文档介绍：学士学位论文
基于虚拟仪器滚动轴承故障分析系统开发
摘要
滚动轴承是在旋转机械中应用最广泛的部件,是机械动力传动部件,旋转机械的故障约有30%是因滚动轴承引起的。由于工作条件恶劣,长期承受载荷和传递载荷,轴承极易疲劳、裂纹、腐蚀、磨损等,导致其断裂,造成事故。这种故障信号是一种典型的宽频带脉冲调制信号, 从含有噪声的振动信号中有效地提取出冲击脉冲信号是振动轴承故障诊断的关键。通过对滚动轴承工作特性及其故障研究,分析了滚动轴承振动机理与失效形式,设计了故障模拟实验台,搭建了测量装置,运用共振解调分析与希尔伯特变换作为滚动轴承故障诊断的方法,开发了基于Labview软件的滚动轴承故障诊断系统,通过对振动信号的采集和故障频率的自动识别,实现了在线检测故障的目的。为了确保分析数据的正确性,本文当中引入了小波函数,通过对不同频段的信号进行包络谱分析,确保故障诊断的准确性。通过实验台模拟内圈故障现象以及轴承故障诊断程序的运行,故障结论是一致的,证明了该轴承故障诊断系统的准确性。
关键词: 滚动轴承;故障诊断;Labview;希尔伯特变换;共振解调
Development of fault analysis system for rolling bearing based on virtual instrument
Abstract
Rolling bearing is the most widely ponents in rotating machinery, mechanical power ponents, about 30% of rotating machinery fault is caused by rolling bearings. Because of the bad working conditions, load for a long time and load, bearing easily fatigue, crack, corrosion, wear, etc., lead to the rupture and cause an accident. The fault signal is a typical broadband pulse modulation signals, from vibration signal containing noise effectively extract the shock pulse signal is the key to the vibration of bearing fault diagnosis. Through the study of rolling bearing working characteristic and its failure, analyzes the rolling bearing vibration mechanism and failure modes, fault simulation test bench was designed and set up a measuring device, using resonance demodulation analysis and Hilbert transform as the rolling bearing fault diagnosis methods, the development of rolling bearing fault diagnosis system based on LabVIEW software, through the collection of vibration signal and fault frequency automatic identification, realized the purpose of online detection fault. In order to ensure the accuracy of the data analysis, this paper introduces the wavelet function, based on the different frequency band of signal envelope spectrum analysis, ensure the accuracy of fault diagnosis. Through simulation test bench and bearing inner ring malfunctions fault diagnosis program is running, the fault conclusion is cons