摘要
提出了多通道相关-自适应共振解调(MCC-ARD)方法 ,该方法使用冗余信号源采集故障信息,并利用谱峭度(SK)优化经验模态分解(EMD)的分解效率,根据互相关系数更加合理地选择本征模态函数(IMF)分量完成重构,对重构IMF进行包络解调,实现对滚动轴承的故障诊断。通过对多通道相关-自适应共振解调方法的实测数据分析,结果表明:该方法不仅克服了单一信号源系统修正能力差的缺陷,而且相频谱辨识率为传统EMD结合谱峭度共振解调方法的2.7倍,对滚动轴承故障的诊断结果更加清晰、准确。
A multi-channel correlation adaptive resonance demodulation(MCC-ARD)method was proposed.MCC-ARD employed redundant signal source to pick up fault information and optimize empirical mode decomposition(EMD)efficiency by spectral kurtosis(SK).The intrinsic mode function(IMF)components were reconstructed by reasonable choice of the cross-correlation coefficient.The method realized the fault diagnosis of rolling bearings by the reconstructed IMF envelope demodulation.Through the measured data analysis of MCC-ARD,result showed that MCC-ARD not only overcame the defect of poor system correction,but also the spectrum identification rate was 2.7 times of the traditional EMD combined spectral kurtosis demodulation method,making the fault diagnosis results of rolling bearing more clearer and more accurate.
作者
谷朝健
马增强
王建东
张俊甲
GU Chaojian;MA Zengqiang;WANG Jiandong;ZHANG Junjia(School of Electronical and Electronics Engineering,Shijiazhuang Tiedao University,Shijiazhuang 05004,China;Qingdao Sifang Company Limited,China;Railway Rolling Stock Corporation Limited,Qingdao Shandong 266111,Chin)
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2018年第7期1750-1757,共8页
Journal of Aerospace Power
基金
国家自然科学基金(11227201
11372199
11572206)
河北省自然科学基金(A2014210142)
关键词
经验模式分解(EMD)
谱峭度
多通道相关
自适应共振解调
滚动轴承故障诊断
empirical mode decomposition (EMD)
spectral kurtosis
multi-channel correlation
adaptive resonance demodulation
rolling bearing fault diagnosis