Prediction of Heating-Line Paths in Induction Heating Process using the Artificial Neural Network

被引：6
|
作者：
Nguyen, Truong-Thinh [1 ]
Yang, Young-Soo [1 ]
Kim, Ki-Seong [2 ]
Hyun, Chung-Min [3 ]
机构：
[1] Chonnam Natl Univ, Dept Mech Engn, Kwangju 500757, South Korea
[2] Chonnam Natl Univ, Div Mech & Automot Engn, Yeosu 550749, Jeonnam, South Korea
[3] Samsung Heavy Ind Co Ltd, Geoje 656710, Gyeongnam, South Korea
来源：
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING | 2011年 / 12卷 / 01期
关键词：
Back-propagation; Neural network; Induction heating; Line heating; Forming plate;
D O I：
10.1007/s12541-011-0013-z
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper presents the development of a back propagation neural network model for the prediction of heating-line positions in induction heating process. The vertical displacements of plate have been considered as the input parameters and the selected induction heating lines as output parameters to develop the model. The training patterns of neural network are obtained using an analytical solution that predicts plate deformations in induction heating process. The feasibility test reveals that the developed method can be used to determine the heating-line positions in line heating process.
引用
收藏
页码：105 / 113
页数：9
相关论文
共 50 条
  • [31] On-line Voltage Instability Prediction using an Artificial Neural Network
    Hagmar, Hannes
    Le Anh Tuan
    Carlson, Ola
    Eriksson, Robert
    2019 IEEE MILAN POWERTECH, 2019,
  • [32] INDUCTION HEATING IN EPITAXIAL PROCESS
    EMERSON, WA
    SEMICONDUCTOR PRODUCTS AND SOLID STATE TECHNOLOGY, 1967, 10 (10): : 50 - &
  • [33] Prediction Performance Analysis of Artificial Neural Network Model by Input Variable Combination for Residential Heating Loads
    Lee, Chanuk
    Jung, Dong Eun
    Lee, Donghoon
    Kim, Kee Han
    Do, Sung Lok
    ENERGIES, 2021, 14 (03)
  • [34] Application of metaheuristic based artificial neural network and multilinear regression for the prediction of higher heating values of fuels
    Aladejare, Adeyemi Emman
    Onifade, Moshood
    Lawal, Abiodun Ismail
    INTERNATIONAL JOURNAL OF COAL PREPARATION AND UTILIZATION, 2022, 42 (06) : 1830 - 1851
  • [35] Prediction of end milling process parameters using artificial neural network
    Parmar, Jignesh G.
    Dave, K. G.
    Gohil, A., V
    Trivedi, H. S.
    MATERIALS TODAY-PROCEEDINGS, 2021, 38 : 3168 - 3176
  • [36] INDUCTION HEATING SPEEDS FORGING LINE
    BURRETT, C
    METALLURGIA AND METAL FORMING, 1975, 42 (10): : 349 - 352
  • [37] An artificial neural network model for predicting building heating and cooling loads
    Nwulu, Nnamdi I.
    2017 INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (IDAP), 2017,
  • [38] Pseudo dynamic transitional modeling of building heating energy demand using artificial neural network
    Paudel, Subodh
    Elmtiri, Mohamed
    Kling, Wil L.
    Le Corre, Olivier
    Lacarriere, Bruno
    ENERGY AND BUILDINGS, 2014, 70 : 81 - 93
  • [39] Algorithm for optimal application of the setback moment in the heating season using an artificial neural network model
    Moon, Jin Woo
    Jung, Sung Kwon
    ENERGY AND BUILDINGS, 2016, 127 : 859 - 869
  • [40] Heating and cooling potential of an earth-to-air heat exchanger using artificial neural network
    Kumar, R
    Kaushik, SC
    Garg, SN
    RENEWABLE ENERGY, 2006, 31 (08) : 1139 - 1155
12345