Epicyclic gear trains (EGTs) are used in the mechanical energy transmission systems where high velocity ratios are needed in a compact space. It is necessary to eliminate duplicate structures in the initial stages of enumeration. In this paper, a novel and simple method is proposed using a parameter, Vertex Incidence Polynomial (VIP), to synthesize epicyclic gear trains up to six links eliminating all isomorphic gear trains. Each epicyclic gear train is represented as a graph by denoting gear pair with thick line and transfer pair with thin line. All the permissible graphs of epicyclic gear trains from the fundamental principles are generated by the recursive method. Isomorphic graphs are identified by calculating VIP. Another parameter “Rotation Index” (RI) is proposed to detect rotational isomorphism. It is found that there are six nonisomorphic rotation graphs for five-link one degree-of-freedom (1-DOF) and 26 graphs for six-link 1-DOF EGTs from which all the nonisomorphic displacement graphs can be derived by adding the transfer vertices for each combination. The proposed method proved to be successful in clustering all the isomorphic structures into a group, which in turn checked for rotational isomorphism. This method is very easy to understand and allows performing isomorphism test in epicyclic gear trains.

Detection of isomorphism in planar and geared kinematic chains (GKCs) is an interesting area since many years. Enumeration of planar and geared kinematic chains becomes easy only when isomorphism problem is resolved effectively. Many researchers proposed algorithms based on topological characteristics or some coding which need lot of computations and comparisons. In this paper, a novel and simple algorithm is proposed based on graph theory by which elimination of isomorphic chains can be done very easily without any tedious calculations or comparisons. A new concept “Net distance” is proposed based on the graph theory to be a quantitative measure to assess isomorphism in planar kinematic chains (PKCs) as well as GKCs. The proposed algorithm is applied on nine-link two-degrees-of-freedom (DOF) distinct kinematic chains completely and the results are presented. Algorithm is tested on examples from eight-link 1-DOF, ten-link 1-DOF, 12-link 1-DOF, and 15link 4-DOF PKCs. The algorithm is also tested on four-, six-link 1-DOF GKCs to detect isomorphism. All the results are in agreement with the existing literature.

Abstract-Structural synthesis of kinematic chains is an interesting area for researchers since many years. Selection of best kinematic chain with desired linkage and degree of freedom for a specific industrial purpose i.e. automotive transmission system, robotic manipulators, lifting devices needs systematic synthesis. Many researchers developed algorithms involving lot of computations. Planar kinematic chains can be modeled as fuzzy systems, so that fuzzy logic will be applied. It is necessary to develop quantitative methods to compare the kinematic chains at the conceptual stage of design for characteristics like static and dynamic behaviour, workspace, rigidity etc. These properties have greater meaning when multi degree of freedom chains are considered for application as platform type robots. It is shown that fuzzy entropy can be utilized to compare many kinematic chains with similar linkage characteristics and degree of freedom. In the present work, concept of fuzzy entropy is applied on 8-link 1-dof kinematic distinct chains (16 No.) for the structural comparison and rating. The results are presented in Appendix I.