A simple and efficient method for isomorphism identification of planar kinematic chains

Isomorphism identification plays an important role in structural design and innovative design. Based on the adjacency matrix and loop theory, a new method is proposed in this paper to identify the isomorphic kinematic chains. It enriches the application of loop-based theory for isomorphism identification. In the kinematic chain, links and joints are connected alternatively and every link corresponds to a fixed link degree. Due to the inherent characteristics, the labeled sequence of links can be random, which does not affect the result of isomorphism identification. By the programming software MATLAB, some examples with 6-, 8-, 10-, 11-, 12-link kinematic chains, and 15-vertex topological graphs are presented. Results show that the proposed method applies to topology graphs and kinematic chains with one or multiple joints. Compared with other methods, the proposed method is confirmed correctly. And there is no counterexample. It lays a solid foundation for structural synthesis in the future.

Synthesis method for planetary gear trains without using rotation graphs

The displacement graphs (d-graphs) are the final form of planetary gear trains (PGTs) synthesis. The existing configuration synthesis methods for the d-graphs of PGTs need rotation graphs (r-graphs) as the intermediate step and produce a large amount of isomorphic KCs. This paper proposes a method to obtain d-graphs directly from the geared graph. Meanwhile, a uniform isomorphism identification method suitable for parent graphs, geared graphs, and d-graphs is presented. Finally, a fully automatic method based on parent graphs is tested on synthesizing 1-DOF PGTs with up to nine links. Our synthesis results and those in the literature are comparatively analyzed, and the reasons for contradictory synthesis results are analyzed.

A new method for isomorphism identification of planetary gear trains

Planetary gear trains (PGTs) are widely used in machinery such as vehicles, pulley blocks, wrist watches, machine tools, and robots. During the process of structural synthesis of PGTs using graph theory, isomorphism identification of graphs is an important and complicated problem. The reliability of the isomorphism detection method directly determines the accuracy of the synthesis result. In this paper, a novel isomorphism identification method for PGTs is proposed. First, a new weighted adjacent matrix is presented to describe the topological graph of PGTs, which has is unique in describing the structure of PGTs. Then, the weighted distance matrix is proposed and the sum of the matrix is obtained, which can determine whether the planetary gear trains is isomorphic or not. Eventually, the examples demonstrate that this new method can be accurately and effectively performed.

Mechanism isomorphism identification based on artificial fish swarm algorithm

The aim of this paper is to propose a practical solution for mechanism kinematic chain isomorphism identification – an artificial fish swarm algorithm. The artificial fish model of mechanism isomorphism identification is established, and behavioral way of the artificial fish is designed. According to isomorphism identification features of topological graph, the process of mechanism isomorphism identification based on artificial fish swarm algorithm is confirmed. The rationality and reliability of artificial fish swarm algorithm on the isomorphic identification of mechanism have been illustrated by a specific example, which provides a new method for intelligent CAD system design of mechanism. It builds a basis for future work in isomorphism identification of mechanism with high efficiency. Isomorphic identification of mechanism will contribute to rational qualitative analysis of mechanism design, perfection of irrationality can be done timely, which is the key factor for mechanical manufacturing. In this paper, we introduce the mechanism kinematic chain firstly, then optimization of artificial fish swarm algorithm is illustrated, and it is shown that how fish swarm algorithm is applied to mechanism kinematic chain. Finally, the feasibility and efficiency of the method are verified by the example of 10 bars, and the complex mechanism can be identified by the example of 14 bars and 18 bars.