發(fā)布時(shí)間：2018-04-25 13:40

  本文選題：滾動(dòng)軸承 + 性能退化�。� 參考：《機(jī)械設(shè)計(jì)與研究》2016年05期

【摘要】：為準(zhǔn)確地評(píng)估滾動(dòng)軸承的性能退化狀態(tài),提出了一種基于經(jīng)驗(yàn)?zāi)B(tài)分解(empirical mode decomposition,EMD)和邏輯回歸的評(píng)估方法。首先,提取軸承振動(dòng)信號(hào)的本征模函數(shù)(intrinsic mode function,IMF)能量作為特征向量;其次,以軸承正常狀態(tài)數(shù)據(jù)和失效狀態(tài)的特征向量建立邏輯回歸模型,獲取回歸參數(shù);最后計(jì)算軸承信號(hào)全壽命周期的評(píng)估指數(shù)(confidential value,CV)。評(píng)估結(jié)果表明,該方法能及時(shí)發(fā)現(xiàn)早期故障,也能很好地描述軸承性能退化的各個(gè)階段。
[Abstract]:In order to accurately evaluate the performance degradation of rolling bearings, an evaluation method based on empirical mode decomposition (EMD) and logical regression is proposed. Firstly, the intrinsic mode function intrinsics mode function IMF energy of the bearing vibration signal is extracted as the eigenvector, secondly, the logical regression model is established based on the normal state data of the bearing and the eigenvector of the failure state, and the regression parameters are obtained. Finally, the evaluation index for calculating the full life cycle of bearing signal is confidential value. The evaluation results show that this method can detect early faults in time, and can well describe each stage of bearing performance degradation.
【作者單位】： 華東交通大學(xué)機(jī)電工程學(xué)院;
【基金】：國家自然科學(xué)基金資助項(xiàng)目(51205130) 江西省科協(xié)重點(diǎn)活動(dòng)項(xiàng)目(贛科協(xié)字[2014]88號(hào)
【分類號(hào)】：TH133.33
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本文編號(hào)：1801571