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Qiang Chen
Nanjing University

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Simulated Annealing Algorithm for Friction Parameters Identification Qiang Chen; Junwei Bao; Minzhuo Wang; Haonan Ye; Fuqiang Peng
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: January 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

The present study is concerned with friction parameters identification in the pushing system of projectile of large caliber cannon howitzer. Coulomb model (CM) is adapted to build friction model in the process of pushing projectile. Random direction search algorithm (RDSA) is probably to get into the local best because of the large number of parameters to identify. So simulated annealing algorithm (SAA) based on continuous search space (CSAA) and based on discrete search space (DSAA) is applied to identify friction parameters. The identification results show that both CSAA and DSAA have better accuracy and convergence than RDSA, and CSAA has better accuracy than DSAA. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.1893
Inertia Force Identification of Cantilever under Moving-Mass by Inverse Method Qiang Chen; Hao Yan; Minzhuo Wang; Haonan Ye
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 8: December 2012
Publisher : Institute of Advanced Engineering and Science

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In this paper, a recursive inverse method is applied to solve the identification problem of inertia force between the cantilever and moving mass. The recursive inverse method consists of two parts: Kalman filter and recursive least-square algorithm. The basic Euler-Bernoulli beam model is introduced. Then, the differential equations and the state space model of the modal responses and the inertia force can be obtained. Finally, the recursive inverse method, which is based on the discretized state function of the system, is adapted. The identification results show that the recursive inverse method is suitable to be adapted in this problem. Some characteristics of the identification results are discussed and some further conclusions are reached. DOI: http://dx.doi.org/10.11591/telkomnika.v10i8.1649
Virtual Training System for Hydraulic Pump Cart Based on Virtual Reality Wusha Huang; Qiang Chen; Minzhuo Wang; Haonan Ye
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 8: August 2013
Publisher : Institute of Advanced Engineering and Science

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This paper dissertates the application of Virtual Reality Technology in the training process. Virtual training system has more advantages than traditional training system. The design of virtual training system based on PTC DIVISION Mockup software, position tracker and 3-D mouse is proposed. The system is divided into two parts: directing part and operating part. Collision detection is discussed to improve the sense of reality in the virtual environment .This system is applied to the training process of hydraulic pump cart’s assembly and disassembly. More immersive training effect is obtained in this system. The goal of reducing training costs and improving the efficiency of training can be achieved in the virtual training system. DOI: http://dx.doi.org/10.11591/telkomnika.v11i8.3026 
Identification of robot arm’s joints’ time-varying stiffness under loads Rui Xu; Qiang Chen; Guolai Yang
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 8: December 2012
Publisher : Institute of Advanced Engineering and Science

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This paper is concerned with the identification problem of two degree of freedom robot arm’s joints’ time-varying stiffness under time-varying torque loads. The industrial robot arms can be simplified into series hinged linkage mechanism. The unrestraint dynamic equation of two degrees of freedom robot arm can be obtained by using analytical mechanics method. The model which was established in Pro/E had been imported into ADAMS for simulation. And the simulation consisted of free vibration and forced vibration. Then by choosing limited memory least square method and using the post-processing measured variables, time-varying stiffness could have been identified. Finally, the calculative stiffness was compared to the “real” stiffness which was simulated in ADAMS. The whole process shows that the robot arm’s dynamic model and the method of identification are both effective. DOI: http://dx.doi.org/10.11591/telkomnika.v10i8.1644
Co-Authors Fuqiang Peng Guolai Yang Hao Yan Haonan Ye Junwei Bao Minzhuo Wang Rui Xu Wusha Huang