基于小波变换的滚动轴承在线检测系统研究

发布时间：2018-04-14 09:02

本文选题：滚动轴承 + 小波变换　；参考：《安徽工程大学》2014年硕士论文

【摘要】：滚动轴承作为旋转机械的重要组成部分,滚动轴承的工况直接关系到整个设备的运行性能,因此对生产的滚动轴承进行快速准确的故障检测将有非常重要的现实意义。本文完成的滚动轴承在线检测系统,利用小波变换的方法对滚动轴承的振动信号进行特征分析,实现诊断滚动轴承故障的目的,同时提高了检测系统的智能化水平。本文详细的介绍了整个在线检测系统的运行开发过程,检测系统是以工控机、数据采集卡为核心,以传感器、生产线控制装置为辅并具有较高自动化水平机电一体化系统,涉及了计算机控制技术、传感器技术以及信号分析处理技术等。在系统的硬件系统的设计过程中,充分考虑了各方面的因素。如在传感器的选型上,充分尊重传感器的选型原则,并力求保证其测量的精度。传感器采集的滚动轴承的振动信号经过滤波后,通过数据采集卡传送到上位机,就完成了对振动信号的采集与传输工作。在检测系统中利用上位机提供了良好的人机交互界面,可以进行故障检测的监测以及检测结果的查询和储存,同时对传送带的运转进行控制,使整个系统的自动化程度得到加强。当滚动轴承出现局部表面损伤后,在运行的过程中会周期性与其他部件发生撞击而产生冲击脉冲力。由于冲击脉冲力的频带较宽,会包含在信号的各个固有频率内,激起滚动轴承的各个固有振动,把原来的平稳信号变为非平稳信号。针对滚动轴承会出现的问题,将小波变换方法应用于对其振动信号的分析与处理中。通过与一些传统方法的对比,说明了小波变换在分析信号过程中所具有的优越性。本文详细介绍了利用MATLAB中小波分析工具对滚动轴承的振动信号进行分解,根据小波系数绘出能量分布图,对出现故障的频段进行小波包重构,从这些结果中可以直观便捷的观察出滚动轴承的故障特征。验证表明,小波包拥有较好的故障诊断能力,本文利用小波包变换与能量谱的方法,成功的诊断出滚动轴承的常见故障,取得了较好的效果。
[Abstract]:As an important part of rotary machinery, the working condition of rolling bearing is directly related to the operation performance of the whole equipment. Therefore, it is of great practical significance to carry out rapid and accurate fault detection of rolling bearings.In this paper, the on-line detection system of rolling bearing is developed. The characteristic analysis of vibration signal of rolling bearing is carried out by the method of wavelet transform, which realizes the purpose of diagnosing the fault of rolling bearing, and at the same time improves the intelligent level of the detection system.This paper introduces the running and developing process of the whole on-line detection system in detail. The detection system is based on industrial control computer, data acquisition card, sensor and production line control device, and has a high automation level mechatronics system.Computer control technology, sensor technology and signal analysis and processing technology are involved.In the design process of the system hardware system, all factors are fully considered.For example, the principle of sensor selection is fully respected and the accuracy of measurement is guaranteed.After the vibration signal of the rolling bearing collected by the sensor is filtered and transmitted to the upper computer through the data acquisition card, the acquisition and transmission of the vibration signal is completed.In the detection system, the upper computer provides a good man-machine interface, which can monitor the fault detection, query and store the test results, and control the running of the conveyor belt.Enhance the automation of the whole system.When the rolling bearing appears local surface damage, the impact pulse force will occur periodically during operation.Because of the wide frequency band of impulse force, it will be included in each natural frequency of the signal, which will arouse the inherent vibration of the rolling bearing and change the original stationary signal into the non-stationary signal.Aiming at the problems of rolling bearing, wavelet transform method is applied to the analysis and processing of its vibration signal.The advantages of wavelet transform in signal analysis are illustrated by comparison with some traditional methods.This paper introduces in detail how to decompose the vibration signal of rolling bearing by using MATLAB wavelet analysis tool, draw the energy distribution map according to the wavelet coefficient, and reconstruct the frequency band of fault by wavelet packet.From these results, the fault characteristics of rolling bearings can be observed intuitively and conveniently.The results show that the wavelet packet has better fault diagnosis ability. The method of wavelet packet transform and energy spectrum is used to diagnose the common faults of rolling bearing successfully, and good results are obtained.
【学位授予单位】：安徽工程大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TH133.33;TH165.3

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