小波在信号检测中的应用毕设论文.doc

小波在信号检测中的应用 毕业论文 诚 信 书 我谨在此保证：本人所写的毕业论文(设计)，凡引用他人的研究成果均已在参考文献或注释中列出。论文(设计)主体均由本人独立完成，没有抄袭、剽窃他人已经发表或未发表的研究成果行为。如出现以上违反知识产权的情况，本人愿意承担相应的责任。 声明人(签名)： 年 月 日  摘 要 小波分析作为必威体育精装版的时-频分析工具，在信号分析、图像处理、特征提取、故障诊断等各领域得到了广泛的应用。小波变换具有表征信号局部特征的能力和多分辨率的特征,因此，很适于探测信号中的瞬态和奇异现象, 并可展示其成份。 本文在综述小波变换的基本思想与具体性质和原理的基础上，重点介绍了小波在滚动轴承机械故障检测中的应用。滚动轴承机械故障信号分析中基函数的不同将导致对信号的观测角度和观测方法的不同，在小波基函数的选取方面 Fourier变换、短时Fourier变换和小波变换各自的基函数有着的本质区别。 本文通过比较故障诊断中常用的各种小波基函数的性能和特点，研究不同的故障信号特征与各种小波基函数的内在联系。利用连续小波变换方法将滚动轴承振动信号的特征信息转化为能量谱与尺度的关系，进而建立尺度和能量相对应的特征向量，为滚动轴承的快速诊断提供了新方法。本文提出一种应用 Daubechies 小波包多层分解、重构提取滚动轴承各部件的故障特征频率和能量特征，通过小波包多层分解确定滚动轴承机械振动的奇异点的方法, 实现故障的精确诊断。 关键词：小波分析、故障诊断、滚动轴承、多层分解 Abstract Wavelet analysis as the latest time - frequency analysis tool in signal analysis, image processing, feature extraction, fault diagnosis and other fields has been widely used. Characterization of the signal wavelet transform has the ability of local features and characteristics of multi-resolution, therefore, it is very suitable for detection of transient signals and singular phenomenon, even to display its components. General speaking the summary of this paper, the basic ideas of wavelet transform and the specific nature, the most important of this paper is focusing on the wavelet applications of fault detection in the rolling machine. In the mechanical failure of the rolling bearing signal analysis, the different basis functions lead to a difference of signal point of observing views and observing methods, which are the essential differences among wavelet transform Fourier transform, short-time Fourier transform. In this paper, by comparing the performances and characteristics of a variety of common used small-wavelet fonctions in fault diagnosis, I research on the internal relations between different characteristics of the fault signal and wavelet fonctions. Making using of continuous wavelet transform method, this paper changes the characteristics of rolling bearing vibration signal information into the r