, which is most of the time affected by the aging effect, plays a very important role for the power-electronics system quality and reliability. Therefore it is important to diagnosis monitoring the condition of an electrolytic capacitor in real-time to predict the failure. In this paper, the on-line remote diagnosis monitoring system for UPS DC link electrolytic capacitors using low-cost single-chip zigbee communication modules is developed. To estimate the health status of the capacitor, the equivalent series resistor(ESR) of the component has to be determined. The capacitor ESR is estimated by using RMS computation using BPF modeling of DC link ripple voltage/current. Zigbee-based hardware experimental results show that the proposed remote capacitor diagnosis monitoring system can be applied to UPS successfully.

지표면 식생 변화 감시를 위한 NDVI 영상자료 시계열 시리즈의 적응 재구축 (Adaptive Reconstruction of NDVI Image Time Series for Monitoring Vegetation Changes)

  • 이상훈
    • 대한원격탐사학회지
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    • 제25권2호
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    • pp.95-105
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    • 2009
  • 지상 관측으로부터 수집된 시계열 원격탐사 자료는 관측환경의 악화와 감지 시스템의 기계적 고장과 같은 관측 장애요인에 의해 많은 미관측 및 악성 자료를 가지게 된다. 육상의 지표면 parameters는 기후와 주로 연관되어 있으므로 육상 관측 위성 영상에 나타나는 많은 물리적 과정은 계절 주기에 따른 시간적 변화를 보인다. 본 연구에서 제안된 적응 feedback 시스템은 계절에 따라 변하는 물리적 과정을 포함하는 시계열 원격 탐사 영상 시리즈를 재구축한다. 이 시스템에서는 계절적 변화를 추적하기 위하여 하모닉 모형을 사용하고 수치 영상 모형의 공간적 의존성을 나타내기 위해 Gibbs Random Field를 사용한다. 재구축 과정을 통하여 구성된 적응 하모닉 모형을 사용하여 지표면 연속적 변화를 감시할 수 있다. 본 연구에서는 1996년부터 2000년까지 한반도로부터 관측된 AVHRR 영상 시리즈를 일 주일 간격으로 정적 합성하여 NDVI 시리즈를 구하고 하모닉 모형을 사용하는 적응 재구축 시스템을 이 NDVI 시리즈에 적용하여 한반도 식생 변화를 추적하였다. 연구 결과는 하모닉 적응 재구축 시스템이 실시간 지표면 변화 감시를 하는데 매우 효과적인 수단이 될 것이라는 잠재성을 보여준다.

ARIMA 모델을 이용한 수막재배지역 지하수위 시계열 분석 및 미래추세 예측 (Time-series Analysis and Prediction of Future Trends of Groundwater Level in Water Curtain Cultivation Areas Using the ARIMA Model)

  • 백미경;김상민
    • 한국농공학회논문집
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    • 제65권2호
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    • pp.1-11
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    • 2023
  • This study analyzed the impact of greenhouse cultivation area and groundwater level changes due to the water curtain cultivation in the greenhouse complexes. The groundwater observation data in the Miryang study area were used and classified into greenhouse and field cultivation areas to compare the groundwater impact of water curtain cultivation in the greenhouse complex. We identified the characteristics of the groundwater time series data by the terrain of the study area and selected the optimal model through time series analysis. We analyzed the time series data for each terrain's two representative groundwater observation wells. The Seasonal ARIMA model was chosen as the optimal model for riverside well, and for plain and mountain well, the ARIMA model and Seasonal ARIMA model were selected as the optimal model. A suitable prediction model is not limited to one model due to a change in a groundwater level fluctuation pattern caused by a surrounding environment change but may change over time. Therefore, it is necessary to periodically check and revise the optimal model rather than continuously applying one selected ARIMA model. Groundwater forecasting results through time series analysis can be used for sustainable groundwater resource management.

