New Approaches for the Determination of Specific Values for Process Models in Machining Using Artificial Neural Networks

被引：16
|
作者：
Arnold, F. [1 ]
Haenel, A. [1 ]
Nestler, A. [1 ]
Brosius, A. [1 ]
机构：
[1] Tech Univ Dresden, Inst Mfg Technol, Chair Forming & Machining Proc, Mommsenstr 13, D-01062 Dresden, Germany
来源：
27TH INTERNATIONAL CONFERENCE ON FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING, FAIM2017 | 2017年 / 11卷
关键词：
process data; Process forces; cutting force model; milling; data collection; artificial neural networks;
D O I：
10.1016/j.promfg.2017.07.277
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The acceptance of the use of mathematical models for the determination of process forces in machining is directly dependent on the quality of the used characteristic values. The approach of an automated data acquisition without the need of an additional force measuring system in the cutting machine is one possibility of a broader application. For the 2.5D milling process, a concept to determine the specific cutting forces k(c) by recording dynamic process data were developed. The specific values are further processed into an artificial neuronal network (ANN) with the aim to learn it. (c) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码：1463 / 1470
页数：8
相关论文
共 50 条
  • [1] New approaches to processing GIS Data using Artificial Neural Networks models
    Mihai, Dana
    [J]. ANNALS OF THE UNIVERSITY OF CRAIOVA-MATHEMATICS AND COMPUTER SCIENCE SERIES, 2021, 48 (02): : 358 - 373
  • [2] Using artificial neural networks for modeling surface roughness of wood in machining process
    Tiryaki, Sebahattin
    Malkocoglu, Abdulkadir
    Ozsahin, Stikrii
    [J]. CONSTRUCTION AND BUILDING MATERIALS, 2014, 66 : 329 - 335
  • [3] Alternative Approaches for Growth Models: Artificial Neural Networks
    Benzer, Recep
    Benzer, Semra
    [J]. 2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2018,
  • [4] Prediction of MEUF process performance using artificial neural networks and ANFIS approaches
    Rahmanian, Bashir
    Pakizeh, Majid
    Mansoori, Seyed Ali Akbar
    Esfandyari, Morteza
    Jafari, Dariush
    Maddah, Heidar
    Maskooki, Abdolmajid
    [J]. JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS, 2012, 43 (04) : 558 - 565
  • [5] Comparison of Bayesian networks and artificial neural networks for quality detection in a machining process
    Correa, M.
    Bielza, C.
    Pamies-Teixeira, J.
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (03) : 7270 - 7279
  • [6] Determination of Drying Characteristics of Timber by Using Artificial Neural Networks and Mathematical Models
    Ceylan, Ilhan
    [J]. DRYING TECHNOLOGY, 2008, 26 (12) : 1469 - 1476
  • [7] Automatic recognition of machining features using artificial neural networks
    V. B. Sunil
    S. S. Pande
    [J]. The International Journal of Advanced Manufacturing Technology, 2009, 41 : 932 - 947
  • [8] Performance estimation in wood machining using artificial neural networks
    Karri, V
    [J]. ADVANCED MANUFACTURING PROCESSES, SYSTEMS, AND TECHNOLOGIES (AMPST 96), 1996, : 271 - 279
  • [9] Automatic recognition of machining features using artificial neural networks
    Sunil, V. B.
    Pande, S. S.
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2009, 41 (9-10): : 932 - 947
  • [10] Determination of daily solar ultraviolet radiation using statistical models and artificial neural networks
    Barbero, F. J.
    Lopez, G.
    Batlles, F. J.
    [J]. ANNALES GEOPHYSICAE, 2006, 24 (08) : 2105 - 2114
12345