• Journal of Biosystems Engineering
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• v.9 no.1
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• pp.1-4
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• 1984

노외차량(路外車輛)의 승차(乘車) 시뮬레이션을 위한 착석(着席) 상태(狀態)의 운전자(運轉者) 모델을 개발(開發)하였다. 운전자(運轉者) 모델은 머리, 몸체, 신부(腎部)로 크게 나누어 자유도(自由度) 3의 진동체로 가정(假定)하고 머리와 몸체, 몸체와 신부(腎部)는 각각 목과 장기(臟器)를 나타내는 탄성체로서 연결하였다. 또한 인체의 해부학적(解部學的) 구조(構造)와 일치(一致)하도록 머리와 신부(腎部)사이에는 척추(脊椎) 부분(部分)을 포함시켰다. 모델의 각 변수(變數)들은 기존(旣存)의 실험(實驗) 결과(結果)를 이용(利用)하여 머리부의 진동(振動)이 실험(實驗) 결과(結果)와 일치(一致)하도록 시뮬레이션 방법(方法)으로 결정(決定)하였다.

• Journal of Biosystems Engineering
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• v.11 no.2
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• pp.66-75
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• 1986

In order to improve the traditional post harvest system in Korea, a model for mechanized grain drying and storage facilities was developed. Also, a computer program for the model system was developed. For the study, flat type steel bin and circulation type dryer were selected for the model and Fortran language was used for the computer program. This program was tested by using various practical data. The following results were obtained from the study: 1. The general model developed can be used for designing a rough rice drying and storage facility within the range from 100 ton to 1000 ton capacity. 2. Major output of the computer program for designing a model system were as follow; a. The dimension of the plant. b. The storage bin size, dryer number and dryer size. c. The dimension of individual equipment and its required HP. d. Capital requirement and operating cost of the model system.

• Agricultural and Biosystems Engineering
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• v.2 no.1
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• pp.15-23
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• 2001

On the assumption that the voices of the cows are produced by the linear prediction filter, we characterized the cows’voices. The order of this filter was determined by examining the voice characteristics both in time and frequency domains. The proposed order of the linear prediction filter is 15 for modeling voice production of the cow. The characteristics of the amplitude envelope of the voice signal was investigated by analyzing the sequence of the short time variance both in time and frequency domains, and the new parameters were defined. One of the coefficients o the linear prediction filter generating the voice signal, the fundamental frequency, the slope of the straight line regressed from the log-log spectra of the short time variance and the coefficients of the linear prediction filter generating the sequence of the short time variance of the voice signal can differentiate the two cows.

• Food Science and Biotechnology
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• v.14 no.3
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• pp.328-333
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• 2005

Finite difference model and dynamic thermal property evaluation system were developed to estimate convection heat transfer coefficient by modeling temperature-time profile of beef cube in continuous flow sterilizing system. As input parameters of the model, specific heat and thermal conductivity values of beef frankfurter meat were independently measured from 20 to $80^{\circ}C$. Convection heat transfer coefficient was estimated by comparing simulated and measured temperature-time profiles. Actual temperature-time profiles of meat cube were measured at flow rates of 15, 30, and 45 L/min and viscosities from 0 to 15 cp, and mean values of convection heat transfer coefficients ranged from 792 to $2107\;W/m^2{\cdot}K$. Convection heat transfer coefficient increased with increase in flow rate and decreased as viscosity increased.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.166-166
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• 2017

모돈의 건강 상태를 정량 지수화 하기 위한 연구를 수행 중이다. 지제이상, 섭식 불량, 수면 패턴 등의 운동 특성 분석을 위하여 복수의 초음파 센서를 이용하였다. 시계열 계측 신호를 분석하여 정량 지수화를 수행하는 과정에서 주파수 도메인 분석을 시도하였다. 이 과정에서 주파수 도메인의 분해능에 따른 편차 극복을 위한 비선형 모델링을 수행하였다. 또한 인접한 시계열 데이터 구간 간의 상관성 분석이 가능하면 대용량 데이터의 실시간 처리로 인한 지연 시간 극복 및 기대되는 예후에 대한 조기 진단이 가능할 것이다. 본 연구에서는 구글에서 제공하는 Tensorflow와 NVIDIA에서 제공하는 CUDA 엔진을 동시 적용한 심층 학습 시스템을 이용하였다. 전 처리를 위하여 주파수 분해능 (2분, 3분, 5분, 7분, 11분, 13분, 17분, 19분)에 따른 데이터 집합을 1단계로 두고, 상위 10 순위 안에 드는 파워 스펙트럼 밀도의 크기를 2단계로 하여, 총 2~10개의 입력 노드를 순차적으로 선정하였고, 동일한 방식으로 인접한 시계열의 파워 스펙터럼 밀도를 순위를 변화시켜 지정하였다. 대표적인 심층학습 모델인 Softmax regression with a multilayer convolutional network를 이용하여 Recursive feature selection 경우의 수를 $8{\times}9{\times}9$로 총 648 가지 선정하고, Epoch는 10,000회로 지정하였다. Calibration 모델링의 경우 Cost function이 10% 이하인 경우 해당 경우의 학습을 중단하였으며, 모델 간 상호 교차 검증을 수행하기 위하여 $_8C_2{\times}_8C_2{\times}_8C_2$ 경우의 수에 대한 Verification test를 수행하였다. Calibration 과정 상 모든 경우에 대하여 10% 이하의 Cost function 값을 보였으나, 검증 테스트 과정에서 모든 경우에 대하여 $r^2$ < 0.5 인 결정 계수 값이 나타났다. 단적으로 심층학습 모델의 과도한 적합(Over fitting) 방식의 한계를 보인 것이라 판단할 수 있다. 적합한 Feature selection 및 심층 학습 모델에 대한 지속적이고 추가적인 고려를 통해 과도적합을 해소함과 동시에 실효적이고 활용 가능한 Classification을 위한 입, 출력 노드 단의 전후 Indexing, Quantization에 대한 고려가 필요할 것이다. 이를 통해 모돈 생체 정보 정량화를 위한 지능형 현장 진단 기술 연구를 지속할 것이다.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.170-170
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• 2017

