• 제목/요약/키워드: PM machine

검색결과 510건 처리시간 0.035초

공사 현장에서의 Machine Guidance 적용에 관한 사례연구 (A Case Study on the Application of Machine Guidance in Construction Field)

  • 김완봉;박상일;이리호;서종원
    • 대한토목학회논문집
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    • 제38권5호
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    • pp.721-731
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    • 2018
  • 국내 건설현장의 인력은 점점 더 고령화 되고 있다. 건설기능인력의 부재 및 인력수급의 어려움으로 인한 건설공사의 생산성 및 품질저하를 막기 위한 다양한 방법들이 고안되고 있다. 특히 건설공사에 필수적인 중장비와 관련해서 Machine Guidance (MG), Remote Machine Control 등 다양한 방법을 적용하여 생산성 제고 및 품질 향상을 도모하고 있다. MG의 등장 이래로 많은 선행연구가 진행되었으나, 측설(공사 등에 있어서 굴착 경계면, 기준선 중심선 등을 표기하는 것)이 힘든 환경에서의 현장 테스트는 아직까지 부족한 상황이다. 본 연구에서는 측설이 복잡한 현장을 대상으로 MG 굴삭기의 현장 테스트를 진행하고 생산성 분석, 품질평가를 수행하였다. MG 굴삭기를 적용한 후 생산성을 분석한 결과 최솟값은 20.5%, 최댓값은 56.9%, 4일 평균 생산성은 표준품셈 대비 38.3% 증가하였다. 또한 품질평가를 진행한 결과 선행연구 결과 대비 수평 오차 ${\pm}1cm$, 수직 오차 ${\pm}2cm$로 검증되었다

심층 신경망모형을 사용한 미세먼지 PM10의 예측 (Prediction of fine dust PM10 using a deep neural network model)

  • 전성현;손영숙
    • 응용통계연구
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    • 제31권2호
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    • pp.265-285
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    • 2018
  • 본 연구에서는 미세먼지 $PM_{10}$의 4가지 분류 등급인 '좋음, 보통, 나쁨, 매우 나쁨' 그리고 2가지 분류 등급인 '좋음 혹은 보통, 나쁨 혹은 매우 나쁨'을 예측하기 위해서 심층 신경망모형을 사용하였다. 2010년부터 2015년까지 국내 6개 대도시 지역에서 관측한 일별 미세먼지 데이터에 대하여 기존 분류기법인 신경망모형, 다항 로지스틱 회귀모형, Support Vector Machine, Random Forest을 적용했을 때에 비해서 심층 신경망모형의 정확도는 더 높아졌다.

임상에서 촬영되는 파노라마 방사선사진의 재현성 조사 (Reproducibility of panoramic radiography in patients)

  • 나경수
    • Imaging Science in Dentistry
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    • 제35권3호
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    • pp.115-119
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    • 2005
  • Purpose : To evaluate the magnification error percentage in repeatedly taken panoramic radiographs of same patient and machine. Materials and Methods : 92 panoramic radiographs from 46 patients were traced and 30 horizontal and vertical measurements were made with digital sliding caliper. The results were compared with paired t-test. Results : There was no statistically significant difference between the two measurements. The overall difference as percentage error was $6.19\pm5.60\%$. The largest error as $14.61\pm12.44\%$ was found at condylar height 1, and smallest as $1.86\pm1.61\%$ at mandibular height. Overall vertical error excluding condylar height 1 was $3.76\pm3.97\%$, and the horizontal error $6.88\pm5.92\%$. Conclusion . Repeatedly taken panoramic radiographs of the same patient and machine was reliable since there was no significant percentage error difference but the percentage error ranged from $1.86\pm1.61\%\;to\;14.61\pm12.44\%$ indicating the error depends on the measuring site.

