Modelling of abrasive flow machining process: a neural network approach

被引：75
|
作者：
Jain, RK
Jain, VK [1 ]
Kalra, PK
机构：
[1] Indian Inst Technol, Dept Mech Engn, Kanpur 208016, Uttar Pradesh, India
[2] Indian Inst Technol, Dept Elect Engn, Kanpur 208016, Uttar Pradesh, India
来源：
WEAR | 1999年 / 231卷 / 02期
关键词：
surface roughness; abrasive flow machining; neural networks;
D O I：
10.1016/S0043-1648(99)00129-5
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
A simple neural network model for abrasive flow machining process has been established. The effects of machining parameters on material removal rate and surface finish have been experimentally analysed. Based on this analysis, model inputs and outputs were chosen and off-line model training using back-propagation algorithm was carried out. Simulation results confirm the feasibility of this approach and show a good agreement with experimental and theoretical results for a wide range of machining conditions. Learning could remarkably be enhanced by training the network with noise injected inputs. (C) 1999 Published by Elsevier Science S.A. All rights reserved.
引用
收藏
页码：242 / 248
页数：7
相关论文
共 50 条
  • [21] Abrasive jet machining of glass: Experimental investigation with artificial neural network modelling and genetic algorithm optimisation
    Abdelnasser, El Shimaa
    Elkaseer, Ahmed
    Nassef, Ahmed
    COGENT ENGINEERING, 2016, 3 (01):
  • [22] GREY RELATION APPROACH IN ABRASIVE JET MACHINING PROCESS
    Paul, Lijo
    Babu, J.
    PROCEEDINGS OF THE ASME 14TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2019, VOL 2, 2019,
  • [23] ABRASIVE FLOW MACHINING
    RHOADES, LJ
    MANUFACTURING ENGINEERING, 1988, 101 (05): : 75 - 78
  • [24] Analysis and validation of erosion process for sea sand as an abrasive material by using Regression model and Neural Network in Abrasive Jet machining process for Alumina
    Pawar, N. S.
    Lakhe, R. R.
    Shrivastava, R. L.
    DYNAMICS OF MACHINES AND MECHANISMS, INDUSTRIAL RESEARCH, 2014, 592-594 : 854 - +
  • [25] An evolutionary neural network approach to machining process planning: A proof of concept
    Chen, Niechen
    49TH SME NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE (NAMRC 49, 2021), 2021, 53 : 690 - 696
  • [26] Modelling the Cutting Process and Cutting Performance in Abrasive Waterjet Machining Using Genetic-Fuzzy Approach
    Aultrin, K. S. Jai
    Anand, M. Dev
    Jose, P. Jerald
    INTERNATIONAL CONFERENCE ON MODELLING OPTIMIZATION AND COMPUTING, 2012, 38 : 4013 - 4020
  • [27] Specific energy and temperature determination in abrasive flow machining process
    Jain, RK
    Jain, VK
    INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2001, 41 (12): : 1689 - 1704
  • [28] Definition of edges in correlation to abrasive flow machining as a finishing process
    Groeger, S.
    Segel, F.
    Uhlmann, E.
    Rosskamp, S.
    SURFACE TOPOGRAPHY-METROLOGY AND PROPERTIES, 2018, 6 (03):
  • [29] Development of Hybrid Forms of Abrasive Flow Machining Process: A Review
    Bhardwaj, Anant
    Ali, Parvesh
    Walia, R. S.
    Murtaza, Qasim
    Pandey, S. M.
    ADVANCES IN INDUSTRIAL AND PRODUCTION ENGINEERING, 2019, : 41 - 67
  • [30] Wall-slip characteristics of viscoelastic abrasive medium in abrasive flow machining process
    Fan, Wulin
    Sun, Yuli
    Su, Qinghuai
    Zhao, Jianshe
    Yang, Fanxuan
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2023, 127 (1-2): : 253 - 261
12345