轴承
軸承
축승
BEARING
2015年
8期
55-58
,共4页
林旭泽%王新军%蔡艳平%禹志航
林旭澤%王新軍%蔡豔平%禹誌航
림욱택%왕신군%채염평%우지항
滚动轴承%AEEMD%峭度%相关系数%包络解调%故障诊断
滾動軸承%AEEMD%峭度%相關繫數%包絡解調%故障診斷
곤동축승%AEEMD%초도%상관계수%포락해조%고장진단
rolling bearing%AEEMD%kurtosis%correlation coefficient%envelope demodulation%fault diagnosis
针对经验模态分解(EMD)和总体集成经验模态分解(EEMD)算法在轴承故障诊断中的缺陷,提出了一种基于自适应总体集成经验模态分解(AEEMD)与峭度和相关系数联合准则的滚动轴承故障诊断方法。首先,通过 AEEMD 将振动信号分解成具有不同特征时间尺度的本征模态分量,然后利用峭度和相关系数联合准则选取包含故障信息最丰富的 IMF,最后对选取的特征 IMF 做包络解调,进行故障诊断。并将 AEEMD 与 EMD 算法进行对比,证明了 AEEMD 算法的有效性和自适应性。
針對經驗模態分解(EMD)和總體集成經驗模態分解(EEMD)算法在軸承故障診斷中的缺陷,提齣瞭一種基于自適應總體集成經驗模態分解(AEEMD)與峭度和相關繫數聯閤準則的滾動軸承故障診斷方法。首先,通過 AEEMD 將振動信號分解成具有不同特徵時間呎度的本徵模態分量,然後利用峭度和相關繫數聯閤準則選取包含故障信息最豐富的 IMF,最後對選取的特徵 IMF 做包絡解調,進行故障診斷。併將 AEEMD 與 EMD 算法進行對比,證明瞭 AEEMD 算法的有效性和自適應性。
침대경험모태분해(EMD)화총체집성경험모태분해(EEMD)산법재축승고장진단중적결함,제출료일충기우자괄응총체집성경험모태분해(AEEMD)여초도화상관계수연합준칙적곤동축승고장진단방법。수선,통과 AEEMD 장진동신호분해성구유불동특정시간척도적본정모태분량,연후이용초도화상관계수연합준칙선취포함고장신식최봉부적 IMF,최후대선취적특정 IMF 주포락해조,진행고장진단。병장 AEEMD 여 EMD 산법진행대비,증명료 AEEMD 산법적유효성화자괄응성。
Aiming at shortages of EMD and EEMD algorithm in fault diagnosis for bearings,a fault diagnosis method for rolling bearings is proposed based on AEEMD and kurtosis -correlation coefficients joint criterion.Firstly,the AEEMD is used to decompose vibration signal into several IMFs of different characteristic time scales .Then the IMF which con-tain the most abundant fault information is selected according to kurtosis -correlation coefficients criterion.Finally,an envelope demodulation is adopted with selected IMF to diagnose fault.The AEEMD and EMD algorithm are compared to verify effectiveness and adaptivity of AEEMD algorithm.