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MCKD最佳故障周期搜索的齿轮箱故障特征提取

冷军发 荆双喜 王志阳 华伟

冷军发, 荆双喜, 王志阳, 华伟. MCKD最佳故障周期搜索的齿轮箱故障特征提取[J]. 机械科学与技术, 2018, 37(1): 36-42. doi: 10.13433/j.cnki.1003-8728.2018.0107
引用本文: 冷军发, 荆双喜, 王志阳, 华伟. MCKD最佳故障周期搜索的齿轮箱故障特征提取[J]. 机械科学与技术, 2018, 37(1): 36-42. doi: 10.13433/j.cnki.1003-8728.2018.0107
Leng Junfa, Jing Shuangxi, Wang Zhiyang, Hua Wei. Optimum Fault Period Searching of MCKD Algorithm for Fault Feature Extraction of Gearbox[J]. Mechanical Science and Technology for Aerospace Engineering, 2018, 37(1): 36-42. doi: 10.13433/j.cnki.1003-8728.2018.0107
Citation: Leng Junfa, Jing Shuangxi, Wang Zhiyang, Hua Wei. Optimum Fault Period Searching of MCKD Algorithm for Fault Feature Extraction of Gearbox[J]. Mechanical Science and Technology for Aerospace Engineering, 2018, 37(1): 36-42. doi: 10.13433/j.cnki.1003-8728.2018.0107

MCKD最佳故障周期搜索的齿轮箱故障特征提取

doi: 10.13433/j.cnki.1003-8728.2018.0107
基金项目: 

国家自然科学基金项目(U1304523)、中国煤炭工业协会项目(MTKJ2015-261)及河南理工大学博士基金项目(B2017-28)资助

详细信息
    作者简介:

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

    通讯作者:

    荆双喜,教授,博士,jsx@hpu.edu.cn

Optimum Fault Period Searching of MCKD Algorithm for Fault Feature Extraction of Gearbox

  • 摘要: 针对最小解熵解卷积(Minimum entropy deconvolution,MED)算法易受强噪声和野值的影响,引出了最大相关峭度解卷积(Maximum correlated kurtosis deconvolution,MCKD)的齿轮箱故障特征提取方法,克服了MED算法的不足。然而凭先验信息选取的故障周期,可能导致MCKD解卷积效果很差,因此提出了MCKD算法的最佳故障周期搜索思路,即在合适的滤波器阶数L下,最佳故障周期的搜索可以限定于理论计算周期左右的某一范围内,使不同步距M关于最佳周期的最大相关峭度达到全局最优,以确保了MCKD算法具有良好的解卷积效果。断齿与局部断齿故障特征提取试验结果佐证了最佳故障周期搜索思路的可行性及其效果。
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出版历程
  • 收稿日期:  2016-10-14
  • 刊出日期:  2018-01-15

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