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滚动轴承故障诊断的自适应包络谱谱峰因子算法

张龙 毛志德 熊国良 崔路瑶

张龙, 毛志德, 熊国良, 崔路瑶. 滚动轴承故障诊断的自适应包络谱谱峰因子算法[J]. 机械科学与技术, 2019, 38(4): 507-514. doi: 10.13433/j.cnki.1003-8728.20180244
引用本文: 张龙, 毛志德, 熊国良, 崔路瑶. 滚动轴承故障诊断的自适应包络谱谱峰因子算法[J]. 机械科学与技术, 2019, 38(4): 507-514. doi: 10.13433/j.cnki.1003-8728.20180244
Zhang Long, Mao Zhide, Xiong Guoliang, Cui Luyao. Adaptive Fault Diagnosis of Rolling Bearings based on Crest Factor of Envelope Spectrum[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(4): 507-514. doi: 10.13433/j.cnki.1003-8728.20180244
Citation: Zhang Long, Mao Zhide, Xiong Guoliang, Cui Luyao. Adaptive Fault Diagnosis of Rolling Bearings based on Crest Factor of Envelope Spectrum[J]. Mechanical Science and Technology for Aerospace Engineering, 2019, 38(4): 507-514. doi: 10.13433/j.cnki.1003-8728.20180244

滚动轴承故障诊断的自适应包络谱谱峰因子算法

doi: 10.13433/j.cnki.1003-8728.20180244
基金项目: 

江西省研究生创新资金项目 YC2017-S248

江西省自然科学基金项目 20161BAB216134

国家自然科学基金项目 51665013

江西省自然科学基金项目 20171BAB206028

江西省自然科学基金项目 20152ACB21020

国家自然科学基金项目 51865010

详细信息
    作者简介:

    张龙(1980-), 副教授, 博士, 研究方向为故障诊断, 工程信号处理及智能算法, longzh@ecjtu.edu.com

  • 中图分类号: TG156

Adaptive Fault Diagnosis of Rolling Bearings based on Crest Factor of Envelope Spectrum

  • 摘要: 表征滚动轴承故障特征的周期性冲击,特别是在故障早期阶段,常常被噪声和其它结构振动所淹没,从而难以辨别。共振解调被广泛用于滚动轴承故障冲击特征提取,但其滤波频带的参数选择常需要一定的先验知识。针对现有的频带优化方法的不足,本文提出一种基于包络谱谱峰因子和复平移Morlet小波滤波的自适应共振解调方法-自适应包络谱谱峰因子算法。包络谱谱峰因子(Crest factor of envelope spectrum,CE)定义为包络谱在一定范围内的最大值和有效值之比,能有效度量信号中周期性冲击强弱,结合粒子群优化算法的寻优特性,对Morlet小波滤波器中心频率和带宽参数进行优化。将包络谱谱峰因子作为适应度函数来比较不同参数组合下的滤波效果,根据适应度函数值最大原则选取Morlet小波滤波器参数。仿真信号、实验信号以及工程实际信号分析验证了该方法在共振解调最优频带选取中的有效性和优越性。
  • 图  1  自适应包络谱峰值因子诊断模型

    图  2  原始及加入脉冲干扰和噪声后的仿真信号

    图  3  仿真信号的谱峭度方法分析结果

    图  4  本文方法的仿真信号分析结果

    图  5  离散遍历寻优结果

    图  6  滚动轴承疲劳试验台

    图  7  第2列数据的Rms演化及第703个数据文件

    图  8  第703个文件第2列数据的谱峭度分析

    图  9  第703个文件的本文方法分析结果

    图  10  货车轴承拆解图

    图  11  原始声音信号及其包络谱

    图  12  本文方法的声音信号分析结果

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出版历程
  • 收稿日期:  2018-04-01
  • 刊出日期:  2019-04-05

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