In order to solve the problems such as completeness and following performance of product model information in process of virtual assembly, a process-oriented virtual assembly model for product information is proposed in this paper. It applies attribute frame to constitute the mapping of geometry topology information and non-geometry information, and basis for information granularity, the structure of multi-layer representation for assembly model information is constructed by framework of tree structure. It can satisfy the requirements of representation completeness, dynamic following and real-time requirements in virtual assembly. A modeling system was established and its feasibility was verified by research result.
For the degree of thermal deformation nonlinear is high and difficult to predict, fuzzy neural network modeling (FNN) based on Takagi-Sugeno model was applied to the NC machine tool thermal error modeling thus the complete thermal error fuzzy neural network mathematical model on NC machine tool was established and network parameters initialization and learning method were discussed. Thermal error experiment was conducted on large NC gantry rail grinder spindle box system and two independent groups of spindle thermal error data were collected, one was used to establish thermal error fuzzy neural network prediction model and another one was used to verify the prediction accuracy of this model. The test results show that fuzzy neural network model has high prediction accuracy.
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