Kinematic Symmetry-Driven Multi-Objective Collaborative Design of a Rigid Crank–Rocker Mechanism

To address the persistent challenges in optimizing the transmission performance of crank-rocker mechanisms—namely, the inaccuracies of local static evaluation models, the non-linear coupling constraints among multiple objectives, and the difficulties of navigating discontinuous and restricted solution spaces—this paper proposes a multi-objective collaborative design methodology grounded in kinematic and dynamic analysis. First, full-cycle mathematical models for transmission efficiency and transmission inertia are established, explicitly quantifying the impact of quick-return characteristics on inertial forces. Second, targeting the maximization of transmission efficiency alongside the minimization of transmission inertia and kinematic asymmetry, an adaptive multi-objective genetic algorithm is developed. Using a bearing life testing machine as the engineering baseline, virtual prototype simulations and multi-load physical bench tests are conducted to validate the proposed approach. Post-optimization results indicate that the full-cycle average transmission efficiency of the mechanism surges significantly from 73.6% to 91.96%, while the transmission inertial force is drastically curtailed by 72.28%. Concurrently, the advance-to-return time ratio, an indicator of kinematic asymmetry, is reduced to 1.0229. Additionally, the torque fluctuations at the output shaft are notably mitigated, and the overall operational noise level is reduced by 4 to 6 dB. This research provides a highly effective theoretical and engineering paradigm for achieving the globally collaborative optimum of planar mechanisms under complex physical constraints.