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Analog-Circuit Model of FGH96 Superalloy Hot Deformation Behaviors Based on Artificial Neural Network

基于ANN的FGH96合金热变形行为的模拟电路模型(英文)
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摘要 At the present time, numerical models (such as, numerical simulation based on FEM) adopted broadly in technological design and process control in forging field can not implement the realtime control of material forming process. It is thus necessary to establish a dynamic model fitting for the real-time control of material deformation processing in order to increase production efficiency, improve forging qualities and increase yields. In this paper, hot deformation behaviors of FGH96 superalloy are characterized by using hot compressive simulation experiments. The artificial neural network (ANN) model of FGH96 superalloy during hot deformation is established by using back propagation (BP) network. Then according to electrical analogy theory, its analog-circuit (AC) model is obtained through mapping the ANN model into analog circuit. Testing results show that the ANN model and the AC model of FGH96 superalloy hot deformation behaviors possess high predictive precisions and can well describe the superalloy's dynamic flow behaviors. The ideas proposed in this paper can be applied in the real-time control of material deformation processing. At the present time, numerical models (such as, numerical simulation based on FEM) adopted broadly in technological design and process control in forging field can not implement the realtime control of material forming process. It is thus necessary to establish a dynamic model fitting for the real-time control of material deformation processing in order to increase production efficiency, improve forging qualities and increase yields. In this paper, hot deformation behaviors of FGH96 superalloy are characterized by using hot compressive simulation experiments. The artificial neural network (ANN) model of FGH96 superalloy during hot deformation is established by using back propagation (BP) network. Then according to electrical analogy theory, its analog-circuit (AC) model is obtained through mapping the ANN model into analog circuit. Testing results show that the ANN model and the AC model of FGH96 superalloy hot deformation behaviors possess high predictive precisions and can well describe the superalloy's dynamic flow behaviors. The ideas proposed in this paper can be applied in the real-time control of material deformation processing.
出处 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2005年第1期90-96,共7页 中国航空学报(英文版)
基金 AeronauticalScienceFoundationofChina (0 3H5 3 0 48) DoctorateCreationFoundationofNorthwesternPolytechnicalUni versity (2 0 0 2 12 )
关键词 FGH96 superalloy flow behavior artificial neural network(ANN) analog-circuit FGH96 superalloy flow behavior artificial neural network(ANN) analog-circuit
作者简介 LIU Yu-hong Born in 1971, she is now a postgraduate of Northwestern Polytechnical University and is doing the study of her dissertation for the Degree of Ph. D., Her research specialty is reliability design and intelligence controlling in plastic deformation. She has published several scientific papers in various periodicals. E-mail: nwpulyh587@sina. com
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