Machining feature recognition method for machining process facing plate parts

被引：0

作者：

Liu, Xiao-Jun ^{[1
,2
]}

Ni, Zhong-Hua ^{[1
,2
]}

Cheng, Ya-Long ^{[1
,2
]}

Liu, Jin-Feng ^{[1
,2
]}

机构：

[1] Jiangsu Provincial Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, Southeast University

[2] School of Mechanical Engineering, Southeast University

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2013年 / 19卷 / 12期

关键词：

Feature recognition; Feature volume extraction; Machining feature recognition; Main processing surface; Plate parts;

D O I：

10.13196/j.cims.2013.12.liuxiaojun.3130.9.20131225

中图分类号：

学科分类号：

摘要：

To realize the intelligent recognition of plate parts' machining features and to accelerate the design speed of 3D machining technique, the machining feature recognition method for the plate parts machining process was researched. Through considering the permeability and openness, the machining feature was divided into five types of All Open Machining Feature (AOMF), Semi-Open Machining Feature (SOMF), Blind Closed Machining Feature (BCMF), Through Closed Machining Feature (TCMF) and Through Semi-Open Machining Feature (TSOMF). The principles of machining feature recognition process was introduced, and the recognition strategies based on the main processing surface was proposed. The recognition process was elaborated in detail, which included the key steps such as type discrimination, feature ambiguity processing and feature extraction. An integration system of CAD/CAPP for plate parts was developed, and two plate parts were used to verify the validity and correctness of the proposed method.

引用

页码：3130 / 3138

页数：8

共 25 条

[1]

Zeng Y., Research on important technologies for computer integrated manuafeturing system, (2006)

[2]

Zhou X., Qiu Y., Hua G., Et al., A feasible approach to the integration of CAD and CAPP, Computer-Aided Design, 39, 4, pp. 324-338, (2007)

[3]

Ding L., Matthews J., A contemporary study into the application of neural network techniques employed to automate CAD/CAM integration for die manufacture, Computers & Industrial Engineering, 57, 4, pp. 1457-1471, (2009)

[4]

Babic B., Nesic N., Miljkovic Z., A review of automated feature recognition with rule-based pattern recognition, Computers in Industry, 59, 4, pp. 321-337, (2008)

[5]

Donaldson I.A., Corney J.R., Rule-based feature recognition for 2.5d machined components, International Journal of Computer Integrated Manufacturing, 6, 1-2, pp. 51-64, (1993)

[6]

Lockett H.L., Guenov M.D., Graph-based feature recognition for injection moulding based on a mid-surface approach, Computer-Aided Design, 37, 2, pp. 251-262, (2005)

[7]

Mokhtar A., Xu X., Lazcanotegui I., Dealing with feature interactions for prismatic parts in STEP-NC, Journal of Intelligent Manufacturing, 20, 4, pp. 431-445, (2009)

[8]

Han J.H., Pratt M., Regli W.C., Manufacturing feature recognition from solid models: A status report, Ieee Transactions on Robotics and Automation, 16, 6, pp. 782-796, (2000)

[9]

Woo Y., Sakurai H., Recognition of maximal features by volume decomposition, Computer-Aided Design, 34, 3, pp. 195-207, (2002)

[10]

Kailash S.B., Zhang Y.F., Fuh J.Y.H., A volume decomposition approach to machining feature extraction of casting and forging components, Computer-Aided Design, 33, 8, pp. 605-617, (2001)

← 1 2 3 →