기후변화 따른 스마트팜 돈사 외부 환경의 변화에 대응하고, 사육 환경을 능동적으로 개선하기 위한 연구가 수행 중이다. 돈사 내 열전달 요소 간 상호 역학성 분석을 위해서 고려해야할 사항은 입기구, 보온 등, 열풍기, 단열제, 위치, 방향, 돈사의 연평균 온도, 습도, 연중 일사량, 가축의 열복사 등 상호 복잡하게 연관되어 있는 물리량이다. 돈사 전체 열손실, 자연발생 에너지량, 강제발생 에너지량, 난방용량 등을 고려한 순간 열부하 산정을 위한 여러 방법 중 우선적으로 CFD(Computational Fluid Dynamics)를 이용하였다. 순간 열부하 산정을 위한 해석 도구 선정에 있어서 다양한 유체 및 기체 전산 유체역학 Solver(Fluent, Open-FOAM, Blender)를 고려하였다. 공간 Mech를 수행하기 위한 도구로는 공개 소프트웨어 인 FreeFem++ 3.51-4 (http://www.freefem.org)를 이용하였다. 이 과정에서 일부 기체 (암모니아)의 농도를 난수로 변화시키는 기법을 적용하여 가상적으로 돈사의 환경을 Pseudo 시뮬레이션 하였다. 결과적으로 Fluent에 비하여 OpenFOAM을 이용하여 얻은 열유동의 방향(속도)과 크기 백터가 상대적으로 크게 나타났다. Fluent가 시계열 상에서 혼합 기체 물리량 변화를 무시할 수 있는 안정되고 균일한 환경에 적합하기 때문인 것으로 판단되었다. Blender의 경우 Lattice Boltzmann methods 과 Smoothed-particle hydrodynamics 방법을 이용한 유체/입자 동력학 모델링을 제공함에 있어 시각적 효과를 강조하는 기능에 중점을 두었다. Fluent와 Blender에서 제공하는 해석 연산 모듈의 정확성 검증을 위해선 공간 분해능을 높인 정밀 계측 시스템을 이용하여 검증할 필요가 있다. Open-FOAM를 이용한 열부하 분석 수행이 상대적으로 높은 절대값을 보이는 특성은 열부하 제어 시스템의 Overshoot를 유발할 가능성이 있으므로 이에 대한 해석 모델의 보정이 추가적으로 필요할 것이다. CFD의 한계인 시간 복잡도를 낮추고 상대적으로 높은 시계열 분해능을 확보할 경우 돈사 내 환기시스템에 맞는 소요 환기량 실시간 산정이 가능해지고 외부기상 및 돈사내부 복사열을 활용함과 동시에 돈군 순환에 상응하는 실시간 열부하 관리 시스템 도출이 가능할 것이다.

• Journal of Biosystems Engineering
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• v.41 no.3
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• pp.221-231
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• 2016

Purpose: The objective of this study was to develop cushion curves models and analyze the cushioning performance of multi-layered corrugated structures (MLCS) using a method based on dynamic stress-energy relationship. Methods: Cushion tests were performed for developing cushion curve models under 12 combinations of test conditions: three different combinations of drop height, material thickness, and static stress for each of four levels of energy densities between 15 and $60kJ/m^3$. Results: Dynamic stress and energy density for MLCS followed an exponential relationship. Cushion curve models were developed as a function of drop height, material thickness, and static stress for different paperboards and flute types. Generally, the differences between the shock pulse (transmitted peak acceleration) and cushion curve (position and width of belly portion) for the first drop and the averaged second to fifth drop were greater than those for polymer-based cushioning materials. Accordingly, the loss of cushioning performance of MLCS was estimated to be greater than that of polymer-based cushioning materials with the increasing number of drops. The position of the belly of the cushion curve of MLCS tends to shift upward to the left with increasing drop height, and the belly portion became narrower. However, depending on material thickness, under identical conditions, the cushion curve of MLCS showed an opposite tendency. Conclusions: The results of this study can be useful for environment-friendly and optimal packaging design as shock and vibrations are the key factors in cushioning packaging design.

