引用本文: | 张云,杜琴,王竟成,等.弹药贮存微环境温度智能化预测[J].国防科技大学学报,2024,46(1):204-211.[点击复制] |
ZHANG Yun,DU Qin,WANG Jingcheng,et al.Intelligent prediction model for ammunition storage microenvironment temperature[J].Journal of National University of Defense Technology,2024,46(1):204-211[点击复制] |
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弹药贮存微环境温度智能化预测 |
张云,杜琴,王竟成,张志明,谢兰川,陈阳 |
(西南技术工程研究所, 重庆 400039)
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摘要: |
高效、准确获取弹药贮存微环境温度变化规律是开展弹药寿命评估与延寿的关键。结合神经网络算法以及传热学原理,研究了弹药贮存微环境温度预测模型,并基于此模型开发了一套弹药包装箱微环境预测软件,用以预测不同气候环境下包装箱内部的温度变化。在敦煌、漠河进行了相关试验,用以验证软件预测正确性以及参数优化。结果表明:应用基于神经网络算法开发的包装箱微环境预测软件,根据不同包装箱材料,调控贮存地点以及控制贮存起始温度,可以实现对箱内温度的控制。 |
关键词: 弹药贮存 BP神经网络 微环境温度 预测模型 |
DOI:10.11887/j.cn.202401022 |
投稿日期:2021-09-15 |
基金项目: |
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Intelligent prediction model for ammunition storage microenvironment temperature |
ZHANG Yun, DU Qin, WANG Jingcheng, ZHANG Zhiming, XIE Lanchuan, CHEN Yang |
(Southwest Technology and Engineering Research Institute, Chongqing 400039, China)
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Abstract: |
It is the key for evaluating and prolonging the life of ammunition to acquire the temperature variation law of ammunition storage microenvironment efficiently and accurately. With the help of the neural network and the heat transfer theory, a model for predicting the microenvironment of ammunition storage was studied, and based on the model, a set of ammunition packaging box prediction software was developed to predict the temperature changes inside the box under different climatic environment. Relevant test was progressed to verify the software correctness and parameter optimization in Dunhuang and Mohe. Results show that with the help of the microenvironment prediction software of packing box developed on the basis of the neural networks algorithm, the microenvironment temperature control can be achieved by adjusting the storage location and storage initial temperature according to different packaging box materials. |
Keywords: ammunition storage BP neural network microenvironment temperature prediction model |
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