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小波分析在突变信号检测中的应用
引用本文:赵红怡,武梦龙,曹淑琴.小波分析在突变信号检测中的应用[J].北方工业大学学报,2004,16(1):21-24.
作者姓名:赵红怡  武梦龙  曹淑琴
作者单位:北方工业大学信息工程学院,100041,北京石景山;北方工业大学信息工程学院,100041,北京石景山;北方工业大学信息工程学院,100041,北京石景山
基金项目:北京市教委科技发展计划项目
摘    要:本文探讨基于小波变换模最大值沿尺度演变的信号突变检测的基本原理与方法,在不同尺度上分析和处理信号的各种频率成分,使信号的奇点、突变点放大,提高信号的分辨率、信噪比.提出通过二进小波变换检测信号奇异点的实用技术,有效地检测出滚动轴承故障发生的起始点,为在线故障诊断做出了有益的探索.

关 键 词:小波变换  频域分析  局部极值  突变检测

Application of Wavelet Analysis to Break Signal Detection
Zhao Hongyi,Wu Menglong,Cao Shuqin.Application of Wavelet Analysis to Break Signal Detection[J].Journal of North China University of Technology,2004,16(1):21-24.
Authors:Zhao Hongyi  Wu Menglong  Cao Shuqin
Abstract:This paper discusses the principle and method based on the signal break detection of the wavelet transformation modulus maximum varying along the scale. All sorts of frequencies are analyzed and processed for various scales. The odd and break points of signals are amplified and the resolving power and SNR are improved. A practical technique developed for signal singularity detection is proposed. Locations where faults occur in the rolling bearings are effectively detected, leading to the beneficial exploration of on-line diagnosis.
Keywords:wavelet transformation  frequency analysis  local extreme value  break detection
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