Dimensional synthesis of mechanical linkages using artificial neural networks and Fourier descriptors
Dimensional synthesis of mechanisms to trace given paths is an important problem with no exact solution. In this paper, the problem is divided into representation of curve shape and learning the relation between curve shape and mechanism dimensions. Curve shape is represented by Fourier descriptors...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2015-04-01
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| Series: | Mechanical Sciences |
| Online Access: | http://www.mech-sci.net/6/29/2015/ms-6-29-2015.pdf |
| Summary: | Dimensional synthesis of mechanisms to trace given paths is an important
problem with no exact solution. In this paper, the problem is divided into
representation of curve shape and learning the relation between curve shape
and mechanism dimensions. Curve shape is represented by Fourier descriptors
of cumulative angular deviation of the curve, which do not depend on the
position or scale of the curve. An artificial neural network (ANN) is trained to
learn the (unknown) relation between the Fourier descriptors of a planar
curve and the dimensions of the mechanism tracing that curve. Presented with
any simple, closed, planar curve, the ANN suggests the dimensions of a
four-bar whose coupler curve is similar in shape. A local optimization
procedure further refines the results. Examples presented indicate the
method is successful as long as the curve shape is such that the mechanism
is able to trace it. |
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| ISSN: | 2191-9151 2191-916X |