• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.1
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• pp.10-17
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• 2000

Recently, as the field of cyclotron application is to be wider, to inject the beam whree the user want to is getting more important. But since it is not the easy way to describe the model equation of cyclotron, it could be operated by only operator's experiences. In this paper, we suggest the cyclotron controller using the fuzzy logic and the genetic algorithm. The proposed controller was verified in useful by applying to the cyclotron's beam line. In the experiment the measured results were obtained by VXIbus and the control algorithm was performed by LabWindows/CVI.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.521-523
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• 1997

In this paper, We carried out investigation of monitoring algorithm development for electric car inspection and repair. For transmitting a data, reliable RS-422 is adopted. The LabWindows/CVI development tool of National Instruments Co. is used for the formation of monitoring screen. The experimental set-up is composed of a PC to PC system. It is applicable to electric car imspection and repair.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.2124-2126
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• 1998

In this paper, we carried out investigation of monitoring algorithm development for examination of inverter system. For transmiting data, RS-422C is adopted. The LabWindows/CVI development tool of National Instruments Co. is used for the formation of monitoring screen. The experimental set-up is composed of a PC to PC system. It is applicable to electric car inspection and repair.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.648-654
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• 2004

The Mass Flow Controller(MFC) has become crucial in semiconductor manufacturing equipments. It is an important element because the quality and the yield of a semiconductor process are decided by the accurate flow control of gas. Therefore, the demand for implementing the high speed and the highly accurate control of MFCs has been increasing. It is hard to find an article of the control algorithm applied to MFCs. But, it is known that commercially available MFCs adopt PID control algorithms. Particularly, when the system detects the flow by way of heat transfer, the MFC control problem includes the slow response and the nonlinearity. In this paper, MFC control algorithm with a superior performance to the conventional PID algorithm is discussed and the superiority is demonstrated through the experiment. A fuzzy controller was utilized in order to compensate the nonlinearity and the slow response, and the performance is compared with that of an MFC currently available in the market. The control system, in this paper, consists of a personal computer, the data acquisition board and the control algorithm carried out by LabWindows/CVI program on the PC. In addition, a method of estimating the actual flow from the sensor output with the slow response is presented. In conclusion, according to the result of the experiment, the proposed algorithm shows better accuracy and is faster than the conventional controller.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1295-1299
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• 2003

The Mass Flow Controller(MFC) has become crucial in semiconductor manufacturing equipments. It is an important element because the quality and the yield of a semiconductor process are decided by the accurate flow control of gas. Therefore, the demand for the high speed and the highly accurate control of MFCs has been requested. It is hard to find an article of the control algorithm applied to MFCs. But, it is known that commercially available MFCs have PID control algorithms. Particularly, when the system detects the flow by way of heat transfer, MFC control problem contains the time delay and the nonlinearity. In this presentation, MFC control algorithm with the superior performance to the conventional PID algorithm is discussed and the superiority is demonstrated through the experiment. Fuzzy controller was utilized in order to compensate the nonlinearity and the time delay, and the performance is compared with that of a product currently available in the market. The control system, in this presentation, consists of a personal computer, the data acquisition board and the control algorithm carried out by LabWindows/CVI program on the PC. In addition, the method of estimating an actual flow from sensor output containing the time delay and the nonlinearity is presented. In conclusion, according to the result of the experiment, the proposed algorithm shows better accuracy and is faster than the conventional controller.

• Journal of Biosystems Engineering
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• v.29 no.6 s.107
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• pp.515-520
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• 2004

A device far estimating the optimal artificial insemination time consisted of a computer, RS module, and six direct-reflex photo-sensors. Program was written in LabWindows CVI. In order to establish references for estimating optimal artificial insemination time, lying rate of the thirty three $Berkshire{\times}Hampshire crossbred sows (parity 5 to 6) was recorded from 2 days after moving into stalls to artificial insemination using a time lapse VCR and was measured every hour with one minute interval using the scan point sampling method. Twenty low hours in a day were divided into three comparing periods : 21:00 to 06:59, 07:00 to 13:59, and 14:00 to 20:59. If sum of the percentages of tying during a comparing period was less than the reference value, the starting hour of the comparing period was considered as onset of estrus and the optimal artificial insemination time was estimated at 20 to 24 hours after onset of estrus. The experimental device was evaluated with twenty five $Berkshire{\times}Hampshire$ crossbred sows (parity 2 to 7) and 23 of 25 sows $(92\%)$ were pregnant. This result suggests that the experimental device is excellent in performance for estimating optimal artificial insemination time.

