TBM主轴承早期故障声发射信号诊断与研究

发布时间：2018-04-26 02:38

本文选题：声发射 + TBM　；参考：《石家庄铁道大学》2013年硕士论文

【摘要】：滚动轴承作为旋转机械的关键部件之一,对设备的运行安全影响重大。由于工作条件、尺寸设计、使用时间等因素的约束,其又是旋转机械中最容易出现故障的零件之一,因此近些年来,针对滚动轴承的状态监测和故障诊断技术成为了热点话题。常用的振动检测技术在该领域已经取得了较好的认可度,但是受环境噪声和信号衰减等因素的影响,传统的振动检测技术和信号分析处理技术对于轴承早期的微弱故障诊断并不是很理想。相比下,声发射检测技术能够更好的发现轴承早期故障特征,同时形态学的信号处理方法也较传统的处理方法有自己的优势。本文首介绍了声发射检测技术及数学形态学方法的国内外的研究现状。详细阐述了声发射检测技术、声发射信号的特点、声发射信号的常用处理方法,同时介绍了数学形态学方法的产生发展情况及其基本数学原理。本文选取重庆地铁六号线铜锣山隧道施工复合式TBM主轴承为研究对象,通过熟悉TBM主要结构构造,工作原理,作业方式等,设计了滚动轴承声发射试验,进行了声发射信号采集试验,并取得较理想的分析信号。根据信号的时域图像特征及相关技术人员的数据支持,初步对TBM主轴承的工作状态做了判断。本文研究了时变峭度法在轴承声发射信号故障特征提取中的应用,利用了峭度对冲击信号敏感的特点,将信号分段来计算峭度指标,绘制时变峭度图,观察峭度值走势,来判别故障。通过对TBM实测信号的分析处理,结果证明了时变峭度分析法是一种快捷有效的轴承故障诊断方法。本文研究了形态学方法在滚动轴承故障信号处理中的应用,通过构造不同的形态算子和结构元素,用多尺度形态滤波器实现了同时抑制噪声和突出脉冲冲击特征的目的。实验数据证明了形态学变换的信号分析方法的可行性及有效性。本课题的研究对于TBM的状态监测及维护检修具有指导性意义。
[Abstract]:As one of the key components of rotating machinery, rolling bearing has a great influence on the safety of the equipment. Due to the constraints of working conditions, dimension design and service time, it is one of the most prone parts in rotating machinery, so in recent years, the status monitoring and fault diagnosis technology for rolling bearings has become a hot topic. The commonly used vibration detection techniques have achieved good recognition in this field, but are affected by environmental noise and signal attenuation. Traditional vibration detection and signal analysis are not ideal for early weak fault diagnosis of bearings. Compared with the conventional methods, the acoustic emission detection technique can better detect the early fault features of bearings, and the morphological signal processing method also has its own advantages. In this paper, the present situation of acoustic emission detection and mathematical morphology is introduced. The acoustic emission detection technology, the characteristics of acoustic emission signals and the common processing methods of acoustic emission signals are described in detail. At the same time, the generation and development of mathematical morphology methods and their basic mathematical principles are introduced. In this paper, the composite TBM main bearing of Chongqing Metro Line 6 is selected as the research object, and the acoustic emission test of rolling bearing is designed by familiar with the main structure, working principle and operation mode of TBM. The acoustic emission signal acquisition test is carried out, and the ideal analysis signal is obtained. According to the time domain image feature of the signal and the data support of the related technicians, the working state of the TBM main bearing is preliminarily judged. In this paper, the application of time-varying kurtosis method in fault feature extraction of bearing acoustic emission signal is studied. By using kurtosis sensitivity to impact signal, the kurtosis index is calculated by the signal segment, the time-varying kurtosis chart is drawn, and the trend of kurtosis value is observed. To identify faults. By analyzing and processing the measured signals of TBM, it is proved that the time-varying kurtosis analysis method is a fast and effective method for bearing fault diagnosis. In this paper, the application of morphological method in fault signal processing of rolling bearing is studied. By constructing different morphological operators and structural elements, multi-scale morphological filter is used to simultaneously suppress noise and highlight impulse impulse characteristics. Experimental data show the feasibility and effectiveness of the signal analysis method based on morphological transformation. The research of this subject has instructive significance for condition monitoring and maintenance of TBM.
【学位授予单位】：石家庄铁道大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TH133.33;TH165.3

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