基于LabVIEW的电机滚动轴承故障诊断系统的研究与实现

发布时间：2018-05-04 15:03

本文选题：滚动轴承 + 故障诊断　；参考：《安徽工业大学》2017年硕士论文

【摘要】：电机是一种极重要的旋转机械。滚动轴承是电机设备中最常用的零部件之一,也是易损件之一。滚动轴承一旦发生故障,不仅会影响电机本身的运行,还会引起连锁反应,造成严重安全事故。为了保证电机的安全运行,防止生产事故的发生,有必要对在线式滚动轴承故障诊断系统进行研究。本文首先对滚动轴承的典型结构、故障表现形式以及故障机理进行了研究,并介绍了轴承故障诊断的常用方法,通过对比它们的优缺点,最终选择了振动信号分析法作为轴承故障诊断方法,它能够迅速、全面地提取轴承的故障特征信息,从而为轴承故障诊断系统的开发提供了理论基础。其次,对基于振动信号的故障诊断方法做了详细的介绍,包括时域分析法、频域分析法、希尔伯特解调法、小波分析以及经验模态分解法。本文针对传统的经验模态分解法存在的模态混叠、包含虚假分量等问题,提出了一种改进的经验模态分解法,并将传统的故障诊断方法与改进经验模态分解相结合,提出了轴承故障综合诊断方法,该方法可以有效地提高故障诊断的效率和准确性。本文利用LabVIEW软件开发平台对滚动轴承故障诊断系统进行了总体设计。硬件方面主要包括传感器的选型、信号调理电路与数据采集装置的设计。软件方面主要实现了基于LabVIEW与MATLAB混合编程的故障诊断系统各功能模块。最后,通过搭建的实验平台对滚动轴承故障诊断系统的实用性进行了验证。实验结果与预期一致,表明本文设计的轴承故障诊断系统能够有效诊断出轴承故障,具有一定的实用价值。
[Abstract]:Motor is a very important rotating machine. Rolling bearing is one of the most commonly used parts and components in motor equipment. Once the rolling bearing breaks down, it will not only affect the operation of the motor itself, but also cause chain reaction and cause serious safety accident. In order to ensure the safe operation of the motor and prevent the production accident, it is necessary to study the on-line rolling bearing fault diagnosis system. In this paper, the typical structure, fault representation and fault mechanism of rolling bearing are studied, and the common methods of bearing fault diagnosis are introduced, and their advantages and disadvantages are compared. Finally, the vibration signal analysis method is chosen as the bearing fault diagnosis method, which can extract the bearing fault characteristic information quickly and comprehensively, thus providing the theoretical basis for the development of the bearing fault diagnosis system. Secondly, the fault diagnosis method based on vibration signal is introduced in detail, including time domain analysis, frequency domain analysis, Hilbert demodulation, wavelet analysis and empirical mode decomposition. In this paper, an improved empirical mode decomposition method is proposed to solve the problems of modal aliasing and false component in the traditional empirical mode decomposition method, which combines the traditional fault diagnosis method with the improved empirical mode decomposition method. A comprehensive diagnosis method for bearing faults is proposed, which can effectively improve the efficiency and accuracy of fault diagnosis. In this paper, the overall design of rolling bearing fault diagnosis system is carried out by using LabVIEW software development platform. Hardware mainly includes sensor selection, signal conditioning circuit and data acquisition device design. In the aspect of software, the function modules of fault diagnosis system based on LabVIEW and MATLAB are realized. Finally, the practicability of the rolling bearing fault diagnosis system is verified by the experimental platform. The experimental results are in agreement with the expectation, which indicates that the bearing fault diagnosis system designed in this paper can diagnose bearing fault effectively and has certain practical value.
【学位授予单位】：安徽工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM307

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