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RISS 인기검색어
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- 저자 : 임용현(Y. H. Im) (검색결과 2 건)
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임용현(Y.H. Im),이상욱(S. W. Lee),조민기(M. G. Cho),신대영(D. Y. Shin),황성호(S.H. Hwang) 유공압건설기계학회 2019 유공압건설기계학회 학술대회논문집 Vol.2019 No.6
In this paper, we propose a real-time simulation model of an excavator considering the operation of functional valves withmain control valve (MCV) using Amesim. The hydraulic system model including pump and MCV was developed, and the kinematics and dynamic modelsof manipulator were also developed to confirm behavior of the excavator. In MCV model configuration, it is possible to simulate the behavior of actual excavator, including regeneration circuit and functional valves such as holding valves, swing and boom priority valves, and arm regen-cut valves. In addition, in order to obtain appropriate real-time calculating performance, we simplified the some components, eliminated high frequency factors, and optimized parameters. Verification of the model was performed by comparing the results using the variable/fixed time step solver with the results of actual vehicle tests.
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임용현(Y. H. Im),이상욱(S. W. Lee),전소연(S. Y. Jeon),황성호(S. H. Hwang) 유공압건설기계학회 2018 유공압건설기계학회 학술대회논문집 Vol.2018 No.6
Performance analysis of the hydraulic actuators is widely used through various experiments or simulations with modeling. In the case of modeling of hydraulic components, various parameters are required and precise measurements or complex experiments are often necessary to get these parameters. Especially, a lot of trial and errorare required to obtain the modeling parameters of a hydraulic motor which is combined with hydraulic components and mechanical elements because of the nonlinear characteristics. To solve this problem, various modeling methods were proposed using statistical techniques instead of analytical techniques. In this paper, a modeling method for a swing motor of an excavator is proposed using artificial neural network, which is composed of a hydraulic motor and various functional valves such as relief valves, makeup valves and antirotation valve, etc. The model for a target swing motor was constructed using artificial neural network, in which the simulation results using commercial software were used as training data. The constructed model was verified by comparing with the computer simulation results through the known Amesim model.
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