摘要
为了对废弃弹药进行分类并安全处理,提出了基于数据融合技术的超声波检测弹体内部成份方法。应用超声检测仪采集大量弹体内部成份样本数据,运用数据融合技术建立神经网络融合模型,对超声波的首波、幅值、频率、增益等特征进行融和处理,从而判断弹药的种类。实验结果表明,该方法准确可靠,具有较高的推广应用价值。
To categories and safe disposal the abandoned ammunition, a design method of use ultrasonic to detect artillery shells＇interior ingredient based on data fusion method is presented.Firstly, a large number of sample data of ammunition internal component is obtined by ultrasonic detector, by using the data fusion method, the neural network fusion modle is built to fusion and handle the feature of the first wave amplitude, frequency, gain and other characteristics of integration, and eventually the distinction is realized.Experiments show that the method is accurate and reliable.
出处
《计算机工程与设计》
CSCD
北大核心
2009年第23期5513-5515,5520,共4页
Computer Engineering and Design
基金
国家自然科学基金项目(69873007)
关键词
废弃弹药
人工神经网络
超声波
数据融合
内部成份
abandoned ammunition
artificial neural networks
ultrasonic
data fusion
internal component
