發(fā)布時(shí)間：2018-01-02 12:26

  本文關(guān)鍵詞：基于小波分析的高速牽引電機(jī)軸承故障診斷研究　出處：《北京交通大學(xué)》2011年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 故障診斷 小波包 高速牽引電機(jī)軸承 EMD分解

【摘要】：近年來,高速列車的出現(xiàn)對高速牽引電機(jī)軸承的工作狀態(tài)提出了嚴(yán)格的要求。國外機(jī)械設(shè)備狀態(tài)監(jiān)測和故障診斷技術(shù)已經(jīng)進(jìn)入實(shí)用化階段。我國故障診斷技術(shù)也有20多年的發(fā)展,不論在故障診斷理論和方法上,還是在工程實(shí)踐及監(jiān)測診斷產(chǎn)品的研發(fā)中,都需要加速發(fā)展。本文采用小波的希爾伯特變換、小波包變換、EMD經(jīng)驗(yàn)?zāi)�態(tài)分解方法對高速牽引電機(jī)軸承故障診斷的時(shí)頻分析及故障識(shí)別方法進(jìn)行了深入研究,并采用Lab VIEW與Matlab相結(jié)合的方法開發(fā)了診斷平臺(tái)。 (1)小波和Hilbert變換相結(jié)合的高速牽引電機(jī)滾動(dòng)軸承故障診斷方法的研究。 首先利用Daubechies小波對故障信號(hào)進(jìn)行小波的分解,然后提取出包含故障特征信息的分解層。對選取的小波層進(jìn)行快速傅里葉變換并提取出特征頻率。與理論上的特征頻率進(jìn)行對比,有效判定軸向線性裂紋故障類型。 (2)小波包方法在高速牽引電機(jī)滾動(dòng)軸承故障診斷中的應(yīng)用研究。 提出了在小波包分解后的節(jié)點(diǎn)進(jìn)行以能量為依據(jù)的最佳節(jié)點(diǎn)方法。并采取均值與方差和為閾值的小波包去噪方式對信號(hào)去噪和重組。選取小波包進(jìn)行快速傅里葉變換,提取出特征故障頻率,能簡便有效地判定軸向線性裂紋故障類型。 (3)將小波包和EMD(Empirical Mode Decomposition)分解二者有機(jī)結(jié)合,探索研究其在高速牽引電機(jī)軸承故障診斷中的應(yīng)用。 將小波包、EMD分解應(yīng)用到高速牽引電機(jī)軸承故障診斷中。在診斷前,首先進(jìn)行小波包去噪,接著進(jìn)行EMD分解,然后選擇與原始信號(hào)相關(guān)系數(shù)最大的一層再次進(jìn)行的小波包分解,并選取合適的小波包進(jìn)行頻譜分析,最后進(jìn)行故障狀態(tài)識(shí)別。該方法雖能診斷出軸向線性裂紋故障特征,但達(dá)到分解平衡耗時(shí)較長,不易與本文程序結(jié)合。 (4)試驗(yàn)臺(tái)組合以及實(shí)驗(yàn)研究。 利用實(shí)驗(yàn)臺(tái)、數(shù)據(jù)采集設(shè)備,并根據(jù)小波分析理論進(jìn)行實(shí)驗(yàn)驗(yàn)證。分別采用小波的Hilbert變換、小波包分解和EMD經(jīng)驗(yàn)分解的方法對軸向線性裂紋故障軸承診斷進(jìn)行實(shí)用分析,總結(jié)出本文最有效的診斷方法—小波包分解。 (5)基于Lab VIEW和Matlab編程的軸承診斷軟件平臺(tái)開發(fā)。 結(jié)合Matlab良好的數(shù)據(jù)處理功能,應(yīng)用yulewalk多通帶濾波器對頻域信號(hào)進(jìn)行濾波,采用虛擬儀器技術(shù)設(shè)計(jì)開發(fā)出故障診斷軟件平臺(tái),最終診斷出故障特征。
[Abstract]:In recent years , the occurrence of high - speed train has put forward strict requirements for the working state of high - speed traction motor bearings . The state monitoring and fault diagnosis technology of mechanical equipment abroad has entered the practical stage . The fault diagnosis technology in China has been developed in more than 20 years . In this paper , the time - frequency analysis and fault identification method of high - speed traction motor bearing fault diagnosis are studied in detail in the theory and method of fault diagnosis . ( 1 ) The research of fault diagnosis method of high speed traction motor rolling bearing combining wavelet and Hilbert transform . Firstly , Daubechies wavelet transform is used to decompose the fault signal , then the decomposition layer containing fault feature information is extracted . The selected wavelet layer is fast Fourier transformed and the characteristic frequency is extracted . Compared with the theoretical characteristic frequency , the fault type of axial linear crack is effectively determined . ( 2 ) The application of wavelet packet method in fault diagnosis of high speed traction motor rolling bearing . In this paper , the optimal node method based on energy is put forward , which is based on energy . The wavelet packet denoising method is used to denoise and recombine the signal . The wavelet packet is selected for fast Fourier transform , and the characteristic fault frequency is extracted . It can be used to determine the fault type of axial linear crack simply and effectively . ( 3 ) Combining the decomposition of the wavelet packet with EMD ( Empirical Mode Decomposition ) , this paper explores its application in fault diagnosis of high - speed traction motor bearing . The wavelet packet and EMD are applied to the fault diagnosis of high - speed traction motor bearings . Before the diagnosis , wavelet packet de - noising is firstly carried out , then EMD is decomposed , then the wavelet packet with the largest correlation coefficient of the original signal is decomposed , and the proper wavelet packet is selected for frequency spectrum analysis , and finally the fault state identification is carried out . ( 4 ) Test bench combination and experimental study . This paper makes a practical analysis of the diagnosis of axial linear crack by means of Hilbert transform , wavelet packet decomposition and EMD ' s empirical decomposition , and summarizes the most effective diagnosis method - wavelet packet decomposition . ( 5 ) Development of bearing diagnosis software platform based on Lab VIEW and Matlab programming . Combined with the good data processing function of Matlab , the frequency domain signal is filtered using yulewalk multi - pass band filter , and the fault diagnosis software platform is developed by using the virtual instrument technology design , and finally the fault feature is diagnosed .

【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類號(hào)】：TH133.33;TH165.3

【引證文獻(xiàn)】

相關(guān)期刊論文 前1條

1 王金福;李富才;;機(jī)械故障診斷技術(shù)中的信號(hào)處理方法:時(shí)頻分析[J];噪聲與振動(dòng)控制;2013年03期

相關(guān)碩士學(xué)位論文 前2條

1 周瑜;氣固流化床結(jié)片監(jiān)測系統(tǒng)設(shè)計(jì)及算法研究[D];北京化工大學(xué);2012年

2 沈智慧;基于LabVIEW的電機(jī)振動(dòng)監(jiān)測系統(tǒng)設(shè)計(jì)[D];東北石油大學(xué);2013年

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本文編號(hào)：1369220