• 전자공학회논문지T
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• 제36T권1호
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• pp.86-92
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• 1999

본 논문에서는 수분센서용으로 적합한 구조의 안테나로 소형의 개 루우프 안테나를 모델로 제시하고, 그 동작특성을 모멘트 법을 이용하여 수치해석 하였다. 수치해석의 결과, 동작 주파수 300MHz ∼ 500MHz의 대역에서 안테나의 파리미터 값을 변화시킴으로써 입력 임피던스는 50Ω으로 정합시킬 수 있으며, 이득은 약 2.5㏈d 정도로 나타났다. 또한, 이 안테나는 동작 주파수에서 협대역 공진특성을 보이고, 안테나의 중심 축 상으로 균일분포의 복사패턴을 보였다. 따라서 본 논문에서 제시된 안테나 모델은 수분센서용 안테나로서 적합한 구조와 동작특성을 갖는다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 가을 학술논문 발표대회
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• pp.8-9
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• 2021

The unit-water content of concrete is one of the important factors in determining the quality of concrete and is directly related to the durability of the construction structure, and the current method of measuring the unit-water content of concrete is applied by the Air Meta Act and the Electrostatic Capacity Act. However, there are complex and time-consuming problems with measurement methods. Therefore, high frequency moisture sensor was used for quick and high measurement, and unit-water content of mortar was evaluated through machine running and deep running based on measurement big data. The multi-input deep learning model is as accurate as 24.25% higher than the OLS linear regression model, which shows that deep learning can more effectively identify the nonlinear relationship between high-frequency moisture sensor data and unit quantity than linear regression.

• Journal of the Korean Wood Science and Technology
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• 제48권6호
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• pp.917-935
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• 2020

본 연구는 산불의 발생과 확산위험성의 지표인 산불연료의 수분함량과 산불위험도의 변화를 예측하기 위한 산불연료습도 자동화 측정센서를 개발하였다. 이 측정센서는 산불연료의 함수율을 전기저항으로 측정하여 자동으로 산불연료의 함수율을 산정하는 방법이다. 이 센서에 사용된 산불연료는 소나무(길이 50cm, 직경 1.5cm)이고, 함수율과 전기저항과의 관계를 추정하는 전기저항=2E(E:Exponent of 10)+13X(X:함수율)-9.705(R²=0.947)인 환산식을 개발하였다. 또한, 이를 이용하여 자동화된 산불연료습도 자동화 측정센서의 소프트웨어와 함체를 설계하여 시제품을 제작하였고, 이를 다시 산림 내에서 현장 모니터링 검증을 실시하여 적합성(R²=0.824)을 확인하였다. 본 연구결과는 산불의 발생, 확산과 강도를 예측할 수 있는 기술의 개발에 도움을 주며, 산불위험예보 기술의 고도화를 위한 기초자료로 활용될 것으로 기대된다.

• 대한원격탐사학회지
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• 제23권1호
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• pp.21-32
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• 2007

Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. However, fuel mapping is extremely difficult because fuel properties vary at spatial scales, change depending on the seasonal situations and are affected by the surrounding environment. Remote sensing has potential to reduce the uncertainty in mapping fuels and offers the best approach for improving our abilities. Especially, Hyperspectral sensor have a great potential for mapping vegetation properties because of their high spectral resolution. The objective of this paper is to evaluate the potential of mapping fuel properties using Hyperion hyperspectral remote sensing data acquired in April, 2002. Fuel properties are divided into four broad categories: 1) fuel moisture, 2) fuel green live biomass, 3) fuel condition and 4) fuel types. Fuel moisture and fuel green biomass were assessed using canopy moisture, derived from the expression of liquid water in the reflectance spectrum of plants. Fuel condition was assessed using endmember fractions from spectral mixture analysis (SMA). Fuel types were classified by fuel models based on the results of SMA. Although Hyperion imagery included a lot of sensor noise and poor performance in liquid water band, the overall results showed that Hyperion imagery have good potential for wildfire fuel mapping.

