高速线材精轧机在线振动监测与故障诊断方法研究

发布时间：2018-03-21 02:49

本文选题：精轧机　切入点：齿轮箱　出处：《东北大学》2011年硕士论文　论文类型：学位论文

【摘要】：精轧机组是线材厂的关键设备,对精轧机组进行在线监测,可以提前预知设备的工作状态以及故障的发展趋势,对保证企业的安全生产有重大意义。锥齿轮箱是精轧机的重要零部件,因此研究锥齿轮箱的诊断技术对于降低设备维修费用,提高产品质量和市场竞争力具有重要的工程应用价值。目前,国内比较通行的办法是利用便携式仪器,对关键设备进行点检,按照一定周期采集设备的振动数据进行分析。但是,此种方法也存在一定局限性,如无法随时对数据进行采集,导致对数据的分析缺少连续性等。论文针对上述问题开展研究,设计开发了基于C/S模式的高速线材精轧机在线振动监测系统,该系统利用安装在设备上的振动传感器对设备的振动数据进行采集分析后以曲线形式反映在系统工作站,起到提前对故障进行预警的作用。论文在参阅国内外相关最新研究成果的基础上,首先,针对轧机生产线的关键设备——锥齿轮箱,重点讨论了锥齿轮箱主要零部件滚动轴承和齿轮的常见故障形式、故障特征频率,讨论了齿轮箱振动信号调幅和调频的产生机理,并针对某钢高线厂的高速线材轧机,计算了某架机组的故障特征频率。论文阐述了常见振动信号的特征提取方法,主要包括振动信号时域波形分析、统计指标分析、幅值谱和包络谱分析、自相关分析和小波分析等。为后续的在线监测系统开发及故障诊断奠定了理论基础。针对高速线材轧机锥齿轮箱的特点,设计了在线监测系统的总体方案,完成了精轧机设备实时在线监测系统的开发。整个系统分为机组管理、数据采集、在线监测等几个功能模块,采用统计棒图、波形图、频谱图和趋势图以及峰值、峰峰值、有效值和峭度值等时域特征参数清楚地反映了设备的运行状态。最后,将故障诊断理论和在线监测系统应用到某钢高线厂精轧机状态监测与故障诊断中,成功捕捉到轴承内圈点蚀、保持架损坏及锥箱齿轮断齿等故障,避免了恶性事故的发生,取得了显著的经济效益。
[Abstract]:Finishing mill unit is the key equipment in wire mill. On-line monitoring of finishing mill unit can predict the working state of the equipment and the development trend of fault ahead of time. Bevel gearbox is an important part of finishing mill, so studying the diagnostic technology of bevel gearbox can reduce the maintenance cost of equipment. Improving product quality and market competitiveness has important engineering application value. At present, the common method in China is to make use of portable instruments to carry out spot inspection of key equipment. The vibration data of the equipment are analyzed according to a certain period. However, this method also has some limitations, such as the data can not be collected at any time, resulting in the lack of continuity in the analysis of the data. Aiming at the above problems, the paper designs and develops the on-line vibration monitoring system of high-speed wire finishing mill based on C / S mode. The system uses the vibration sensor installed on the equipment to collect and analyze the vibration data of the equipment, and then it is reflected in the system workstation in the form of curves, which plays the role of warning the faults in advance. On the basis of referring to the latest research results at home and abroad, firstly, aiming at the key equipment of rolling mill production line, bevel gear box, the common fault forms of rolling bearing and gear of main parts of bevel gear box are discussed emphatically. The mechanism of amplitude modulation and frequency modulation of gear box vibration signal is discussed, and the fault characteristic frequency of a certain unit is calculated for a high speed wire mill in a steel wire mill. In this paper, the methods of feature extraction of common vibration signals are described, including time domain waveform analysis, statistical index analysis, amplitude spectrum and envelope spectrum analysis. Autocorrelation analysis and wavelet analysis are the theoretical basis for the following on-line monitoring system development and fault diagnosis. According to the characteristics of bevel gearbox of high-speed wire mill, the overall scheme of on-line monitoring system is designed. The development of real-time on-line monitoring system for finishing mill equipment is completed. The whole system is divided into several functional modules, such as unit management, data acquisition, on-line monitoring and so on. The system adopts statistical bar diagram, waveform chart, spectrum chart and trend chart, as well as peak and peak, peak and peak, etc. The time domain characteristic parameters such as effective value and kurtosis value clearly reflect the running state of the equipment. Finally, the fault diagnosis theory and the on-line monitoring system are applied to the condition monitoring and fault diagnosis of the finishing mill in a high wire mill. The faults such as pitting of the inner ring of the bearing, damage of the cage and broken teeth of the bevel box gear are successfully captured. The malignant accidents are avoided and remarkable economic benefits are obtained.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：TG333;TH165.3

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