内燃机传动噪声识别的小波分析方法

为了降低内燃机噪声必须确定其噪声源。基于内燃机噪声信号非平稳和周期性的特点,用模拟数据说明了将小波分析应用于内燃机噪声信号分析的合理性,并利用连续小渡变换对一台车用发动机前、后端的噪声源进行了识别诊断,确定了发动机的噪声源,证明了小渡分析是内燃机噪声源识别的一种有效方法。     

基于小波分析和RBF神经网络的轴承故障诊断研究

为了提高轴承故障信号的诊断性能,采用小波分析和RBF神经网络相结合的方法对轴承振动信号进行故障分类。首先对轴承振动信号进行小波变化,采用软阈值去噪方法滤除振动信号噪声,然后对振动信号矩阵化处理,接着构建RBF神经网络,输入轴承振动信号特征向量,初始化权重和阈值,最后通过不断反向迭代得到稳定的RBF神经网络故障判别模型。实验证明：通过差异化设置隐藏层神经元数量,确定合适的RBF神经网络规模,经过小波去噪可以有效提高轴承故障判别准确率,相比于常见轴承故障分类算法,算法具有更高的故障判别准确率。     

空气_旋转阀脉冲燃烧器的性能试验研究

介绍了空气－旋转阀脉冲燃烧器试验装置,试验过程,并且通过试验得出了此种燃烧器的运行特性,探讨了进行流量对燃烧器压力、幅值、频率等参数的影响。通过对结果的分析,阐述了空气－旋转阀脉冲燃烧器的工作机理。     

Quo vadis Anionenextraktion?

Quo Vadis Anion Extraction? Reactive extraction processes represent efficient and smart technologies for separation and concentration of metal ions in solution. Despite the importance of anions in biology, medicine, environment and industry, practical examples of anion extraction are relatively limited compared to metal ion separation. Anion extraction processes are mainly based on the non‐specific ion‐pair formation with hydrophobic ammonium cations. In these processes the phase transfer of anions is dominated by their lipophilicity. The specific characteristics of anions in comparison to those of cations are closely connected to the difference in extraction processes for the two ion types. Novel approaches for specific binding and selective transport of anionic components are based both on the better understanding of the biological role of anions and on the possibilities of supramolecular chemistry to built up receptor architectures with complementary binding modes for anions. In the given review the authors discuss present research tendencies and application possibilities of new extractant types for separation and concentration of anionic species in solution.