Three-dimensional CAD model intelligent classification method based on improved deep residual network

Abstract

The invention discloses a three-dimensional CAD model intelligent classification method based on an improved depth residual network, and the method comprises the steps of representing a model througha plurality of views of a three-dimensional CAD model, carrying out the data enhancement on the views to obtain a multi-view data set, and further obtaining a training data set through the gray scaletransformation and the normalization processing; importing the training data set into an improved deep residual network for training, and storing the trained network; when classification is needed, obtaining and preprocessing one or more views of any size of the new model, further calling the trained network to recognize the input views, and finally obtaining the category with the highest score after the average value of all view recognition results as the category to which the model belongs. According to the present invention, by adopting the improved deep residual network, the intelligent classification of the three-dimensional CAD model is achieved, and the method has the advantages of being flexible and convenient in classification input, high in classification accuracy, good in practicability, high in intelligent degree and the like.

Description

technical field [0001] The invention belongs to the field of intelligent information technology of advanced manufacturing technology, and in particular relates to an intelligent classification method for three-dimensional CAD models based on an improved deep residual network. Background technique [0002] With the vigorous development and wide application of CAD technology, enterprises have accumulated massive 3D CAD models. The 3D CAD model provides a wealth of case resources for the development of new products because it carries a large amount of topology knowledge, principle semantic knowledge, process knowledge, etc. In the process of new product development, reusing the existing 3D CAD model of the enterprise and its embedded knowledge such as process documents, fixtures and product operation plans can not only improve product quality and research and development efficiency, shorten the product development cycle, but also promote enterprise personnel. Learning and insp...

AI Technical Summary

Problems solved by technology

Although the above method solves many problems caused by manual archiving to a certain extent, the practicability of the above method is poor due to the complexity of the descriptor construction; secondly, because the constructed descriptor misses some information of the 3D CAD model, resulting in Its classification accuracy is not high

Therefore, the business community and industry still lack a practical, accurate and intelligent 3D CAD model classification method

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