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大型磨机故障诊断方法的研究

发布时间:2018-12-05 21:39
【摘要】:磨机机械是工业上应用非常广泛的设备之一,由于其自身结构的复杂性,并且工作时的工况比较恶劣,因此,对磨机的故障诊断要比常规设备要求高、难度大。而随着振动测试和信号分析等相关技术的不断发展,以振动信号检测、处理和分析为基础的故障诊断技术已成为故障诊断领域一个重要的研究方向。EMD方法是一种新型的信号处理方法,一经提出,就得到了迅速的发展,并在故障诊断领域得到了广泛的应用。本文基于EMD方法,研究了几种时频分析方法,并将这些方法运用于实际的磨机故障诊断中,准确识别出了故障,取得了很好的效果。首先,详细介绍了EMD方法的理论,包括EMD理论中瞬时频率和本征模函数的概念,并细述了EMD分解的过程,然后针对EMD存在的端点效应问题和虚假分量问题进行了改进,并做了信号仿真的验证。其次,基于EMD方法,研究了能量算子解调法、分频段加权时频熵法和局部Hilbert谱分析法,对于能量算子解调法,通过与传统的Hilbert解调法对比,验证了该方法的优越性;对于分频段加权时频熵法,是在原时频熵法上的改进;对于局部Hilbert谱分析法,包括Hilbert时频谱和Hilbert边际谱,并对其做了改进;对以上三种方法,都分别利用仿真信号和模拟实验,验证了这些方法在信号分析中的有效性。最后,利用基于EMD方法的上述三种方法对磨机故障进行了诊断,包括减速机内的齿轮、轴承,以及磨机的磨辊部件,三个部分。研究结果表明,基于EMD方法的能量算子解调法、分频段加权时频熵法和局部Hilbert谱分析法,在磨机各部分故障诊断中具有很好的效果。
[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.
【学位授予单位】:南京航空航天大学
【学位级别】:硕士
【学位授予年份】:2015
【分类号】:TH165.3

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