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基于最小熵解卷积的齿轮箱早期故障诊断

冷军发 荆双喜 禹建功

冷军发, 荆双喜, 禹建功. 基于最小熵解卷积的齿轮箱早期故障诊断[J]. 机械科学与技术, 2015, 34(3): 445-448. doi: 10.13433/j.cnki.1003-8728.2015.0324
引用本文: 冷军发, 荆双喜, 禹建功. 基于最小熵解卷积的齿轮箱早期故障诊断[J]. 机械科学与技术, 2015, 34(3): 445-448. doi: 10.13433/j.cnki.1003-8728.2015.0324
Leng Junfa, Jing Shuangxi, Yu Jiangong. Incipient Fault Diagnosis of the Gear box Based on the Minimum Entropy Deconvolution[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(3): 445-448. doi: 10.13433/j.cnki.1003-8728.2015.0324
Citation: Leng Junfa, Jing Shuangxi, Yu Jiangong. Incipient Fault Diagnosis of the Gear box Based on the Minimum Entropy Deconvolution[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(3): 445-448. doi: 10.13433/j.cnki.1003-8728.2015.0324

基于最小熵解卷积的齿轮箱早期故障诊断

doi: 10.13433/j.cnki.1003-8728.2015.0324
基金项目: 

国家自然科学基金项目(11272115)与河南省机械工程重点学科项目资助

详细信息
    作者简介:

    冷军发(1974-),副教授,博士研究生,研究方向为机械振动及故障诊断,lengjf@hpu.edu.cn

Incipient Fault Diagnosis of the Gear box Based on the Minimum Entropy Deconvolution

  • 摘要: 齿轮箱发生早期故障时,其振动信号一般很微弱,且隐含的能反应出齿轮箱运转状态的冲击成分常被淹没在强烈的噪声中,直接做频谱分析或包络谱分析,很难提取其故障特征。论文将最小解卷积方法应用于炼胶机的齿轮箱故障诊断。首先利用该方法对齿轮箱振动信号进行解卷积滤波处理,然后对滤波后的信号进行包络解调分析,最后提取出了该齿轮箱轴5上齿轮8(z8=28)齿根轻微裂纹的故障特征,实现了该齿轮箱的早期诊断。应用实例验证了最小熵解卷积方法的有效性和优点。
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出版历程
  • 收稿日期:  2013-08-13
  • 刊出日期:  2015-03-05

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