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

【摘要】：針對滾動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)和線性預測濾波的診斷技術。首先,通過經驗模態(tài)分解(EMD)把振動信號分解成一系列的固有模態(tài)函數(shù)。根據(jù)包絡頻譜相關信息提出了一種固有模態(tài)函數(shù)重構方法,將故障信息敏感的固有模態(tài)函數(shù)重構為一個新的信號。然后通過線性預測濾波加強重構后信號的沖擊故障信息,最后利用信號的功率譜有效的展現(xiàn)了軸承的故障頻率特性。通過實測滾動軸承信號對該方法進行了驗證,結果表明該方法能準確的檢測滾動軸承故障。
[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】： 山東理工大學電氣與電子工程學院;山東理工大學機械工程學院;
【基金】：國家自然科學基金(51305243) 山東省自然科學基金(ZR2012EEL06)
【分類號】：TH133.33
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本文編號：1661275