A volume decomposition approach to machining feature extraction of casting and forging components

被引:24
|
作者
Kailash, SB [1 ]
Zhang, YF [1 ]
Fuh, JYH [1 ]
机构
[1] Natl Univ Singapore, Dept Engn Mech, Singapore 119260, Singapore
关键词
feature extraction; process mapping; casting and forging parts;
D O I
10.1016/S0010-4485(00)00107-X
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This paper reports a method for machining feature extraction of forging and casting components. it employs a volume decomposition approach to map machining removal faces into machining processes. The geometric reasoning from the characteristic surfaces produced by machining operations forms the basis of the recognition process. There are three phases in the mapping process: (1) Boolean decomposition of the final part model and raw part model; (2) identification of machined faces (M faces) and concatenation of M-faces into groups (M-group); and (3) mapping M-groups into all feasible machining process types. This recognition technique is process oriented, which is able to overcome the limitation of new feature additions. This approach is also able to deal with some types of feature intersecting. The results can be used directly for process planning of complicated geometric parts, e.g. casting and forging components. (C) 2001 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:605 / 617
页数:13
相关论文
共 50 条
  • [41] An incremental approach to converting design feature model to machining feature model
    Chen, ZM
    Ma, J
    Gao, SM
    Peng, QS
    CAD/GRAPHICS '2001: PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON COMPUTER AIDED DESIGN AND COMPUTER GRAPHICS, VOLS 1 AND 2, 2001, : 769 - 774
  • [42] A Novel Approach for Automatic Machining Feature Recognition with Edge Blend Feature
    Keong, Chen Wong
    Yusof, Yusri
    8TH INTERNATIONAL CONFERENCE ON MECHANICAL AND MANUFACTURING ENGINEERING 2017 (ICME'17), 2017, 135
  • [43] Efficient sculptured pocket machining using feature extraction and conversion
    Joo, J
    Cho, H
    JOURNAL OF MANUFACTURING SYSTEMS, 1999, 18 (02) : 100 - 112
  • [44] Flow Control Based on Feature Extraction in Continuous Casting Process
    Abouelazayem, Shereen
    Glavinic, Ivan
    Wondrak, Thomas
    Hlava, Jaroslav
    SENSORS, 2020, 20 (23) : 1 - 18
  • [45] An approach for the impact feature extraction method based on improved modal decomposition and singular value analysis
    Bie, Fengfeng
    Horoshenkov, Kirill V.
    Qian, Jin
    Pei, Junfeng
    JOURNAL OF VIBRATION AND CONTROL, 2019, 25 (05) : 1096 - 1108
  • [46] The effect of forging texture and machining parameters on the fatigue performance of titanium alloy disc components
    Fernandez, Daniel Suarez
    Wynne, B. P.
    Crawforth, P.
    Fox, K.
    Jackson, M.
    INTERNATIONAL JOURNAL OF FATIGUE, 2021, 142
  • [47] A Dual Decomposition Approach to Feature Correspondence
    Torresani, Lorenzo
    Kolmogorov, Vladimir
    Rother, Carsten
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (02) : 259 - 271
  • [48] Volume decomposition and feature recognition .1. Objects
    Sakurai, H
    COMPUTER-AIDED DESIGN, 1995, 27 (11) : 833 - 843
  • [49] P/M REPLACES COMPONENTS MADE BY INVESTMENT-CASTING, MACHINING AND STAMPING
    JOHNSON, PK
    INTERNATIONAL JOURNAL OF POWDER METALLURGY, 1982, 18 (04): : 355 - 359
  • [50] A feature extraction and deep learning approach for network traffic volume prediction considering detector reliability
    Zou, Xiexin
    Chung, Edward
    Zhou, Yue
    Long, Meng
    Lam, William H. K.
    COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2024, 39 (01) : 102 - 119