• Structural Monitoring and Maintenance
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• 제7권2호
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• pp.109-124
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• 2020

Benefiting from the massive monitoring data collected by the Structural health monitoring (SHM) system, scholars can grasp the complex environmental effects and structural state during structure operation. However, the monitoring data is often missing due to sensor faults and other reasons. It is necessary to study the recovery method of missing monitoring data. Taking the structural temperature monitoring data of Nanjing Dashengguan Yangtze River Bridge as an example, the long short-term memory (LSTM) network-based recovery method for missing structural temperature data is proposed in this paper. Firstly, the prediction results of temperature data using LSTM network, support vector machine (SVM), and wavelet neural network (WNN) are compared to verify the accuracy advantage of LSTM network in predicting time series data (such as structural temperature). Secondly, the application of LSTM network in the recovery of missing structural temperature data is discussed in detail. The results show that: the LSTM network can effectively recover the missing structural temperature data; incorporating more intact sensor data as input will further improve the recovery effect of missing data; selecting the sensor data which has a higher correlation coefficient with the data we want to recover as the input can achieve higher accuracy.

• 대한원격탐사학회지
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• 제38권4호
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• pp.355-364
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• 2022

In this study a tendency of abnormal sea surface temperature (SST) occurrence in the seas around South Korea is analyzed from daily SST data from satellite and 14 buoys from August 2020 to July 2021. As thresholds 28℃ and 4℃ are used to determine marine heatwaves(MHWs) and abnormal low water temperature (ALWT), respectively, because those values are adopted by the National Institute of Fisheries Science for the breaking news of abnormal temperature. In order to calculate frequency of abnormal SST occurrence spatially by using satellite SST, research area was divided into six areas of coast and three open seas. ALWT dominantly appeared over a wide area (7,745 km²) in Gyeonggi Bay for total 94 days and it was also confirmed from buoy temperature showing an occurrence number of 47 days. MHWs tended to be high in frequency in the coastal areas of Chungcheongdo and Jeollabukdo and the south coastal areas while in case of buoy temperature Jupo was the place of high frequency (32 days). This difference was supposed to be due to the low accuracy of satellite SST at the coasts. MHWs are also dominant in offshore waters around Korean Peninsula. Although detecting abnormal SST by using satellite SST has advantage of understanding occurrence from a spatial point of view, we also need to perform detection using buoys to increase detection accuracy along the coast.

• 소성∙가공
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• 제26권2호
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• pp.101-107
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• 2017

Aluminum alloys are widely used in automotive industry because of their high strength-to-density ratio and excellent corrosion resistance. However, conventional cold stamping of aluminum alloys leads to low formability and excessive spring-back. To overcome these problems, Hot Forming Quenching (HFQ) is applied to manufacture automotive part using aluminum alloy. The purpose of this study is to investigate effect of forming temperature on spring-back in HFQ of T6 heat treated AA6061 sheet. In this study, hat shape forming test was adopted to evaluate spring-back characteristics according to various forming temperatures. In additions, the test was also performed with warm forming conditions in comparison with dimensional accuracy of HFQed part. The experimental results showed that dimensional accuracy of HFQed part was superior to warm formed part and amount of spring-back was decreased as forming temperature rise.

• 한국가스학회:학술대회논문집
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• 한국가스학회 2006년도 추계학술발표회 논문집
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• pp.123-128
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• 2006

This paper describes NDIR $CO_2$ gas sensor that shows the characteristics of temperature compensation. It consists of novel optical cavity that has two elliptical mirrors and a thermopile detector that includes ASIC chip in the same metal package for the amplification of detector output voltage and temperature sensor. The newly developed sensor modules shows high accuracy (less than +/-40 ppm) throughout the measuring concentration of $CO_2$ gas from 0 ppm to 2,000 ppm. After implementing the calculation methods of gas concentration, which is based upon the experimental results, the sensor module shows high accuracy less than +/- 5 ppm error throughout the measuring temperature range $(15^{\circ}C\;to\; 35^{\circ}C)$ and gas concentrations.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.387-390
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• 2001

