Articles | Volume 6, issue 1
https://doi.org/10.5194/ms-6-29-2015
https://doi.org/10.5194/ms-6-29-2015
Research article
 | 
01 Apr 2015
Research article |  | 01 Apr 2015

Dimensional synthesis of mechanical linkages using artificial neural networks and Fourier descriptors

N. Khan, I. Ullah, and M. Al-Grafi

Abstract. 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.

Download
Short summary
The problem of dimensional synthesis of mechanisms to trace a given closed curve is solved by (a) representation of curve shape using normalized Fourier descriptors and (b) learning the relation between Fourier descriptors and mechanism dimensions by an artificial neural network (ANN). The ANN developed suggests dimensions of a four-bar mechanism with coupler curve of shape similar to the one desired. The dimensions are further refined by optimization.