【摘要】：磨機(jī)機(jī)械是工業(yè)上應(yīng)用非常廣泛的設(shè)備之一,由于其自身結(jié)構(gòu)的復(fù)雜性,并且工作時的工況比較惡劣,因此,對磨機(jī)的故障診斷要比常規(guī)設(shè)備要求高、難度大。而隨著振動測試和信號分析等相關(guān)技術(shù)的不斷發(fā)展,以振動信號檢測、處理和分析為基礎(chǔ)的故障診斷技術(shù)已成為故障診斷領(lǐng)域一個重要的研究方向。EMD方法是一種新型的信號處理方法,一經(jīng)提出,就得到了迅速的發(fā)展,并在故障診斷領(lǐng)域得到了廣泛的應(yīng)用。本文基于EMD方法,研究了幾種時頻分析方法,并將這些方法運用于實際的磨機(jī)故障診斷中,準(zhǔn)確識別出了故障,取得了很好的效果。首先,詳細(xì)介紹了EMD方法的理論,包括EMD理論中瞬時頻率和本征模函數(shù)的概念,并細(xì)述了EMD分解的過程,然后針對EMD存在的端點效應(yīng)問題和虛假分量問題進(jìn)行了改進(jìn),并做了信號仿真的驗證。其次,基于EMD方法,研究了能量算子解調(diào)法、分頻段加權(quán)時頻熵法和局部Hilbert譜分析法,對于能量算子解調(diào)法,通過與傳統(tǒng)的Hilbert解調(diào)法對比,驗證了該方法的優(yōu)越性;對于分頻段加權(quán)時頻熵法,是在原時頻熵法上的改進(jìn);對于局部Hilbert譜分析法,包括Hilbert時頻譜和Hilbert邊際譜,并對其做了改進(jìn);對以上三種方法,都分別利用仿真信號和模擬實驗,驗證了這些方法在信號分析中的有效性。最后,利用基于EMD方法的上述三種方法對磨機(jī)故障進(jìn)行了診斷,包括減速機(jī)內(nèi)的齒輪、軸承,以及磨機(jī)的磨輥部件,三個部分。研究結(jié)果表明,基于EMD方法的能量算子解調(diào)法、分頻段加權(quán)時頻熵法和局部Hilbert譜分析法,在磨機(jī)各部分故障診斷中具有很好的效果。
[Abstract]:Mill machinery is one of the most widely used equipments in industry. Because of its complexity of structure and bad working conditions, the fault diagnosis of mill is more difficult than that of conventional equipment. With the continuous development of vibration testing and signal analysis and other related technologies, vibration signal detection, The technology of fault diagnosis based on processing and analysis has become an important research direction in the field of fault diagnosis. EMD method is a new kind of signal processing method. And has been widely used in the field of fault diagnosis. In this paper, based on EMD method, several time-frequency analysis methods are studied, and these methods are applied to the actual mill fault diagnosis, the fault is identified accurately, and good results are obtained. Firstly, the theory of EMD method is introduced in detail, including the concepts of instantaneous frequency and eigenmode function in EMD theory, and the process of EMD decomposition is described in detail. Then, the endpoint effect problem and false component problem existing in EMD are improved. And the signal simulation is done. Secondly, based on the EMD method, the energy operator demodulation method, the frequency-divided weighted time-frequency entropy method and the local Hilbert spectrum analysis method are studied. Compared with the traditional Hilbert demodulation method, the superiority of this method is verified. The local Hilbert spectrum analysis method, including the Hilbert time-frequency spectrum and the Hilbert marginal spectrum, is an improvement on the original time-frequency entropy method, and the local Hilbert spectral analysis method includes the Hilbert time-frequency spectrum and the Hilbert marginal spectrum. For the above three methods, the effectiveness of these methods in signal analysis is verified by using the simulation signal and the simulation experiment, respectively. Finally, the three methods based on EMD method are used to diagnose the malfunction of the mill, including the gear in the reducer, the bearing, and the roller parts of the mill. The results show that the energy operator demodulation method based on EMD method, frequency band weighted time-frequency entropy method and local Hilbert spectrum analysis method have good results in the fault diagnosis of various parts of mill.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TH165.3

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