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넙치 및 조피볼락용 습사료의 보관조건에 따른 안정성 평가
안창범,주용석,정관식,서경란,신태선 여수대학교 1998 論文集 Vol.13 No.2
본 실험은 습사료를 대상으로 보관조건(온도별, 시간별)에 따른 지질의 산화진행 정도를 파악하여 사료의 효율적인 이용성을 구명하고자 산가(acid value, AV), 과산화물가(peroxide avlue, POV) 및 비타민 함량을 분석하였다. 생사료와 분말배합사료를 혼합하여 제조한 습사료는 혼합비가 8:2 사료에서 5:5 사료보다 높은 AV와POV를 나타내었고, 보관기간이 경과함에 따라 보관조건과는 상관없이 8:2 사료에서 빠른 산패를 보였다. 산화진행속도는 4℃ 보관조건하에서는 48시간째, -15℃ 보관조건하에서는 72시간째에서 빠르게 일어났다. 60,000 Lux이상의 직사광선 노출하에서의 AV,POV는 노출시간이 길어질수록 증가하였고, 8:2사료에서 빠르게 변화하였다. This experiment was conducted to investigate rancidity in moist pellet(MP) during various practical condition of handling and storage conditions. The experimental moist pellet diets were prepared by mixing frozen raw fish (FRF) and commercial compound meal (CCM) in ratio of 8:2 and 5:5, respectively. Immediately before and after manufacturing of MP, the MPs were stored at 4℃ and -15℃, and exposed under the sunlight(30±2℃, 60000Lux). The rancidity of each MP was determined from 1 to 96 hours after pellting. The acid value (AV) and peroxide value (POV) in the diets stored at 4 and -15℃ increased rapidly after 48 and 72 hours, respectively. For the sample exposed sunlight, AV and POV were slightly increased with the exposed time. The rancidity increased in the 8:2MP(FRF : CCM) than in the 5:5MP(ERF : CCM) at all storage condition and the amount of vitamin E in MPs decreased rapidly as AV and POV increased.
Performance Improvement of Pneumatic Artificial Muscle Manipulators Using Magneto-Rheological Brake
Ahn, Kyoung-Kwan,Cong Thanh, TU Diep,Ahn, Young-Kong The Korean Society of Mechanical Engineers 2005 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.19 No.3
A novel pneumatic artificial muscle actuator (PAM actuator), which has achieved increased popularity to provide the advantages such as high strength and high power/weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available and cheap power source, inherent safety and mobility assistance to humans performing tasks, has been regarded during the recent decades as an interesting alternative to hydraulic and electric actuators. However, some limitations still exist, such as the air compressibility and the lack of damping ability of the actuator bring the dynamic delay of the pressure response and cause the oscillatory motion. Then it is not easy to realize the performance of transient response of pneumatic artificial muscle manipulator (PAM manipulator) due to the changes in the external inertia load with high speed. In order to realize satisfactory control performance, a variable damper-MagnetoRheological Brake (MRB), is equipped to the joint of the manipulator. Superb mixture of conventional PID controller and a phase plane switching control method brings us a novel controller. This proposed controller is appropriate for a kind of plants with nonlinearity, uncertainties and disturbances. The experiments were carried out in practical PAM manipulator and the effectiveness of the proposed control algorithm was demonstrated through experiments, which had proved that the stability of the manipulator can be improved greatly in a high gain control by using MRB with phase plane switching control method and without regard for the changes of external inertia loads.
New Approach to Design MR Brake using a Small Steel Roller as a Large Size Magnetic Particle
Ahn Kyoung Kwan,Tran Hai Nam,Yoon Young Il 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
Nowadays, conventional Magneto-Rheological (MR) fluid has been commonly used in many types of device operating within three its modes that have widely known as valve, shear and squeeze film modes. Except valve mode, shear and squeeze film modes just can generate the weak resistance force. Therefore, this paper proposes a new approach with the purpose that it can help to increase the weak force in shear mode by the application of a large size magnetic particle which is a small steel roller. This kind of particle with its hydrodynamic form helps the new MR brake device which can generate the higher braking torque than the conventional one. The theory of this proposed approach is based on the deformation theory with the support of the improved magnetic field .The practical application of this approach has been examined by experimental results.
Force Control of Hybrid Actuator Using Learning Vector Quantization Neural Network
Kyoung Kwan AHN,NGUYEN Huynh Thai Chau 대한기계학회 2006 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.20 No.4
Hydraulic actuators are important in modern industry due to high power, fast response, and high stiffness. In recent years, hybrid actuation system, which combines electric and hydraulic technology in a compact unit, can be adapted to a wide variety of force, speed and torque requirements. Moreover, the hybrid actuation system has dealt with the energy consumption and noise problem existed in the conventional hydraulic system. Therefore, hybrid actuator has a wide range of application fields such as plastic injection-molding and metal forming technology, where force or pressure control is the most important technology. In this paper, the solution for force control of hybrid system is presented. However, some limitations still exist such as deterioration of the performance of transient response due to the variable environment stiffness. Therefore, intelligent switching control using Learning Vector Quantization Neural Network (LVQNN) is newly proposed in this paper in order to overcome these limitations. Experiments are carried out to evaluate the effectiveness of the proposed algorithm with large variation of stiffness of external environment. In addition, it is understood that the new system has energy saving effect even though it has almost the same response as that of valve controlled system.
Kyoung Kwan Ahn,TU Diep Cong Thanh 대한기계학회 2005 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.19 No.1
A novel actuator system which has achieved increased popularity to provide these advantages such as high strength and power/weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available, cheap power source, inherent safety and mobility assistance to humans performing tasks has been the utilization of the pneumatic artificial muscle (PAM) manipulator, in recent times. However, the complex nonlinear dynamics of the PAM manipulator makes it a challenging and appealing system for modeling and control design. The problems with the time variance, compliance, high hysteresis and nonlinearity of pneumatic systems have made it difficult to realize precise position control with high speed. In order to realize satisfactory control performance, the effect of nonlinear factors contained in the PAM manipulator must be considered. The purpose of this study is to improve the control performance of the PAM manipulator using a nonlinear PID controller. Superb mixture of conventional PID controller and the neural network, which has powerful capability of learning, adaptation and tackling nonlinearity, brings us a novel nonlinear PID controller using neural network. This proposed controller is appropriate for a kind of plants with nonlinearity uncertainties and disturbances. The experiments were carried out in practical PAM manipulator and the effectiveness of the proposed control algorithm was demonstrated through the experiments, which suggests its superior performance and disturbance rejection.