基于循环双谱的机械振动仿真信号分析

发布时间：2018-03-24 01:34

本文选题：循环平稳　切入点：循环双谱　出处：《昆明理工大学》2017年硕士论文

【摘要】：特征提取在机械设备的状态监测和故障诊断中是一个非常重要的信号处理问题。自上世纪80年代以来,为了满足对机械故障进行精确诊断的需要,对非线性、非高斯、非平稳的信号处理技术在机械故障诊断领域受到越来越多的关注。由于高阶统计量有抑制高斯噪声的性质,本文采用理论和Matlab仿真实验相结合的手段,研究了基于循环双谱的机械振动仿真信号的分析。首先,本文拟采用高阶统计分析方法分析平稳随机信号,高阶统计量可以抑制高斯噪声,提取非平稳、非线性、非高斯故障信号的特征信息,对故障的诊断具有重要的意义。但随着阶数越来越高,计算量就越来越大,而三阶统计量既能有效地抑制高斯噪声,又能提取非线性信号特征信息,计算量是相对最小的,因此本文着重分析了双谱估计。其次,研究循环平稳信号的定义和分析方法。(1)分析了一阶和二阶循环统计量的基本理论,利用循环自相关函数的切片谱能在循环频率域分离载波频率信息和调制频率信息的优点,可以更容易地在循环频率低频率段提取出故障的调制频率信息;使用周期频率和频率特性之间的相关特点,用切片图可以提炼出有用的信息,然后分析频率信息的特点。(2)机械振动信号可以产生幅度调制信号、频率调制信号、多载波频率调制信号、多调制源调幅信号和多载波调幅信号等,为了能更加准确的了解机械设备的故障特征情况,研究这些复杂的调制信号解调方法,发现循环自相关解调分析可以有效地分离出调制信号、载波信息等,具有较强的噪声抑制特性。最后,本文对机械振动的仿真信号进行了仿真实验研究,因循环双谱涉及四维分析计算量较大,而自相关切片谱不能有效抑制高斯噪声,结合两者的特点,本文将循环自相关函数切片的方法引入到循环双谱分析,提出了采用循环双谱载波频率切片法提取故障特征,可以直观的表达谱分析的结果,有效的提取出故障特征频率信息。同时,本文还将故障信号先小波去噪再进行双谱分析,实验仿真结果表明,小波去噪后的循环双谱载波频率切片谱图中的干扰明显减少,特征频率信息更突出的表现了出来。
[Abstract]:Feature extraction in condition monitoring and fault diagnosis of mechanical equipment is a very important signal processing problems. Since the last century since 80s, in order to meet the needs for accurate diagnosis of mechanical faults of nonlinear, non Gauss, non-stationary signal processing technology has attracted more and more attention in the field of mechanical fault diagnosis due to the high. Order statistics properties suppress Gauss noise, this paper uses the theory and method of combining Matlab simulation experiment, studied the simulation analysis of mechanical vibration signal based on the cyclic bispectrum. Firstly, this paper uses high order statistics method analysis of stationary random signal, high-order statistics can suppress Gauss noise, nonlinear, non-stationary extraction. Non Gauss characteristic information of fault signals, has important significance for fault diagnosis. But with the order of computation is more and more high, more and more large, and the three order statistics Quantity can effectively suppress the Gauss noise, and can extract the nonlinear feature information of signal, the amount of calculation is relatively minimal, so this paper focuses on the analysis of the bispectrum estimation. Secondly, the research of cyclostationary signal definition and analysis. (1) the analysis of the basic theory of one order and two order cyclic statistics, the advantages of recycling the autocorrelation function of the slice spectrum can separate carrier frequency modulation information and frequency information in cyclic frequency domain, can be more easily extracted rate modulation frequency information of fault in cycle frequency; related characteristics of cycle frequency and frequency characteristics of the section map can extract useful information, and then analyzes the characteristics the frequency of information. (2) the mechanical vibration signal can generate the amplitude modulation signal, frequency modulation signal, multi carrier frequency modulation signal, multi modulation amplitude modulation signal and multi carrier modulation signals, in order to A more accurate understanding of the fault features of mechanical equipment status and Research on these complex modulation signal demodulation method, cyclic autocorrelation demodulation analysis can effectively separate the modulated signal carrier information, has strong noise suppression characteristics. Finally, the simulation of the mechanical vibration signal was studied by simulation, cyclic bispectrum the analysis involves a large amount of calculation and correlation dimension, slice spectrum can not effectively suppress Gauss noise, combined with the characteristics of this method, the cyclic autocorrelation function is introduced to slice cyclic bispectrum analysis, the carrier frequency of cyclic bispectrum slice method to extract fault features, the results of the analysis can be intuitive expression, extract the characteristic frequency of fault information effectively. At the same time, this paper will first fault signal wavelet denoising and bispectrum analysis, simulation results show that after wavelet denoising The interference in the cyclic bispectral frequency slice spectrum is obviously reduced, and the characteristic frequency information is more prominent.

【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TH17

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