Method for STEP-NC manufacturing feature recognition based on STEP and improved neural network

ZHANG Yu; DONG Xiaoye; LI Dongsheng; ZENG Qifeng; YANG Shuhua; GONG Yadong

doi:10.7527/S1000-6893.2018.22687

ACTA AERONAUTICAET ASTRONAUTICA SINICA >

2019 , Vol. 40 >Issue 7: 422687 - 422687

DOI: https://doi.org/10.7527/S1000-6893.2018.22687

Material Engineering and Mechanical Manufacturing

Method for STEP-NC manufacturing feature recognition based on STEP and improved neural network

ZHANG Yu ,
DONG Xiaoye ,
LI Dongsheng ,
ZENG Qifeng ,
YANG Shuhua ,
GONG Yadong

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1. School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China;
2. Shenyang Blower Works Group Corporation, Shenyang 110869, China

Received date: 2018-09-18

Revised date: 2018-10-18

Online published: 2018-12-19

Supported by

National Natural Science Foundation of China (51205054);China Postdoctoral Science Foundation(2017M611245); the Fundamental Research Funds for the Central Universities (N180313010, N160304009); Postdoctoral Fund of Northeastern University

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Abstract

Feature recognition is an important step to implement STEP-NC theory and a key to realize the open, intelligent and networked STEP-NC CNC system. A feature recognition method based on STEP and improved neural network for STEP-NC manufacturing features is presented in this paper. This method first extracts the geometric and topological information from the STEP AP203 file of a part, and builds the minimum subgraph of the part based on the judgment of the convexity of edges. Then, an improved BP neural network is proposed by combining the chaos algorithm, the genetic algorithm, and the BP neural network algorithm. Finally, by inputting the information data from the minimum subgraph of the part to the improved BP neural network, efficient and accurate feature recognition for STEP-NC manufacturing features in the part is achieved. The validity and feasibility of the proposed method are verified by two case studies.

Key words： STEP-NC; feature recognition; STEP AP203 file; minimum subgraph; improved (BP) neural network

Cite this article

ZHANG Yu , DONG Xiaoye , LI Dongsheng , ZENG Qifeng , YANG Shuhua , GONG Yadong . Method for STEP-NC manufacturing feature recognition based on STEP and improved neural network[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2019 , 40(7) : 422687 -422687 . DOI: 10.7527/S1000-6893.2018.22687

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