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Forecasting daily PM10 concentrations in Seoul using various data mining techniques

  • Choi, Ji-Eun;Lee, Hyesun;Song, Jongwoo
    • Communications for Statistical Applications and Methods
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    • 제25권2호
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    • pp.199-215
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    • 2018
  • Interest in $PM_{10}$ concentrations have increased greatly in Korea due to recent increases in air pollution levels. Therefore, we consider a forecasting model for next day $PM_{10}$ concentration based on the principal elements of air pollution, weather information and Beijing $PM_{2.5}$. If we can forecast the next day $PM_{10}$ concentration level accurately, we believe that this forecasting can be useful for policy makers and public. This paper is intended to help forecast a daily mean $PM_{10}$, a daily max $PM_{10}$ and four stages of $PM_{10}$ provided by the Ministry of Environment using various data mining techniques. We use seven models to forecast the daily $PM_{10}$, which include five regression models (linear regression, Randomforest, gradient boosting, support vector machine, neural network), and two time series models (ARIMA, ARFIMA). As a result, the linear regression model performs the best in the $PM_{10}$ concentration forecast and the linear regression and Randomforest model performs the best in the $PM_{10}$ class forecast. The results also indicate that the $PM_{10}$ in Seoul is influenced by Beijing $PM_{2.5}$ and air pollution from power stations in the west coast.

다중선형회귀와 기계학습 모델을 이용한 PM10 농도 예측 및 평가 (Evaluation and Predicting PM10 Concentration Using Multiple Linear Regression and Machine Learning)

  • 손상훈;김진수
    • 대한원격탐사학회지
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    • 제36권6_3호
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    • pp.1711-1720
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    • 2020
  • 최근 급속한 산업화와 도시화로 인해 인위적으로 발생하는 미세먼지(Particulate matter, PM)는 기상 조건에 따라 이동 및 분산되면서 피부와 호흡기 등 인체에 악영향을 미친다. 본 연구는 기상인자를 multiple linear regression(MLR), support vector machine(SVM), 그리고 random forest(RF) 모델의 입력자료로 하여 서울시 PM10 농도를 예측하고, 모델 간 성능을 비교 평가하는데 그 목적을 둔다. 먼저 서울시에 소재한 39개소 대기오염측정망(air quality monitoring sites, AQMS)에서 관측된 PM10 농도 자료를 8:2 비율로 구분하여 모델 훈련과 검증 데이터셋으로 사용되었다. 또한 기상관측소(automatic weather system, AWS)에서 관측되고 있는 자료 중 9개 기상인자(평균기온, 최고기온, 최저기온, 일 강수량, 평균풍속, 최대순간풍속, 최대순간풍속풍향, 황사발생유무, 상대습도)가 모델의 입력자료로 선정되었다. 각 AQMS에서 관측된 PM10 농도와 MLR, SVM, 그리고 RF 모델에 의해 예측된 PM10 농도 간 결정계수(R2)는 각각 0.260, 0.772, 그리고 0.793이었고, RF 모델이 PM10 농도 예측에 가장 높은 성능을 나타냈다. 특히 모델 검증에 사용되는 AQMS 중 관악구와 강남대로 AQMS는 상대적으로 AWS에 가까워 SVM과 RF 모델에서 높은 정확도를 나타냈다. 종로구 AQMS는 AWS에서 비교적 멀리 떨어져 있지만, 인접한 두 AQMS 데이터가 모델 학습에 사용되었기 때문에 두 모델에서 높은 정확도를 나타냈다. 반면 용산구 AQMS는 AQMS 및 AWS에서 비교적 멀리 떨어져 있기에 두 모델의 성능이 낮게 나타냈다.

영구자석 사용 효율 향상을 위한 IPM 전동기의 최적 토폴로지 (Topology Optimal Interior Permanent Magnet Machine to Improve the Utilization Ratio of Permanent Magnet)

  • 도욱;장전해;주립훈;고창섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2015년도 제46회 하계학술대회
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    • pp.862-863
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    • 2015
  • This paper presents an improved estimation procedure for the contribution to no-load flux linkage created by the permanent magnet (PM) in interior permanent magnet synchronous machines. In the proposed method, the saturation effect in stator and rotor cores are taken into account by utilizing the frozen permeability method (FPM). This improved procedure can evaluate the contribution for each local element in the PM to the no-load flux linkage. According to the analysis results, an effective PM topology optimal design can be carried out to achieve high utilization ratio of PM in the machine. In order to determine the threshold of the low contribution of PM for removing, one multi-objective optimization model is proposed. Based on the optimal threshold, the final optimal topology design of PM can be achieved.