Thermopile thermometer can measure the temperature of an object without attaching the object. It measures the temperature by receiving the radiation energy from objects. The idea of this is from the law of Stefan-Boltzmann. In the past it was not used well because the size was big and the cost was too expensive. But, In these days it can be used many field because the size become smaller and advantage of cost by using micro machine technology. However, The accuracy of measuring is not better than electric type. So we want to improve the accuracy of sensor by analyzing the heat transfer of the thermopile. To analyze temperature distribution in the thermopile sensor, we use the FEM software which is named ANSYS. The conduction and radiation heat transfer is considered to simulate the temperature distribution and time response inside of the sensor.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.141-143
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• 2013

현재 나와 있는 휴대용 방사선 검출장치들은 기능적으로 제약이 크다. 이러한 단점을 해결하고자 안드로이드 플랫폼 기반의 휴대용 방사선 검출장치에 관한 연구가 이루어졌다. 연구초기 단계인 만큼 방사선 측정은 가능하지만, 정확도가 나와 있는 제품들만큼 높지 못하다. 이러한 안드로이드 플랫폼 기반의 휴대용 방사선 검출장치는 온도에 따라 오차가 발생하게 된다. 이와 같은 온도에 따른 오차를 제거하기 위해 온도에 따른 보상 알고리즘을 구현하여 정확도를 향상하고자 한다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 추계학술발표회 논문집
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• pp.47-53
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• 2004

Water vapor is an important parameter in monitoring changes in the Earth's climate and it can be used to improve weather forecasting However, it haven't observed accurately by reasons of structural and economic problem of observation. GPS meteorology technique for precipitable water vapor measurement is currently actively being researched an advanced nation. Main issue of GPS meteorology is an accuracy of PWV measurement related weighted mean temperature and meteorological data. In this study, the korean weighted mean temperature had been recalculated by a linear regression method based on meteorological observations from 6 radiosonde stations for 2003 year. We examined the accuracy of PWV estimates from GPS observations and Radiosonde observations by new korean weighted mean temperature and others.

• 한국측량학회지
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• 제30권6_2호
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• pp.615-622
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• 2012

Since the accuracy of precipitable/integrated water vapor estimates from GNSS measurements is proportional to the accuracy of water vapor Weighted Mean Temperature Model (WMTM), the WMTM is a significant formulation in the retrieval of precipitable water vapor from zenith wet delay of GNSS signal. The purpose of this paper is to develop available the WMTM to apply for GNSS meteorology in the region of Algeria, by using the Algerian radiosonde network in the World Meteorological Organization (WMO). It can be concluded that the available GNSS precipitable water vapor which is retrieved by the developed Algerian Weighted Mean Temperature Equation (AWMTE) can be useful technique for sensing of water vapor in the Algeria, after Algerian Continuously Operating Reference System (CORS) will be constructed.

• Steel and Composite Structures
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• 제12권2호
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• pp.129-147
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• 2012

In this paper, the thermal buckling analysis of rectangular composite laminated plates is investigated using the Differential Quadrature (DQ) method. The composite plate is subjected to a uniform temperature distribution and arbitrary boundary conditions. The analysis takes place in two stages. First, pre-buckling forces due to a temperature rise are determined by using a membrane solution. In the second stage, the critical temperature is predicted based on the first-order shear deformation theory. To verify the accuracy of the method, several case studies were used and the numerical results were compared with those of other published literatures. Moreover, the effects of several parameters such as aspect ratio, fiber orientation, modulus ratio, and various boundary conditions on the critical temperature were examined. The results confirm the efficiency and accuracy of the DQ method in dealing with this class of engineering problems.

• Nuclear Engineering and Technology
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• 제53권8호
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• pp.2610-2615
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• 2021

The prediction of irradiation-induced transition temperature shift for RPV steels is an important method for long term operation of nuclear power plant. Based on the irradiation embrittlement data, an irradiation-induced transition temperature shift prediction model is developed with machine learning method XGBoost. Then the residual, standard deviation and predicted value vs. measured value analysis are conducted to analyze the accuracy of this model. At last, Cu content threshold and saturation values analysis, temperature dependence, Ni/Cu dependence and flux effect are given to verify the reliability. Those results show that the prediction model developed with XGBoost has high accuracy for predicting the irradiation embrittlement trend of RPV steel. The prediction results are consistent with the current understanding of RPV embrittlement mechanism.