基于改进奇异谱分解的形态学解调方法及其在滚动轴承故障诊断中的应用

发布时间：2018-01-11 07:03

  本文关键词：基于改进奇异谱分解的形态学解调方法及其在滚动轴承故障诊断中的应用　出处：《机械工程学报》2017年07期 　论文类型：期刊论文

  更多相关文章： 奇异谱分解 端点效应 形态学解调 滚动轴承 故障诊断

【摘要】：针对强背景噪声及干扰源信号影响下滚动轴承故障特征难以检测的问题,提出一种基于改进奇异谱分解的形态学解调方法用于轴承故障诊断。首先,为了克服奇异谱分析按经验性选取嵌入维数长度的缺陷,采用一种新的自适应信号处理方法——奇异谱分解(Singular spectrum decomposition,SSD)进行振动信号分析,该方法通过构建一个轨迹矩阵与自适应选择嵌入维数长度,将非平稳信号从高频至低频依次划分为若干个单分量信号。针对奇异谱分解在分量序列重构过程中两端数据会偏离实际数据值进而引起端点效应现象的问题,提出运用特征波形匹配延拓法对奇异谱分解进行改进,提高其对振动信号的分解质量,获得一系列更接近实际曲线的单分量序列。为准确提取单分量中蕴含的有用故障特征信息,提出一种基于特征能量比自适应确定结构元素最佳尺度的自互补顶帽变换对单分量信号进行形态学解调。最后,分析解调结果的频谱特征并提取突出频率成分,实现轴承故障类型的准确判别。仿真和实测信号分析验证了方法的有效性。
[Abstract]:In order to solve the problem that the fault characteristics of rolling bearing are difficult to detect under the influence of strong background noise and interference source signal, a morphological demodulation method based on improved singular spectrum decomposition is proposed for bearing fault diagnosis. In order to overcome the defect of selecting embedding dimension length by experience in singular spectrum analysis. A new adaptive signal processing method, singular spectrum decomposition (SSD), is used for vibration signal analysis. This method constructs a trajectory matrix and adaptively selects the embedding dimension length. The non-stationary signal is divided into several single-component signals from high frequency to low frequency. In order to solve the problem that the data at both ends of the singular spectrum decomposition will deviate from the actual data value in the process of component sequence reconstruction, the phenomenon of endpoint effect will be caused. The characteristic waveform matching continuation method is proposed to improve the decomposition quality of the vibration signal. A series of single component sequences, which are closer to the actual curve, are obtained to extract the useful fault feature information contained in the single component accurately. A self-complementary top-cap transform based on the adaptive determination of the optimal scale of structural elements is proposed to demodulate the single component signal. Finally, the spectrum features of the demodulation results are analyzed and the outburst frequency components are extracted. The validity of the method is verified by simulation and actual signal analysis.
【作者单位】： 东南大学机械工程学院;
【基金】：国家自然科学基金(51675098) 高等学校博士学科点专项科研基金(20130092110003)资助项目
【分类号】：TH133.33
【正文快照】： 0前言*滚动轴承是机械设备中的核心组件,在长期高速运转、交变载荷等恶劣工况下,极易产生局部损伤并演化成晚期故障,影响着整个机械传递系统的工作性能。因此,针对轴承早期损伤阶段进行有效检测备受关注。而在实际工程中,轴承振动信号往往表现为周期非平稳特性,其受到部件间多，

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