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Design of Reactionless Mechanisms Based on Constrained Optimization Procedure

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Dynamic Balancing of Mechanisms and Synthesizing of Parallel Robots

Abstract

This chapter presents an optimization technique to dynamically balance planar mechanisms by minimizing the shaking forces and shaking moments due to inertia-induced forces. Dynamically equivalent systems of point masses which represent rigid links and counterweights are useful for developing optimization technique. The point-mass parameters are explicitly identified as the design variables. The balancing problem is formulated as both single-objective and multi-objective optimization problem and solved using genetic algorithm which produces better results as compared to the conventional optimization algorithm. Also, for the multi-objective optimization problem, multiple optimal solutions are created as a Pareto front using the genetic algorithm. The reduction of shaking force and shaking moment is obtained by optimizing the link mass distribution and counterweight of their point masses. The inertial properties of balanced mechanism are then computed in reverse by applying dynamical equivalent conditions from the optimized design variables. The effectiveness of the methodology is shown by applying it to problems of planar four-bar, slider-crank, and Stephenson six-bar mechanisms.

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Acknowledgment

The following material is used “With kind permission of Springer Science + Business Media.”

Section 4.1 (Chapter 4) and Sects. 5.1, 5.2 (Chapter 5) including Figs. 5.1, 5.3, 5.4 and Table 5.1; pp: 87–92, 100–101, 104–105, 110–117 from book Dynamics and Balancing of Multibody Systems, Lecture notes in applied and computational mechanics, Vol. 37 by Himanshu Chaudhary, Subir Kumar Saha, published by springer-Verlag Germany, 2009 ISBN 978-3-540-78178-3.

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Chaudhary, H., Chaudhary, K. (2016). Design of Reactionless Mechanisms Based on Constrained Optimization Procedure. In: Zhang, D., Wei, B. (eds) Dynamic Balancing of Mechanisms and Synthesizing of Parallel Robots. Springer, Cham. https://doi.org/10.1007/978-3-319-17683-3_11

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  • DOI: https://doi.org/10.1007/978-3-319-17683-3_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17682-6

  • Online ISBN: 978-3-319-17683-3

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