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소형 풍력발전기용 AFPM 발전기 코깅토크 저감 설계 (Cogging Torque Reduction in AFPM Generator Design for Small Wind Turbines)

  • 정대원
    • 전기학회논문지
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    • 제61권12호
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    • pp.1820-1827
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    • 2012
  • This paper is to present a new method of cogging torque reduction for axial flux PM machines of multiple rotor surface mounted magnets. In order to start softly and to run a power generator even the case of weak wind power, reduction of cogging torque is one of the most important issues for a small wind turbine, Cogging torque is an inherent characteristic of PM machines and is caused by the geometry shape of the machine. Several methods have been already applied for reducing the cogging torque of conventional radial flux PM machines. Even though some of these techniques can be also applied to axial flux machines, manufacturing cost is especially higher due to the unique construction of the axial flux machine stator. Consequently, a simpler and low cost method is proposed to apply on axial flux PM machines. This new method is actually applied to a generator of 1.0kW, 16-poles axial flux surface magnet disc type machine with double-rotor-single-stator for small wind turbine. Design optimization of the adjacent magnet pole-arc which results in minimum cogging torque as well as assessment of the effect on the maximum available torque using 3D Finite Element Analysis (FEA) is investigated in this design. Although the design improvement is intended for small wind turbines, it is also applicable to larger wind turbines.

철도 차량용 고출력 고효율 선형 추진시스템 설계 (A Design of Linear Motor with High Power Density and High Efficiency for Railway and Magnetic Levitation System)

  • 강도현
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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    • pp.393-396
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    • 2001
  • According to the development of power electronic element(GTO, IGBT) and material for electrical machines(permanent magnet, super conductor), the technology for electrical machines is nowaday rapidly developing. Here with, a novel electrical machine, based on the new conception of transverse flux configuration leads to a considerable Increase in power density and enables simultaneously high efficiency. The transverse flux machine with PM excitation will be applied to gearless direct drives for railway traction system and magnetic levitation system. The designed and measured performance of transverse machine for railway traction system and magnetic levitation system revealed a great potential of system improvements to reduce linear motor mass and increase efficiency.

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The Practical Method and Experimental Verification of Temperature Estimation in the Permanent Magnet of Electric Machine

  • Kang, Kyongho;Yu, Sukjin;Lee, Geunho;Lee, Byeong-Hwa
    • Journal of Magnetics
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    • 제20권4호
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    • pp.421-426
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    • 2015
  • This paper presents a practical method for estimation of average temperature in the permanent magnet (PM) of electric machine by using finite element analysis (FEA) and dynamo load experiment. First of all, the temperature effect of PM to the torque has been employed by FEA in order to evaluate the Temperature-Torque characteristic curve. The 1st order polynomial equation which is torque attenuation coefficient is derived by the FEA result of the Temperature-Torque curve. Next, torque saturation test with constant current condition is performed by dynamo load experiment. Then, the temperature trend can be estimated by adding the initial starting temperature using the torque attenuation coefficient and torque saturation curve. Lastly, estimated temperature is validated by infrared thermometer which measures temperature of PM surface. The comparison between the estimated result and experimental result gives a good agreement within a deviation of maximum $8^{\circ}C$.

영구자석 기기의 철손 예측을 위한 자계 거동 해석 (Magnetic Field Distribution Analysis for Core Loss Estimation of Permanent Magnet Machine)

  • 장석명;고경진;최장영;박지훈;이성호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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    • pp.93-95
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    • 2008
  • Nowadays more attention is paid to the developing high efficiency electrical machines for energy saving and protection of natural resources. In general, the electromagnetic losses appearing in electrical machines are widely classified into copper loss, core loss and rotor loss. Particularly, in permanent magnet (PM) machines, core loss forms a larger portion of the total losses than in another machine. So, satisfactory prediction of core loss at the design or analysis stage of PM machines is essential to active high efficiency and high performance. This paper deals with analysis of magnetic field distribution due to geometry of stator core for magnetic core loss calculation of multi-pole PM synchronous machine.

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