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基于小波包和Elman神经网络的液压泵故障诊断
引用本文:刘红梅,王少萍,欧阳平超.基于小波包和Elman神经网络的液压泵故障诊断[J].北京航空航天大学学报,2007,33(1):67-71.
作者姓名:刘红梅  王少萍  欧阳平超
作者单位:北京航空航天大学 自动化科学与电气工程学院, 北京 100083
摘    要:针对液压泵出口故障检测信号信噪比低、难以进行故障特征提取的特点,及 传统的BP网络进行故障诊断时网络学习具有收敛速度慢和学习、记忆不稳定的缺陷,提出了 一种将小波包变换和改进Elman神经网络相结合,进行液压泵故障诊断的新方法.利用具有 紧支结构的小波函数对信号进行分解,削减小波系数以滤除信号中的噪声;单支重构以有效 提取各频带的故障特征,并以频带能量作为识别故障的特征向量;应用改进的Elman神经网 络建立从特征向量到故障模式之间的映射,实现液压泵故障分类.试验结果表明,采用小波 包和改进Elman神经网络相结合的方法可有效的实现液压泵故障的诊断.

关 键 词:小波包分析  Elman神经网络  液压泵  故障诊断
文章编号:1001-5965(2007)01-0067-05
收稿时间:2006-01-05
修稿时间:2006-01-05

Fault diagnosis based on wavelet package and Elman neural network for a hydraulic pump
Liu Hongmei,Wang Shaoping,Ouyang Pingchao.Fault diagnosis based on wavelet package and Elman neural network for a hydraulic pump[J].Journal of Beijing University of Aeronautics and Astronautics,2007,33(1):67-71.
Authors:Liu Hongmei  Wang Shaoping  Ouyang Pingchao
Institution:School of Automation Science and Electrical Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China
Abstract:Considering the low signal-to-noise,faint failure characteristics of hydraulic pump,and slow convergence speed and the instability of BP network,a new fault diagnosis method based on the wavelet package analysis and Elman neural network is presented.The wavelet package analysis is adopted to eliminate the noise in the actual signals and to extract the fault characteristics.Through signal decomposition and single reconfiguration with wavelet package,the noise can be eliminated from signals to strengthen the failure signal and to extract fault feature in every frequency bands effectively.Energy of various frequency bands acting as the fault feature vector is input into the improved Elman neural network to realize the mapping between the feature vector and the fault mode.The experiment results verified the effectiveness of the proposed method in the hydraulic pump fault diagnosis.
Keywords:wavelet package analysis  Elman neural network  hydraulic pump  fault diagnosis
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