高压工况下底排推进剂燃速的反向传播神经网络模型

张领科; 余永刚; 李志锋; 刘东尧

doi:10.11858/gywlxb.2012.02.015

高压工况下底排推进剂燃速的反向传播神经网络模型

doi: 10.11858/gywlxb.2012.02.015

1.
南京理工大学能源与动力工程学院，江苏南京 210094；
2.
中国人民解放军驻724厂军代室，辽宁沈阳 110045

详细信息

通讯作者:
张领科 E-mail:nustzlk@126.com

计量
- 文章访问数: 7444
- HTML全文浏览量: 423
- PDF下载量: 537
出版历程
- 收稿日期: 2010-06-18
- 修回日期: 2010-11-20
- 发布日期: 2012-04-15

Back Propagation Neural Networks of Base Bleed Propellant Burning Rate under High Pressure Condition

1.
School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, China;
2.
PLA Military Representative Office in 724 Factory, Shenyang 110045, China

摘要

摘要: 为了研究底排推进剂在火炮膛内随弹丸运动时的燃烧特性，采用密闭爆发器仿真实验技术，针对底排推进剂在膛内高压工况下的燃烧特性进行实验研究，获得了两种不同装填密度下平均压力随时间变化的关系，并对压力进行了全程热散失修正。采用多次平滑、滤波数据处理技术和发射药燃速处理方法，得到了燃速与压力（8~150 MPa）之间的关系。基于实验数据特征样本，建立并训练得到了底排推进剂高压工况下的反向传播（Back Propagation）神经网络燃速模型，该模型与传统的指数模型相比，具有拟合精度高和稳定性强的特点。
- 底排推进剂 /
- 高压 /
- 反向传播神经网络 /
- 燃速
Abstract: To investigate the combustion characteristics of base bleed propellant moving with the projectile in the gun bore, the closed bomb semi-physical and experimental simulation technology was employed. The combustion property under the condition of simulative high pressure in the gun bore was studied. Two average pressure-time curves corrected by heat loss were obtained under different charge density of the closed bomb. The correlation data between burning rate and pressure (8－150 MPa) were processed by smoothing, filtering and data transformation. The burning rate model adopting back propagation (BP) neural networks describing, which is suitable for high combustion pressure condition, was built based on training data samples. Comparing with the exponential burning rate model, the BP neural networks burning rate model of base bleed propellant has higher fitting precision and stronger robust.
- base bleed propellant /
- high pressure /
- back propagation neural networks /
- burning rate

HTML全文

参考文献(22)

Moore F G. An improved semiempirical method for power-on base drag prediction [A]//Proceedings of the AIAA Atmospheric Flight Mechanics Conference [C]. Montreal, Canada, 2001: 4328.

Guo X F. Exterior Ballistics of Base Bleed Projectile [M]. Beijing: National Defence Industry Press, 1995. (in Chinese)

郭锡福. 底部排气弹外弹道学 [M]. 北京: 国防工业出版社, 1995.

Miller M S, Holmes H E. An experimental determination of subatomospheric burning rates and critical diameters for AP/HTPB propellant [A]//Proceedings of the 1987 JANNAF Combustion Meeting [C]. Monterry, California, US, 1987.

Cui Y L, Ma H W, Zhang Y Q, et al. The method to study the combustion behavior of the base bleed projectile by using flash X-ray high photography [J]. Journal of Ballistics, 2002, 14(2): 93-96. in Chinese)

崔艳丽, 马宏伟, 张炎清, 等. 利用X光高速摄影研究底排药剂燃烧特性 [J]. 弹道学报, 2002, 14(2): 93-96.

Lu C Y. Study on characteristics of unstable combustion of base bleed unit [D]. Nanjing: Nanjing University of Science and Technology, 2009. (in Chinese)

陆春义. 底排装置强非稳态燃烧特性研究 [D]. 南京: 南京理工大学, 2009.

Huang Z Y, Wang Z S, Zhang Y B. Regularity of burning rate pressure exponent for propellant [J]. Chinese Journal of Energetic Material, 2006, 14(2): 123-126. (in Chinese)

黄振亚, 王泽山, 张远波. 发射药燃速压力指数变化规律的研究 [J]. 含能材料, 2006, 14(2): 123-126.

Vasile T, Barb C, Safta D. Regarding the determination of exponent from burning rate law of powder using the closed bomb data [A]. New Trends in Research of Energetic Materials [C]. Pardubice: Universtiy of Pardubice, 2005: 20.

Ghosh A K, Singhal A, Jha A. Flight path prediction of an artillery shell using feed forward neural networksl [A]//Proceedings of the AIAA Atmospheric Flight Mechanics Conference [C]. Austin, Texas, US, 2005: 11-14.

Liu J M, Tang S C, Xu F M, et al. Prediction of burning rate of HTPB propellant by artificial neural network model [J]. Chinese Journal of Explosives and Propellants, 2006, 29(3): 13-16. (in Chinese)

刘建民, 唐少春, 徐复铭, 等. 基于ANN的丁羟复合推进剂燃速预测 [J]. 火炸药学报, 2006, 29(3): 13-16.

Guan H Z, Zou R R. Experimental Interior Ballistics [M]. Beijing: Weapon Industry Press, 1997. (in Chinese)

官汉章, 邹瑞荣. 实验内弹道学 [M]. 北京: 兵器工业出版社, 1997.

Ying S J, Xiao Z G, Xu F M. A new correcting method for pressure curve in the whole burning process of propellants in closed bomb test [J]. Chinese Journal of Explosives and Propellants, 2007, 30(4): 62-64. (in Chinese)

应三九, 肖正刚, 徐复铭. 密闭爆发器实验中发射药燃烧全过程压力曲线的修正方法 [J]. 火炸药学报, 2007, 30(4): 62-64.

Simon H. Theory of Neural Networks [M]. Translated by Ye S W, Shi Z Z. Beijing: China Machine Press, 2004. (in Chinese)

Simon H. 神经网络原理 [M]. 叶世伟, 史忠植, 译. 北京: 机械工业出版社, 2004.

Dong C H. Matlab Neural Network and Application [M]. Beijing: National Defence Industry Press, 2005. (in Chinese)

董长虹. Matlab神经网络与应用 [M]. 北京: 国防工业出版社, 2005.

施引文献

资源附件(0)

访问统计