Abstract
Existing assembly analysis methods often fail to accurately capture the complexities involved in the precision assembly of real-world parts. This paper introduces an advanced precision assembly error analysis method based on multi-constraint surface matching, aimed at overcoming these limitations. The proposed approach incorporates interference-free constraints and force stability constraints to develop an assembly positioning model that better reflects the realistic assembly process. To solve the model, Spatial Pyramid Matching with chaotic mapping is employed for population initialization, thereby enhancing population diversity. A nonlinear control mechanism is further introduced to dynamically adjust inertia weight, and a simulated annealing mechanism is integrated into the particle swarm optimization algorithm to enhance the efficiency of the surface matching process. The method ultimately achieves high-precision multi-constraint surface matching and completes a comprehensive assembly error analysis. The effectiveness and enhanced performance of the proposed methodology are validated through the precision assembly of a vibratory bowl feeder, demonstrating its potential to significantly improve assembly accuracy in precision manufacturing contexts.
Published Version
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