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基于第二代小波变换的振动信号去噪与故障诊断
引用本文:唐贵基,王誉蓉,郭新富,胡爱军,范德功.基于第二代小波变换的振动信号去噪与故障诊断[J].汽轮机技术,2006,48(4):295-297.
作者姓名:唐贵基  王誉蓉  郭新富  胡爱军  范德功
作者单位:1. 华北电力大学机械工程学院,保定,071003
2. 中石油宁夏销售分公司,银川,750001
基金项目:华北电力大学博士学位教师基金项目(项目编号:92104392)。
摘    要:旋转机械故障振动信号存在不同形式的波形特征,传统小波去噪中,小波分解的结果与所采用的小波基函数有关,选用不适当的小波基函数会冲淡振动信号的局部特征信息,而造成原始信号的部分有用的细节信息丢失。为了克服上述缺陷,提出一种基于第二代小波变换的振动信号预处理方法,即针对分析信号的局部特征,以预测方差最小为目标,对每个样本选择最佳的预测算子,使小波基函数始终能够匹配信号的局部特征。仿真试验表明,该方法克服了传统小波去噪中降噪信号丢失了部分细节信息的缺点,不仅可有效地去除故障诊断振动信号的噪声,而且能够保留信号的局部信息。

关 键 词:第二代小波变换  预处理  小波基函数  预测算子
文章编号:1001-5884(2006)04-0295-03
收稿时间:2006-03-26
修稿时间:2006-03-26

Denoising Method and Fault Diagnosis of Vibrating Signal Based on Second Generation Wavelet Transform
TANG Gui-ji,WANG Yu-rong,GUO Xin-fu,HU Ai-jun,FAN De-gong.Denoising Method and Fault Diagnosis of Vibrating Signal Based on Second Generation Wavelet Transform[J].Turbine Technology,2006,48(4):295-297.
Authors:TANG Gui-ji  WANG Yu-rong  GUO Xin-fu  HU Ai-jun  FAN De-gong
Affiliation:1 School of Mechanical Engineering, North China Electric Power University, Baoding 071003, China ; 2 NingXia Marketing Branch Company,China National Petroleum Corp. , Yinchuan 750001 ,China
Abstract:There is different characteristics of signal in the fault vibrating signal of rotating machinery.In the denoising of traditional wavelet tansform,the result of wavelet decomposing is related with wavelet basis function.And the adopted wave- let which is ill-suilted for original signal can delute the local characteristic of vibrating signal,and lost some useful detail information of original signal.In order to overcome mentioned limitation,a pre-processing method based on second genera- tion wavelet transform for vibrating signal is adopted.According to the local characteristics of signal and the selection crite- rion of minimizing the squared error,an optimal predicting operator is selected for a transforming sample so that the used wavelet basis function can always fit the local characteristics of the signal.The simulation showed that the proposed method could overcome the denoising disadvantage of traditional wavelet transform.It not only can fiher noise from original signal ef- fectively,but also can hold local characteristics of original signal for fault diagnosis in the denoised signals.
Keywords:second generation wavelet transform  pre-processing  wavelet basis function  predicting operator
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