Position tolerance optimization of assembly of hydraulic torque converter under virtual assembly

DOI:	10.11809/bqzbgcxb2023.12.012
Keywords:	virtual reality aided assembly; hydraulic torque converter; radial circular runout; tolerance analysis; improved adaptive genetic algorithm; assembly tolerance optimization
Abstract:	The tolerance of the hydraulic torque converter assembly, that is, the radial circular runout of the oil distribution sleeve, is the key performance indicator which reflects whether the hydraulic torque converter can work at high speed. The radial runout of the oil distribution sleeve is not only affected by the tolerance distribution of the parts, but also by the assembly sequence. Although virtual reality aided assembly can be used for design for assembly of products, the lack of tolerance information can not reflect the assembly quality of actual products. Based on the Unity3D rendering engine, a virtual assembly aided tolerance optimization system has been established that integrates four modules of 3D information annotation, tolerance analysis, tolerance optimization, and experimental verification. This system can establish the assembly sequence of the hydraulic torque converter with human machine interaction, where the practical engineering experience of the operators can be used. It also includes a tolerance optimization model aimed at improving assembly accuracy, limiting assembly costs and quality losses. In response to the problem of adaptive genetic algorithms being prone to local optima, the improved adaptive genetic algorithm is provided by adjusting the cross probability and mutation probability values based on population fitness, moreover, the Monte Carlo method is included to predict the radial circular runout of torque converter. The virtual assembly experiment of hydraulic torque converter shows that the system can optimize the parts’ tolerance values of hydraulic torque converter, predict the radial circular runout of different assembly sequences, and improve the tolerance design efficiency.
Issue:	Vol. 44 No. 12 (2023)
Published:	2023-12-28
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