摘要
水轮机尾水管中涡带引起的压力脉动,对水轮机的稳定运行有重要的影响。在对尾水管压力脉动检测信号进行小波分析的基础上,采用自组织人工神经神经网络,对尾水管压力脉动状态进行识别。实例分析结果表明,基于自组织人工神经网络的尾水管压力脉动状态的识别方法,在样本数目比较少的情况下,能够获得满意的结果,可以应用于水轮机的运行状态分析中。
Pressure fluctuation caused by the vortices in the draft tube of the water turbine has an important impact on the stable operation of the turbine. Based on the analytical signal detected from the pressure fluctuation in the draft tube, this paper uses the self -organizing neural networks to identify the pressure fluctuation in the draft tube. An experimental result shows that the method based on self-organizing neural networks can get a satisfying result in the case of small number samples. So this method can be used to analyze the operation of the water turbine.
出处
《中国农村水利水电》
北大核心
2010年第2期144-146,共3页
China Rural Water and Hydropower
基金
河北省重点发展学科(水利水电工程)基金资助
关键词
尾水管
压力脉动
自组织神经网络
聚类分析
draft tube
pressure pulsation
self-organizing neural networks
clustering analysis
