本文關(guān)鍵詞：基于EEMD與MED的沖擊信號自適應(yīng)故障特征提取方法　出處：《上海大學(xué)》2016年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： EEMD MED 自適應(yīng)方法 沖擊信號 特征提取 故障診斷

【摘要】：振動信號是機(jī)械系統(tǒng)行為的最直觀反映,它攜帶大量設(shè)備狀態(tài)信息,可以及時地反映機(jī)械系統(tǒng)的動態(tài)變化過程。因此,振動信號被廣泛地應(yīng)用于狀態(tài)監(jiān)測與故障診斷。特征提取是故障診斷技術(shù)的關(guān)鍵環(huán)節(jié),為了從復(fù)雜的非平穩(wěn)、非線性信號中有效地提取沖擊故障的特征信息,本文深入研究了EEMD與MED兩種自適應(yīng)故障特征提取方法,主要研究工作如下:(1)針對EEMD方法均值曲線構(gòu)造過程中易出現(xiàn)過包絡(luò)的問題,本文根據(jù)極值點(diǎn)存在的極值冗余或偽極值點(diǎn)現(xiàn)象,提出局部極值包絡(luò)均值曲線構(gòu)造方法。繼而,將該方法替換EEMD原均值曲線構(gòu)造方法,形成局部極值包絡(luò)EEMD方法,通過與EEMD方法對比分析,發(fā)現(xiàn)局部極值包絡(luò)EEMD方法在消除模態(tài)混淆方面可取得更好的實(shí)驗(yàn)效果。(2)針對如何從EEMD分解出的多個IMF中選取出反映沖擊故障特征信息的問題,本文通過定義雙值特征參數(shù)的“從屬”和“不從屬”邏輯關(guān)系,提出選取EEMD沖擊故障特征信號的雙值區(qū)間準(zhǔn)則。根據(jù)峭度對沖擊信號敏感的特點(diǎn),將最大譜峭度頻帶區(qū)間作為雙值特征參數(shù),結(jié)合雙值區(qū)間準(zhǔn)則對沖擊故障特征信號進(jìn)行篩選。仿真實(shí)驗(yàn)及實(shí)測沖擊信號分析表明,雙值區(qū)間準(zhǔn)則可方便地選取出EEMD沖擊故障特征信號。(3)由于EEMD沖擊故障特征信號在本質(zhì)上仍然為沖擊脈沖信號與傳遞函數(shù)卷積計(jì)算的結(jié)果,為了消除傳遞函數(shù)的干擾,對沖擊脈沖信號進(jìn)行自適應(yīng)特征提取,本文將MED方法應(yīng)用于EEMD沖擊故障特征信號。重點(diǎn)分析了影響MED提取沖擊脈沖信號效果的主要因素,提出EEMD-MED和形態(tài)學(xué)濾波的沖擊脈沖信號增強(qiáng)方法,仿真實(shí)驗(yàn)和實(shí)例研究均表明該方法可有效地增強(qiáng)MED沖擊脈沖信號的提取效果。(4)針對MED沖擊脈沖信號在進(jìn)行包絡(luò)解調(diào)時會出現(xiàn)大量高次諧波成分的問題,本文利用沖擊脈沖信號的卷積性質(zhì),將脈沖信號與高斯核函數(shù)進(jìn)行卷積運(yùn)算并對卷積結(jié)果進(jìn)行傅里葉變換,提出沖擊脈沖信號的解調(diào)思路。根據(jù)短時傅里葉變換的計(jì)算過程是將原信號與高斯核函數(shù)進(jìn)行卷積,且其計(jì)算過程與MED脈沖信號的解調(diào)思路一致,本文提出增強(qiáng)MED短時傅里葉變換的脊線解調(diào)故障診斷方法。通過滾動軸承實(shí)例分析,并與EEMD包絡(luò)解調(diào)方法及譜峭度包絡(luò)解調(diào)方法進(jìn)行對比,驗(yàn)證了該方法的有效性。
[Abstract]:The vibration signal is the most intuitionistic reflection of the mechanical system behavior. It carries a large number of equipment state information, which can reflect the dynamic change process of the mechanical system in time. Therefore, vibration signals are widely used in state monitoring and fault diagnosis. Feature extraction is the key technology of fault diagnosis, feature information for non-stationary and nonlinear signals effectively extract fault impact from the complex, this paper studies EEMD and MED two kinds of adaptive fault feature extraction method, the main research work is as follows: (1) easy to appear for process of the EEMD method in the mean curve structure the envelope of the problem, according to the extreme value redundancy limit exists or pseudo extremum phenomenon, put forward the local extremum of mean envelope curve construction method. Then, this method replaces the construction method of EEMD's original mean curve to form the local extreme envelope EEMD method. By comparing and analyzing with EEMD method, it is found that the local extreme value envelope EEMD method can get better experimental results in eliminating modal confusion. (2) for the problem of how to extract the characteristic information of impact fault from multiple IMF decomposed by EEMD, by defining the logical relationship between "subordinate" and "non subordinate" of two valued feature parameters, we propose a two valued interval rule that selects EEMD impulse fault characteristic signal. According to the sensitivity of kurtosis to the impact signal, the maximum spectral kurtosis band interval is used as a dual characteristic parameter, and the double fault interval criterion is applied to screen the characteristic signal of impact fault. The simulation experiment and the measured impact signal analysis show that the dual value interval criterion can easily select the EEMD impact fault characteristic signal. (3) the impact of the EEMD fault characteristic signal in essence is still the impulse signal and the transfer function of the convolution calculation results, in order to eliminate the interference of the transfer function, the impulse signal adaptive feature extraction, the MED method is applied to EEMD impact fault characteristic signal. The main factors that affect the effect of MED on extracting impulse signal are analyzed. A method of enhancing impulse pulse signal based on EEMD-MED and morphological filtering is proposed. Simulation experiments and case studies show that the method can effectively enhance the extraction effect of MED impulse signal. (4) the impact of the MED pulse signal will appear a large number of harmonics in the envelope demodulation problem, convolution of impulse signals using, convolution and Fourier transform of the convolution result pulse signal with Gauss kernel function, put forward ideas on pulse signal demodulation at. According to the computation process of short-time Fourier transform, the original signal is convoluted with Gauss kernel function, and its computation process is consistent with the demodulation idea of MED pulse signal. In this paper, a MED fault diagnosis method based on ridge transform demodulation is proposed. The validity of the method is verified by comparing the EEMD envelope demodulation method and the spectral kurtosis envelope demodulation method through the analysis of the rolling bearing case.
【學(xué)位授予單位】：上海大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TN911.7

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相關(guān)期刊論文 前1條

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本文編號：1342074