Evaluation of kinematic chains topological performance based on the PEKC-EAID index

During the initial stages of structural design, understanding the topological properties of simple kinematic chains can significantly enhance structural synthesis efficiency and mechanical configuration performance. Currently, most methods for evaluating kinematic chains performance offer limited effectiveness and low efficiency, requiring manual calculations that make it difficult to provide comprehensive evaluation results quickly. However, in the field of kinematic chains isomorphism detection, a molecular topology index method can efficiently characterize the topological structure of kinematic chains. Inspired by this approach, this study integrates multiple design invariants of kinematic chains to establish an evaluation model based on the number of links and degrees of freedom. The static and dynamic characteristics of kinematic chains are characterized by the magnitude of the Performance Evaluation Kinematic Chains-Extended Feature Adjacency Identification Index (PEKC-EAID). The validity of this evaluation model is validated through three types of kinematic chains: simple joint chains, compound joint chains, and gear train chains. Based on the adjacency matrix, the developed Matlab algorithm efficiently computes the PEKC-EAID index. This index demonstrates high discriminative efficiency in structural conceptual design, guiding the prioritization of structural characteristics and serving as an ideal tool for mechanism innovation.