轴承
軸承
축승
BEARING
2014年
6期
41-44,57
,共5页
任学平%庞震%辛向志%邢义通
任學平%龐震%辛嚮誌%邢義通
임학평%방진%신향지%형의통
滚动轴承%改进小波包%总体经验模态分解%故障诊断
滾動軸承%改進小波包%總體經驗模態分解%故障診斷
곤동축승%개진소파포%총체경험모태분해%고장진단
rolling-bearing%improved-wavelet-packet%EEMD%fault-diagnosis
针对轴承振动信号非平稳性及工作情况下难以获得故障频率,提出一种基于改进小波包和总体经验模态分解(EEMD)的轴承故障诊断方法。首先运用改进小波包对振动信号进行分解,得到按顺序排列的子带频带。然后提取故障频率范围的子带信号并进行EEMD,以互相关系数和峭度准则提取故障分量,避免了固有模态函数(IMF)分量选择的盲目性。仿真和试验分析结果表明,该方法能有效且准确地检测出轴承故障。
針對軸承振動信號非平穩性及工作情況下難以穫得故障頻率,提齣一種基于改進小波包和總體經驗模態分解(EEMD)的軸承故障診斷方法。首先運用改進小波包對振動信號進行分解,得到按順序排列的子帶頻帶。然後提取故障頻率範圍的子帶信號併進行EEMD,以互相關繫數和峭度準則提取故障分量,避免瞭固有模態函數(IMF)分量選擇的盲目性。倣真和試驗分析結果錶明,該方法能有效且準確地檢測齣軸承故障。
침대축승진동신호비평은성급공작정황하난이획득고장빈솔,제출일충기우개진소파포화총체경험모태분해(EEMD)적축승고장진단방법。수선운용개진소파포대진동신호진행분해,득도안순서배렬적자대빈대。연후제취고장빈솔범위적자대신호병진행EEMD,이호상관계수화초도준칙제취고장분량,피면료고유모태함수(IMF)분량선택적맹목성。방진화시험분석결과표명,해방법능유효차준학지검측출축승고장。
In view of the non-stationary of vibration signals of bearings and the difficulty to obtain fault frequencies in practice,a fault diagnosis method for bearings is put forward based on improved wavelet packet and EEMD.Firstly,the vibration signals are decomposed by improved wavelet packet,a number of sub-band frequency bands in order are ob-tained.Then the sub-band signals of fault frequency range are extracted and the EEMD is carried out.The fault com-ponent is extracted by cross correlation coefficient and kurtosis criteria,which can avoid the blindness of the IMF com-ponent selection.The simulation and test analysis results show that the method can effectively and accurately detect fault of bearings.