噪声与振动控制2017，Vol.37Issue(3)：173-176,4.DOI:10.3969/j.issn.1006-1355.2017.03.034
基于最大相关峭度反褶积的齿轮箱复合故障特征提取
A Feature Extraction Method for Gearboxes with Compound Faults Based on MCKD
摘要
Abstract
A feature extraction method for gearboxes with compound faults is proposed. The maximum correlated kurtosis deconvolution (MCKD) method is used to reduce the noise of the original signal and extract the related periodic components. Comparing the result of this method with that of the minimum entropy deconvolution (MED) method, the superiority of the MCKD method on noise reduction is proved. Applying the proposed method to the compound fault diagnosis of the gearboxes, the fault features can be extracted successfully.关键词
振动与波/最大相关峭度反褶积/最小熵反褶积/复合故障/故障检测Key words
vibration and wave/maximum correlated kurtosis deconvolution (MCKD)/minimum entropy deconvolution (MED)/multi-fault/fault detection分类
信息技术与安全科学引用本文复制引用
王志坚,寇彦飞,王俊元,张纪平,齐明思,赵志芳..基于最大相关峭度反褶积的齿轮箱复合故障特征提取[J].噪声与振动控制,2017,37(3):173-176,4.基金项目
山西省自然科学基金资助项目(2015011063) （2015011063）
