相关技术在滚动轴承故障诊断中的应用

众所周知自相关技术能够有效地从随机嘈声中提取周期性信号.在滚动轴承元件的故障诊断中,由于信号图象不同,我们无法从原信号直接得到故障的情况,这种信号的显示就像宽频带随机嘈声在自相关函数的显示一样.本文中,信号经过了预处理,其结果证明是行之有效的.应用自相关技术我们还可以得到已测定的可比采样,这对于建立轴承运行条件的数据基础和进行故障诊断是十分重要的.     

Rolling bearing fault detection using correlation technique

It's known that auto-correlation technique is effective in extracting periodical signals from random noises. In the case of fault monitoring of rolling element bearing, we can't acquire the.fault information directly from the original signal because of the difference of signal phases. And the signal is shown as the wide band random signal in auto-correlation function. In this paper, the signal is pre-processed and the results are proved effctive. Moreow, by taking the auto-correlation fumction we can obtain the determined and comparable samples. This is very important for establishing the data base of running condition and for detecting the faults.     

The application of pattern recognition techniques in fault diagnosis of machinery equipment

In this paper,the characteristics of vibration signal of machinery in different runningconditions are statistically analysed,and some moments of statistical distribution of signalsare selected as the eigenvector to condense the state information.Here,we divide the statesof machinery into two:‘good’and‘aulty’,and the pattern recognition techniques are usedto classify the running conditions of machinery.At the end of this paper,the authors presentsome test data,and from the results obtained,it’s verified that the eigenvector selected isreliable and sensible to faults.And the results also show the effectiveness of classificationrule.     

旋转机械故障诊断中的哈尔谱研究

本文将哈尔变换应用于旋转机械故障诊断之中,并提出了用于诊断的“脉冲锐度”指标.基于付立叶分析的频谱分析是目前广泛采用的方法,与快速付立叶变换相比,哈尔变换具有实时性,逼近效果好,适用于对脉冲的提取等优点.而不足之处是受样本始点选取及样本长的影响大.对此,本文提出了控制各次样本的等效性的方法,改善了哈尔谱的稳定性与比较性.最后,通过对滚珠轴承故障模拟试验台进行试验得到的结果证实了哈尔谱及脉冲锐度指标对故障的敏感性.     

模式识别技术在机械设备故障诊断中的应用

本文从统计意义上分析了机械设备在不同运行状态下振动信号的特征;选择信号幅值的概率分布的前n阶矩作为特征向量来进行状态信息凝聚.在此,将设备的状态分为“完好”和“故障”两种,应用模式识别技术进行状态分类.最后通过对试验数据的分析,证实了特征参数的稳定性和对故障的敏感性.结果表明,分类判据是有效的.     

Research on Haar Spectrum in fault diagnosis of rotating machinery

In this paper,Haar Transform(HT)is used in the fault diagnosis of rotatingmachinery,and the“Impulse Sharpness”is presented as a diagnostic index.At present,Fourier Spectrumanalysis is most widely used Compared with FFT,HT is more rapid incomputation and more effective in discrete approximation.It’s very suitable for theextraction of pulses in the signal.However,HT has some shortcomings.It’s greatlyaffected by the starting point and length of the sample.Here,the authors present a methodto improve the stability and comparability of Haar Spectrum.The fault imitating test ofrolling bearing is carried out,and the results obtained have verified the sensitivity of HaarSpectrum and Impulse Index to the fault.