基于包络谱分析的振动信号研究及其FPGA实现

发布时间：2018-05-13 01:19

本文选题：振动信号 + 小波分析　；参考：《西安理工大学》2017年硕士论文

【摘要】：振动是机械设备运行当中的一种常见现象。通过对振动信号的提取可以分析机械设备的运行状态。由于滚动轴承是机械设备的关键零件,它的好坏与设备的正常与否息息相关,因此对滚动轴承的振动信号进行研究有重要的意义。包络谱分析法是振动信号常用的分析方法,为了提高算法运行的速度,快速得到结果,可以通过FPGA来实现。为完成以上要求,本文设计了一个滚动轴承振动测试系统并且开展了以下工作:(1)研制振动信号采集的硬件模块。根据振动信号的特点选取了振动加速度传感器作为数据的拾取装置,通过调理电路的设计对采集到的信号进行预处理。数模转换电路将处理过后的信号送入控制芯片当中进行存储和处理,经过无线Wi-Fi传输到终端设备当中。(2)振动信号特征的提取。首先对常用的振动信号的分析方法进行了阐述,详细介绍了幅值域分析、傅里叶分析、小波分析、Hilbert包络谱分析的理论。对比这几种理论方法,选取了一种基于小波分解和Hilbert包络谱的振动信号分析方法。利用小波理论对信号进行不同频段的分解,提取出含有故障信息的频段,用Hilbert包络谱分析找出故障特征频率,同时在FPGA上实现该分析方法。(3)在滚动轴承实验平台上,利用振动数据采集的硬件装置,采集存在损伤的故障轴承,结合小波和Hilbert包络谱对其进行分析,得到故障特征频率,对比FPGA和MATLAB得到的结果。通过实验,将FPGA和MATLAB所得到故障频率与理论值进行对照,证明了该振动信号采集分析系统是可行的,能够快速有效的提取振动信号的特征信息。
[Abstract]:Vibration is a common phenomenon in the operation of mechanical equipment. The operating state of mechanical equipment can be analyzed by extracting vibration signal. Because the rolling bearing is the key part of the mechanical equipment, its quality is closely related to the normal or not of the equipment, so it is of great significance to study the vibration signal of the rolling bearing. Envelope spectrum analysis is a common method for vibration signal analysis. In order to improve the speed of the algorithm and get the results quickly, it can be realized by FPGA. In order to fulfill the above requirements, a rolling bearing vibration testing system is designed and the following work is carried out: 1) the hardware module of vibration signal acquisition is developed. According to the characteristics of the vibration signal, the vibration acceleration sensor is selected as the data pickup device, and the collected signal is preprocessed by the design of the conditioning circuit. The digital-to-analog conversion circuit sends the processed signal into the control chip for storage and processing, and then transmits it to the terminal device via wireless Wi-Fi to extract the characteristic of the vibration signal. Firstly, the common methods of vibration signal analysis are described, and the theory of amplitude range analysis, Fourier analysis and Hilbert envelope spectrum analysis is introduced in detail. Compared with these methods, a vibration signal analysis method based on wavelet decomposition and Hilbert envelope spectrum is selected. The wavelet theory is used to decompose the signal in different frequency bands, and the frequency band containing fault information is extracted, and the fault characteristic frequency is found by Hilbert envelope analysis. At the same time, the analysis method is realized on FPGA. The method is implemented on the rolling bearing experimental platform. Using the hardware device of vibration data acquisition, the fault bearing with damage is collected. The fault characteristic frequency is obtained by combining wavelet and Hilbert envelope spectrum, and the results obtained by FPGA and MATLAB are compared. Through experiments, the fault frequency obtained by FPGA and MATLAB is compared with the theoretical value. It is proved that the vibration signal acquisition and analysis system is feasible and can extract the characteristic information of vibration signal quickly and effectively.
【学位授予单位】：西安理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TH133.33;TP212

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