• Journal of Biosystems Engineering
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• v.29 no.6 s.107
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• pp.501-507
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• 2004

Fruits we subjected to complex dynamic stresses in the transportation environment. During a long journey from the production area to markets, there is always some degree of vibration present. Vibration inputs are transmitted from the vehicle through the packaging to the fruit. Inside, these cause sustained bouncing of fruits against each other and container wall. These steady state vibration input may cause serious fruit injury, and this damage is particularly severe whenever the fruit inside the package is free to bounce, and is vibrated at its resonant frequency. The determination of the resonant frequencies of the fruit may help the packaging designer to determine the proper packaging system providing adequate protection for the fruit, and to understand the complex interaction between the components of fruit when they relate to expected transportation vibration inputs. The vibration characteristics of the pears in corrugated fiberboard container in transit were analyzed using FEM (finite element method) modeling, and the FEM modeling approach was first validated by comparing the results obtained from simulation and experiment for the pear in the frequency range 3 to 150 Hz and acceleration level of 0.25 G-rms and it was found that between simulated and measured frequencies of the pears have a relatively good agreement. It was observed that the fruit and vegetables in corrugated fiberboard container could be analyzed by finite element method. As the elastic modulus of the cushion materials of corrugated fiberboard pad and tray cup decreased, the first frequencies of upper and lower pears increased and the peak acceleration decreased.

• Journal of Biosystems Engineering
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• v.17 no.1
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• pp.65-78
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• 1992

When using a computer vision system for a measurement, the geometrically distorted input image usually restricts the site and size of the measuring window. A geometrically distorted image caused by the image sensing and processing hardware degrades the accuracy of the visual measurement and prohibits the arbitrary selection of the measuring scope. Therefore, an image calibration is inevitable to improve the measuring accuracy. A calibration process is usually done via four steps such as measurement, modeling, parameter estimation, and compensation. In this paper, the efficient error calibration technique of a geometrically distorted input image was developed using a neural network. After calibrating a unit pixel, the distorted image was compensated by training CMLAN(Cerebellar Model Linear Associator Network) without modeling the behavior of any system element. The input/output training pairs for the network was obtained by processing the image of the devised sampled pattern. The generalization property of the network successfully compensates the distortion errors of the untrained arbitrary pixel points on the image space. The error convergence of the trained network with respect to the network control parameters were also presented. The compensated image through the network was then post processed using a simple DDA(Digital Differential Analyzer) to avoid the pixel disconnectivity. The compensation effect was verified using known sized geometric primitives. A way to extract directly a real scaled geometric quantity of the object from the 8-directional chain coding was also devised and coded. Since the developed calibration algorithm does not require any knowledge of modeling system elements and estimating parameters, it can be applied simply to any image processing system. Furthermore, it efficiently enhances the measurement accuracy and allows the arbitrary sizing and locating of the measuring window. The applied and developed algorithms were coded as a menu driven way using MS-C language Ver. 6.0, PC VISION PLUS library functions, and VGA graphic functions.

• Journal of Energy Engineering
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• v.24 no.4
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• pp.200-210
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• 2015

The modeling for fast pyrolysis of biomass in fluidized bed reactor has been developed for accurate prediction of bio-oil and gas products and for yield improvement. The purpose of this study is to analyze and to compare the CFD(Computational Fluid Dynamics) simulation results with the experimental data from the CFD simulation results with the experimental data from the reference(Mellin et al., 2014) for gas products generated during fast pyrolysis of biomass in fluidized bed reactor. CFD(ANSYS FLUENT v.15.0) was used for the simulation. Complex pyrolysis reaction scheme of biomass subcomponents was applied for the simulation of pyrolysis reaction. This pyrolysis reaction scheme was included reaction of cellulose, hemicellulose, lignin in detail, gas products obtained from pyrolysis were mainly $CO_2$, CO, $CH_4$, $H_2$, $C_2H_4$. The deviation between the simulation results from this study and experimental data from the reference was calculated about 3.7%p, 4.6%p, 3.9%p for $CH_4$, $H_2$, $C_2H_4$ respectively, whereas 9.6%p and 6.7%p for $CO_2$ and CO which are relatively high. Through this study, it is possible to predict gas products accurately by using CFD simulation approach. Moreover, this modeling approach should be developed to predict fluidized bed reactor performance and other gas product yields.