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On-line 학습 신경회로망을 이용한 열간 압연하중 예측
손준식,이덕만,김일수,최승갑 한국공작기계학회 2005 한국생산제조학회지 Vol.14 No.1
In the face of global competition, the requirements for the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. In this paper, an on-line training neural network for both long-term learning and short-term learning was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.
손준식,김일수,권욱현,최승갑,박철재,이덕만 한국공작기계학회 2001 한국생산제조학회지 Vol.10 No.5
The quality requirements for thickness accuracy in cold rolling continue to become more stringent, particularly in response to exacting design specification from automotive customers. One of the major impacts from the tighter tolerance level is more unusable product on the head end and tail end of tandem mill coils when the mill is in transition to or from steady state rolling condition. A strip thickness control system for a tandem cold steel rolling mills is composed with blocked non-interacting controller and controllers for strip thickness and tension control of each rolling stands. An intelligent mathematical model included an elastic deformation of strip has been developed and applied to the field in order to predict the rolling force. The simulated results showed that the effect of elastic recovery should be included the model, even if the effect of elastic compression was not important.
방사형기저함수망을 이용한 열간 사상압연의 압연하중 예측에 관한 연구
손준식,이덕만,김일수,최승갑 한국공작기계학회 2004 한국생산제조학회지 Vol.13 No.6
A major concern at present is the simultaneous control of transverse thickness profile and flatness in the finishing stages of hot rolling process. The mathematical modeling of hot rolling process has long been recognized to be a desirable approach to investigate rolling operating practice and the design of mill equipment to improve productivity and quality. However, many factors make the mathematical analysis of the rolling process very complex and time-consuming. In order to overcome these problems and to obtain an accurate rolling force, the predicted model of rolling force using neural networks has widely been employed. In this paper, Radial Basis Function Network(RBFN) is applied to improve the accuracy of rolling force prediction in hot rolling mill. In order to verify and analyze the performance of applied neural network, the comparison with the measured rolling force and the predicted results using two different neural networks-RBFN, MLP, has respectively been carried out. The results obtained using RBFN neural network are much more accurate those obtained the MLP.
On-line 학습 신경회로망을 이용한 열간 압연하중 예측
손준식,이덕만,김일수,최숭갑 한국공작기계학회 2003 한국공작기계학회 춘계학술대회논문집 Vol.2003 No.-
In the face of global competition, the requirements for the continuously increasing productivity, flexibility and quality(dimensional accuracy, mechanical properties and surface properties) have imposed a major change on steel manufacturing industries. Indeed, one of the keys to achieve this goal is the automation of the steel-making process using AI(Artificial Intelligence) techniques. The automation of hot rolling process requires the developments of several mathematical models for simulation and quantitative description of the industrial operations involved. In this paper, a on-line training neural network for both long-term learning and short-term learning was developed in order to improve the prediction of rolling force in hot rolling mill. This analysis shows that the predicted rolling force is very closed to the actual rolling force, and the thickness error of the strip is considerably reduced.
Ill-Min Chung,Min-Jeong An,Kyoung-Jin Lee,Ji-Hee Lee,Sung-Kyu Park,Na-Young Son,Yeon-Ju An,Jae-Gu Han,Won-Sik Kong,Seung-Hyun Kim 한국버섯학회 2017 버섯 Vol.21 No.2
Although Agaricus bisporus mushroom is a popular mushroom consumed world-widely, the application of common bio-elements to verify its geographical origin remains highly limited. Therefore, this study aimed to verify whether the six cultivation regions in Korea of A. bisporus could be determined by the stable isotope composition analysis of bio-elements, which are unique and abundant in most living creatures. δ13C, δ15N, δ18O, and δ34S in A. bisporus were influenced by the region, cultivar, and the interactions between these two factors (P < 0.05). In particular, the effect of cultivation region was more significant to the isotope ratio profiles as compared to the mushroom cultivar effect. During the cultivation period of A. bisporus, the C, N, O, and S isotopic fractionation was observed between the mushroom and cultivation medium, note higher in the mushroom (P < 0.05). Two dimensional plot of δ15N, δ18O, or δ34S effectively distinguished the cultivation regions, Nonsan, Buyeo, Boryung, Daegu, and/or Gyeongju examined in this study. Further, these isotope ratio profiles measured in this study would be statistically analyzed with various chemometrics to provide isotope markers for the authenticity of geographical origin. Our preliminary case study improves our understanding of how the isotope composition of A. bisporus varies with respect to cultivation regions and cultivars. In conclusion, the analysis of stable isotope ratios is a suitable potential tool for discrimination between the cultivation origins of A. bisporus collected from Korea, with potential application to other countries after certain validation steps required.
A MODIFIED NIEMENTOWSKI REACTION FOR THE SYNTHESIS OF 4-HYDROXYQUINOLINE AND ITS REALTED COMPOUNDS
Son, Jae Keun,Kim, Seung Ill,Jahng, Yurngdong 영남대학교 약품개발연구소 2002 영남대학교 약품개발연구소 연구업적집 Vol.11 No.-
The iminoketene generated from anthranilic acid and thionyl chloride reacted with ketones to afford 4-hydroxyquinoline derivatives in good yields.