• Journal of Biosystems Engineering
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• 제43권4호
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• pp.426-439
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• 2018

Purpose: To continuously monitor soil and climatic properties, a data acquisition system (DAQ) was developed and tested in plum farms (Gyewol-ri and Haechang-ri, Suncheon, Korea). Methods: The DAQ consisted of a Raspberry-Pi processor, a modem, and an ADC board with multiple sensors (soil moisture content (SEN0193), soil temperature (DS18B20), climatic temperature and humidity (DHT22), and rainfall gauge (TR-525M)). In the laboratory, various tests were conducted to calibrate SEN0193 at different soil moistures, soil temperatures, depths, and bulk densities. For performance comparison of the SEN0193 sensor, two commercial moisture sensors (SMS-BTA and WT-1000B) were tested in the field. The collected field data in Raspberry-Pi were transmitted and stored on a web server database through a commercial communications wireless network. Results: In laboratory tests, it was found that the SEN0193 sensor voltage reading increased significantly with an increase in soil bulk density. A linear calibration equation was developed between voltage and soil moisture content depending on the farm soil bulk density. In field tests, the SEN0193 sensor showed linearity (R = 0.76 and 0.73) between output voltage and moisture content; however, the other two sensors showed no linearity, indicating that site-specific calibration is important for accurate sensing. In the long-term monitoring results, it was observed that the measured climate temperature was almost the same as website information. Soil temperature information was higher than the values measured by DS18B20 during spring and summer. However, the local rainfall measured using TR 525M was significantly different from the values on the website. Conclusion: Based on the test results obtained using the developed monitoring system, it is thought that the measurement of various parameters using one device would be helpful in monitoring plum growth. Field data from the local farm monitoring system can be coupled with website information from the weather station and used more efficiently.

• Water Engineering Research
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• 제3권1호
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• pp.31-44
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• 2002

The effect of diurnal cycle, intermittent visit of observation satellite, sensor installation, partial coverage of remote sensing, heterogeneity of soil properties and precipitation to the soil moisture estimation error were analyzed to present the global sampling strategy of soil moisture. Three models, the theoretical soil moisture model, WGR model proposed Waymire of at. (1984) to generate rainfall, and Turning Band Method to generate two dimensional soil porosity, active soil depth and loss coefficient field were used to construct sufficient two-dimensional soil moisture data based on different scenarios. The sampling error is dominated by sampling interval and design scheme. The effect of heterogeneity of soil properties and rainfall to sampling error is smaller than that of temporal gap and spatial gap. Selecting a small sampling interval can dramatically reduce the sampling error generated by other factors such as heterogeneity of rainfall, soil properties, topography, and climatic conditions. If the annual mean of coverage portion is about 90%, the effect of partial coverage to sampling error can be disregarded. The water retention capacity of fields is very important in the sampling error. The smaller the water retention capacity of the field (small soil porosity and thin active soil depth), the greater the sampling error. These results indicate that the sampling error is very sensitive to water retention capacity. Block random installation gets more accurate data than random installation of soil moisture gages. The Walnut Gulch soil moisture data show that the diurnal variation of soil moisture causes sampling error between 1 and 4 % in daily estimation.

• 패션비즈니스
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• 제15권6호
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• pp.40-55
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• 2011

The purpose of this research is to review testing principle, testing design and experimental results of the four dynamic moisture movement testers. The research analyzes Moisture Manager Tester (MMT), Alambeta Instrument, Dynamic Surface Moisture Movement Tester, and Gravimetric Absorbent Testing Method based on American Society for Testing and Material (ASTM) E 96 which is an international standard testing method. Although many of researches use ASTM E 96 to measure moisture movement on a fabric, it has several weaknesses, such as long experimental time and a physical change of sample by a holder of the frame. Hence, lots of researchers have studied and developed the new measurement systems measuring moisture management on a fabric or garment and ultimately mimic heat energy and perspiration created by the human body. These moisture management systems use a variety of parameters, such as electricity, color, and sensor to measure their movement in the fabric. Through comparison with the existing tester (ASTM E 96), the research recognizes the strength and weakness in the dynamic moisture movement testers.

• 한국자원식물학회지
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• 제34권6호
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• pp.608-615
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• 2021

Soil moisture control system including soil sensing and automatic water supply chain was constructed on open farmland and pot conditions. Soil moisture was controlled by the system showing over the soil moisture contents except 40% treatment. EC was gradually decreased by increasing cultivation days. On applying this system to control soil moisture, the growth and development characters of the bellflower were improved compared with control, cultivation without the automatic irrigation. Of the growth and development characters, plant height with water treatments was higher than that of control in 1st-year plants. Moreover, numbers of branch were increased by the increased soil moisture on farmland and pot condition. Capsule numbers for seed were best at 20%, 30% soil moisture treatment in 1st-year plants, and 20% to 50% treatment in 2nd-year plants. The construction of automatic soil moisture control system provide fundamental data for plant growth and development on open farmland soil condition.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 학술발표대회 논문집
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• pp.74-79
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• 1996

• 한국농공학회논문집
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• 제62권6호
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• pp.11-20
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• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).