다중 시계열 패턴인식을 이용한 반도체 생산장치의 지능형 감시시스템 (An Intelligent Monitoring System of Semiconductor Processing Equipment using Multiple Time-Series Pattern Recognition)

  • 이중재;권오범;김계영
    • 정보처리학회논문지D
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    • 제11D권3호
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    • pp.709-716
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    • 2004
  • 본 논문에서는 다중 시계열 패턴인식 사용하여 생산장치의 상태자료부터 공정결과를 예측하여 정상 또는 비정상을 판정하는 지능형 감시시스템에 관하여 기술한다. 제안하는 감시스템은 초기화, 학습 그리고 인식의 세 단계로 구성된다. 초기화 단계에서는 감시대상의 생산장치가 가지는 인사들 각각의 가중치와 각 인자들이 가지는 시계열 자료 중에서 학습과 인식에 유효단계를 설정한다. 학습단계에서는 LBG알고리즘을 사용하여 이 생산장치에 의하여 생성되고 수집된 패턴들을 군집화 한다. 각 패턴은 시계열 형태의 자료와 처리 완료 후 계측기에 의하여 측정된 ACI로 구성된다. 인식단계에서는 DTW를 사용하여 실시간으로 입력된 패턴과 군집화된 패턴들 사이의 대응을 수행하여 가장 잘 정합되는 패턴을 찾는다. 다음은 이 패턴이 가지는 ACI, 차 그리고 가중치들의 조합으로 예측된 ACI 값을 산출한다. 최종적으로 예측된 ACI가 정상으로 수용할 수 있는 값 범위에 없는지 여부를 결정한다. 제안하는 시스템의 성능평가를 위하여 식각장치로부터 획득된 자료를 대상으로 실험하였다. 실험결과에서는 학습횟수가 증가함에 따라 예측 ACI값과 실측ACI값 사이의 오차가 현저히 감소함을 볼 수 있다

시계열 간섭 모형을 이용한 불법 오물 투기 실시간 탐지 알고리즘 연구 (Real time detection algorithm against illegal waste dumping into river based on time series intervention model)

  • 문지은;송규문;김태윤
    • Journal of the Korean Data and Information Science Society
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    • 제21권5호
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    • pp.883-890
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    • 2010
  • 수질오염의 요인인 불법 오물 투기는 사회적 이슈로 대두되고 있고 관련 감독기관이 해결해야 할 문제들 중의 하나이다. 따라서 불법 오물 투기를 막는 체계적인 관리, 감독이 시급한 상황이다. 이를 위해 최근 들어 관련기관들은 실시간으로 연속적으로 수질의 상태를 감지 할 수 있는 자동측정기를 하천에 설치하고 있다. 본 논문에서는 수질 자동측정기로부터 발생하는 실시간 데이터를 감시하여 이상점을 탐지하게 하는 수질 감시 알고리즘을 제안한다. 특히 수질 자동 측정기로서 흔히 사용되는 화학적 산소요구량 자동측정 장치기를 위한 수질 감시 알고리즘을 개발한다. 본 논문의 수질 감시 알고리즘은 기본적으로 시계열 간섭모형을 활용한다.

Usability of inclinometers as a complementary measurement tool in structural monitoring

  • Pehlivan, Huseyin;Bayata, Halim Ferit
    • Structural Engineering and Mechanics
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    • 제58권6호
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    • pp.1077-1085
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    • 2016
  • In the last few years, many structural monitoring studies have been performed using different techniques to measure structures of different scales such as buildings, dams or bridges. One of the mostly used tools are GPS instruments, which have been utilized in various combinations with accelerometers and some other conventional sensors. In the current study, observation series were recorded for 8 hours with GPS receivers (NovAtel) and Inclination Measurement Sensors mounted on a television tower in Istanbul, Turkey. Each series of observations collected from two different sensors were transformed into a single coordinate system (Local Topocentric Coordinates System). The positional changes of the tower were calculated from the GPS and the inclination data. These changes were plotted in two dimensions (2D) on the same graphic. Thus, the possibility of comparison and analysis were found using the data from both the GPS and the Inclinometer complement each other, in the real test area. The positional changes of the tower were modeled for further examination. As a result, the movement of the tower within an area of $1{\times}1cm^2$ was observed. Based on the results, it can be concluded that inclinometers can be used for monitoring the structural behavior of the tower.