水利学报2011，Vol.42Issue(9)：1075-1080,6.
基于小波分析与人工神经网络的水轮机压力脉动信号分析
Analysis of pressure fluctuation in draft tube based on wavelet analysis and artificial neural networks
摘要
Abstract
In view of the non-stationary and time-varying characteristics of the pressure fluctuation signal in draft tube,this paper presents a method combining wavelet analysis with a self-organizing artificial neural network to analysis the pressure fluctuation signal.Firstly,the wavelet threshold value method was used to decrease the noise and reduce interference,then the wavelet coefficients were reconstructed to obtain signal component of different frequency band and extract significant different band energy.Then,the band energy is used as the characteristic vector to apply the self-organizing neural network for pattern recognition and obtained the different patterns of pressure fluctuation in draft tube.This method was used to analyze the pressure fluctuation data for a model of Francis turbine.The results show that this method is effective in identifying the state of pressure fluctuathon in draft tube.关键词
水轮机/小波分析/自组织人工神经网络/模式识别Key words
hydraulic turbine/wavelet analysis/self-organizing artificial neural networks/pattern recognition分类
建筑与水利引用本文复制引用
赵林明,楚清河,代秋平,王利英..基于小波分析与人工神经网络的水轮机压力脉动信号分析[J].水利学报,2011,42(9):1075-1080,6.基金项目
国家自然科学基金项目 （）
河北省自然科学基金项目 （）
