Rotating mechanical equipment virtual assembly model and method based on context awareness

Abstract

The invention discloses a rotating mechanical equipment virtual assembly model and method based on context awareness. A virtual assembly task is decomposed into an assembly knowledge layer, an assembly decision-making layer and a user control layer. The layers are endowed with different responsibilities. The virtual assembly model is defined for the assembly knowledge layer for containing assembly knowledge and assembly semantics to achieve contextualization of virtual assembly. Each part of the decision-making layer is regarded as an independent Agent, communication templates and decision-making rules between the Agents are defined according to the characteristics of the virtual assembly process, and user guide regularization is achieved. Through an offline clustering algorithm, the position and orientation of a user under a specific assembly situation are predicted, and time spent on adjusting a camera by the user is shortened. Compared with an existing assembly sensing technology, the model and method have the advantages that the assembly model is low in weight, interaction intelligence is achieved, and the interaction efficiency is high, and the assembly process can be customized to guide user operation.

Description

Technical field [0001] The invention relates to the technical field of virtual assembly simulation of large-scale rotating machinery equipment, in particular to a virtual assembly model and assembly method of rotating machinery equipment based on context perception. Background technique [0002] Virtual reality technology has the characteristics of immersion, interactivity and imagination. Virtual assembly technology is a typical application of virtual reality technology, which is widely used in product design verification and computer-aided assembly planning. Virtual perception technology is an important part of the virtual assembly system, which can reduce the user's cognitive burden on virtual scene information, and interact with the three-dimensional scene accurately and conveniently in the virtual scene. [0003] The existing virtual assembly perception mechanisms are commonly used: geometric constraints for feature matching and semantic constraints for task guidance. The ge...

AI Technical Summary

Problems solved by technology

The density-based clustering algorithm determines the cluster center by calculating the density of all sample points, but there is a problem that the density radius is difficult to determine

Hierarchical clustering initially regards each sample point as a class, and merges each class layer by layer according to certain conditions until the stop condition. Hierarchical clustering algorithms have a problem with a relatively large amount of computation.

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