圆柱滚子轴承速度型振动信号分析系统

发布时间：2018-05-08 23:23

本文选题：圆柱滚子轴承 + 故障诊断　；参考：《河南科技大学》2017年硕士论文

【摘要】：圆柱滚子轴承多用于高速、重载场合,当轴承出现剥落、裂纹等局部故障时,故障部位将引起较大的瞬时冲击,严重影响主机运行的稳定性和生产安全。因此,及时识别轴承的早期故障对保障机械系统的安全运行、避免重大事故的发生具有重要意义。目前针对滚动轴承故障诊断技术的研究主要集中于球轴承,而对圆柱滚子轴承早期故障诊断的研究较少,且多集中于故障分析模型的建立和故障特征仿真分析。圆柱滚子轴承由于其结构及工况特点使得其早期故障振动信号为准周期信号,且一个周期内振动脉冲较少,振动信号信噪比较低。相对于球类轴承,圆柱滚子轴承为线接触,对缺陷的敏感度较低,造成在相同故障尺寸下圆柱滚子轴承比球轴承更难检测。本文针对圆柱滚子轴承故障诊断提出了两种故障诊断方法:一种是基于希尔伯特振动分解(hilbert vibration decomposition,HVD)降噪、多频段局部最优频带叠加的滚动轴承故障诊断方法;另一种是基于峭度曲线和频谱叠加的滚动轴承故障检测方法。本文主要研究内容及结论如下:1、针对轴承出现故障时在频域内出现多个共振峰的特点,将轴承振动信号进行频段划分,提取多个局部最优频带,并将其频谱进行叠加,形成基于HVD降噪和多频段频谱叠加的圆柱滚子轴承故障诊断方法。针对快速峭度图频带划分方法的不足,提出一种基于峭度曲线的频带提取方法,并通过频谱叠加进一步突出轴承故障特征,奠定了圆柱滚子轴承早期故障特征的理论基础。2、对圆柱滚子轴承进行了振动试验,首先通过在圆柱滚子轴承不同零件上加工3mm凹坑来模拟含有较大故障的轴承,通过对含有不同故障的轴承进行振动分析,提取了不同故障类型的故障特征。随后在圆柱滚子轴承不同零件上加工0.4mm凹坑来模拟轴承的早期故障,利用本文提出的故障诊断方法对含有早期故障轴承的振动信号进行处理,提取了圆柱滚子轴承的故障特征,并与快速峭度图算法进行了对比,验证了本文故障诊断方法的优越性。3、完成了圆柱滚子轴承故障判断系统的搭建,根据圆柱滚子轴承故障特征完成圆柱滚子轴承故障类型的自动判断。
[Abstract]:Cylindrical roller bearings are often used in high speed and heavy load situations. When the bearing occurs local faults such as spalling and cracking the fault site will cause a large instantaneous impact which seriously affects the stability of the main engine and the safety of production. Therefore, it is of great significance to identify the early faults of bearing in time to ensure the safe operation of mechanical system and to avoid the occurrence of major accidents. At present, the research on fault diagnosis of rolling bearing is mainly focused on ball bearing, but the research on early fault diagnosis of cylindrical roller bearing is less, and mostly on the establishment of fault analysis model and simulation analysis of fault characteristics. Due to its structure and working conditions, the cylindrical roller bearing has its early fault vibration signal quasi periodic signal, and the vibration pulse is less and the signal-to-noise ratio of the vibration signal is lower in one period. Compared with ball bearings, cylindrical roller bearings are in linear contact, and are less sensitive to defects, resulting in more difficult detection of cylindrical roller bearings than ball bearings in the same fault size. In this paper, two fault diagnosis methods for cylindrical roller bearing are proposed: one is based on Hilbert vibration decompositionHVD (Hilbert vibration decompositionHVD) for noise reduction and multi-frequency band local optimal frequency band superposition method for rolling bearing fault diagnosis; The other is the rolling bearing fault detection method based on kurtosis curve and spectrum superposition. The main contents and conclusions of this paper are as follows: 1. Aiming at the characteristic of multiple resonance peaks in frequency domain when bearing failure occurs, the bearing vibration signal is divided into frequency bands, several local optimal frequency bands are extracted, and its frequency spectrum is superposed. A fault diagnosis method for cylindrical roller bearing based on HVD noise reduction and multi-frequency spectrum superposition is developed. Aiming at the shortage of fast kurtosis chart frequency band partition method, a frequency band extraction method based on kurtosis curve is proposed, and the bearing fault feature is further highlighted by spectrum superposition. The theoretical foundation of the early fault characteristics of cylindrical roller bearing is established. The vibration test of cylindrical roller bearing is carried out. Firstly, the bearing with larger fault is simulated by machining 3mm pits on different parts of cylindrical roller bearing. Through vibration analysis of bearing with different faults, fault characteristics of different fault types are extracted. Then 0.4mm pits are processed on different parts of cylindrical roller bearing to simulate the early fault of bearing. The vibration signal of bearing with early fault is processed by using the fault diagnosis method proposed in this paper, and the fault characteristics of cylindrical roller bearing are extracted. Compared with the fast kurtosis graph algorithm, the superiority of the fault diagnosis method in this paper is verified, and the fault judgement system of cylindrical roller bearing is built. According to the fault characteristics of cylindrical roller bearing, the fault type of cylindrical roller bearing is automatically judged.
【学位授予单位】：河南科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TH133.33

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