• Korean Journal of Environmental Agriculture
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• v.24 no.4
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• pp.386-390
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• 2005

This study was conducted to develop the biofilter fur reducing ammonia $(NH_3)$ and hydrogen sulfide $(H_2S)$ gas emission from a pig house. A biofilter was designed and constructed by a type of squeeze air into the column type of air flow upward. Its column size was ${\Phi}260{\times}360mm$. It was used pressure drop gauge, turbo blower, air temperature, velocity sensor and control program that was programed by LabWindows CVI 5.5. Mixing materials were consisted with composted pine tree bark and perlite with 7:3 ratio (volume). The biofilter media inoculated with ammonia (Rhodococcus equi A3) and hydrogen sulfide (Alcaligenes sp. S5-5.2) oxidizing microorganisms was installed in a commercial pig house to analyzed the effectiveness of biogas removal for 10 days. Removal rates of ammonia and hydrogen sulfide gases were 90.8% and 81.5%, respectively. This result suggests that the pine compost-perlite mixture biofilter is effective and economic for reducing ammonia ana hydrogen sulfide gases.

• Journal of Animal Science and Technology
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• v.49 no.5
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• pp.677-688
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• 2007

돼지를 포함한 대부분의 동물은 일정한 발정주기를 가지고 일정한 시기에 배란을 하는 자연배란동물이지만, 토끼, 고양이, 밍크 등의 암놈은 교미자극에 의해 배란이 일어나는 유기배란동물이다. 또한 1년에 한 번만 발정하는 단발정동물과 1년에 수차례 발정하는 다발정동물이 있다. 이 중에서 모돈은 1년에 수차례 발정하는 다발정 동물로서 발정기에 들면 비발정기와는 다른 행동을 나타낸다(Diehl 등, 2001). 양돈가의 수익을 최대화하기 위해서는 비생산일수를 최소로 줄여야 한다. 모돈의 비생산일수를 줄일 수 있는 한 가지 방법은 성공적으로 교배를 시키는 것이다. 이처럼 성공적으로 교배를 시키기 위해서는 수정적기를 정확히 예측해야 한다. 만약 수정적기를 정확히 판단하지 못하여 수태가 되지 않으면, 비생산일수가 늘어나 손실을 입게 된다. 따라서 수정적기를 정확히 판단하는 것은 모돈의 성공적인 인공수정에 있어서 중요한 요소이다. 수정적기는 배란이 일어나기 전 10시간에서 12시간 사이이며, 발정이 시작되는 시점을 기준으로 하였을 때 경산돈의 경우 26시간에서 34시간 사이이고 미경산돈의 경우는 18시간에서 26시간 사이이다(Evans 등, 2001). 현재 하루에 두 번 모돈의 발정을 확인하는 것이 일반화되어 있으며, 이 때 웅돈을 접촉시키거나 육안관찰을 통하여 발정 유무를 판단한다. 이러한 방법에는 숙련된 기술과 풍부한 경험이 요구될 뿐만 아니라 총 소요노동력의 30% 정도가 요구된다(Perez 등, 1986). 하루에 두 번밖에 발정을 감지하지 않기 때문에 발정이 언제 시작되었는지를 정확히 알 수 없으며, 또한 발정의 대부분이 새벽에 시작되므로 수정적기를 정확히 판단하기란 매우 어렵다. 만약 발정을 감지했더라도 적기에 인공수정을 하지 못한다면, 수태율이 낮아지므로 경제적 손실이 초래된다. 현재 이러한 문제점 때문에 2회에서 3회에 걸쳐 인공수정을 하고 있으나 이에 따른 소요비용과 소요노동력 등은 양돈가의 부담을 가중시키는 요인이 되고 있다. 돼지는 발정기가 되면 비발정기에 나타내지 않던 외음부의 냄새를 맡는 행동, 귀를 세우는 행동 및 승가허용 행동 등을 나타낸다(Diehl 등, 2001). 또한 돼지는 비발정기에 비하여 발정기에 더 많은 활동량을 나타낸다(Altman, 1941; Erez and Hartsock, 1990). Freson 등(1998)은 스톨에서 개별적으로 사육되고 있는 모돈의 활동량을 적외선센서를 이용하여 측정함으로써 발정을 86%까지 감지하였다고 보고하였다. 그러나 이 연구는 단지 모돈의 발정을 감지하였을 뿐 번식관리에 있어서 가장 중요한 수정적기의 판단 기준을 제시하지 못하였다. 따라서, 본 연구는 스톨에서 사육되는 모돈의 활동량을 측정함으로써 발정시작시각을 감지하고 이를 기준으로 인공수정적기를 예측할 수 있는 인공수정적기 예측 장치를 개발한 후 이의 성능을 농장실증실험을 통하여 시험하고자 수행되었다.