含能材料2012，Vol.20Issue(3)：355-358,4.DOI:10.3969/j.issn.1006-9941.2012.03.020
基于径向基神经网络的电火工品安全电流预测方法
Prediction Method of No-firing Current of Electric Explosive Device Based on RBF Neural Network
崔伟成 1刘林密 1孟凡磊1
作者信息
- 1. 海军航空工程学院飞行器工程系,山东烟台264001
- 折叠
摘要
Abstract
A prediction method of the no-firing current of electric explosive device was studied. The electric-thermal parameters of the electric explosive device such as resistance and heat loss coefficient were measured with the non-destructive transient pulse test system,then the heat loss coefficient was redeemed using the no-firing current measured by the Bruceton method. The no-firing current of the electric explosive device was predicated using the radial basis function (RBF) neural network. The results show that the predicted result is consistent with that measured with the firing validated test system,and the electric explosive device with the larger predicted value owns the larger firing probability. The mean predicted current equals to the firing current measured by the Bruceton method.关键词
军事化学与烟火技术/电火工品/径向基(RBF)神经网络/安全电流Key words
military chemistry and pyrotechnics/ electric explosive device/ radial basis function (RBF) neural network/ no-firing current分类
军事科技引用本文复制引用
崔伟成,刘林密,孟凡磊..基于径向基神经网络的电火工品安全电流预测方法[J].含能材料,2012,20(3):355-358,4.
