本文選題：固有模態(tài)函數(shù)　切入點(diǎn)：預(yù)測濾波　出處：《組合機(jī)床與自動(dòng)化加工技術(shù)》2016年08期

【摘要】：針對滾動(dòng)軸承早期故障信息難以提取的問題,提出了基于固有模態(tài)函數(shù)(IMF)和線性預(yù)測濾波的診斷技術(shù)。首先,通過經(jīng)驗(yàn)?zāi)B(tài)分解(EMD)把振動(dòng)信號(hào)分解成一系列的固有模態(tài)函數(shù)。根據(jù)包絡(luò)頻譜相關(guān)信息提出了一種固有模態(tài)函數(shù)重構(gòu)方法,將故障信息敏感的固有模態(tài)函數(shù)重構(gòu)為一個(gè)新的信號(hào)。然后通過線性預(yù)測濾波加強(qiáng)重構(gòu)后信號(hào)的沖擊故障信息,最后利用信號(hào)的功率譜有效的展現(xiàn)了軸承的故障頻率特性。通過實(shí)測滾動(dòng)軸承信號(hào)對該方法進(jìn)行了驗(yàn)證,結(jié)果表明該方法能準(zhǔn)確的檢測滾動(dòng)軸承故障。
[Abstract]:In order to solve the problem that it is difficult to extract the early fault information of rolling bearing, a diagnosis technique based on inherent mode function (IMF) and linear predictive filtering is proposed. The vibration signal is decomposed into a series of inherent mode functions by empirical mode decomposition (EMD). According to the information of envelope spectrum, a reconstruction method of inherent mode function is proposed. The inherent mode function which is sensitive to fault information is reconstructed into a new signal, and then the impulse fault information of the reconstructed signal is enhanced by linear predictive filtering. Finally, the power spectrum of the signal is used to show the fault frequency characteristics of the bearing effectively, and the method is verified by the measured rolling bearing signal. The results show that the method can accurately detect the fault of the rolling bearing.
【作者單位】： 山東理工大學(xué)電氣與電子工程學(xué)院;山東理工大學(xué)機(jī)械工程學(xué)院;
【基金】：國家自然科學(xué)基金(51305243) 山東省自然科學(xué)基金(ZR2012EEL06)
【分類號(hào)】：TH133.33
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本文編號(hào)：1661275