基于双谱分析的大型汽轮机振动故障特性提取

汽轮机轴系振动通常以与转速同步的频率(基频)及其谐波成分为主,具有典型的亚高斯信号特征,多数轴系故障均表现为某些谐波成分的变化,并且谐波间存在一定程度的非线性耦合作用,使得基于二阶统计量的功率谱分析技术在故障原因分析和特征提取方面受到限制。该文针对大型汽轮机组在实际运行中出现的某种具有半频特征的不稳定振动现象,将高阶谱应用于实测轴系振动信号分析,通过对比分析稳定状态和不稳定状态下振动信号的双谱和1(1/2)分数维谱,确定引起不稳定振动的半频成分的非线性谐波耦合特性。在此基础上,提出采用双谱的边际谱以及1(1/2)分数维谱中对应成分作为特征值,对不稳定振动现象的变化趋势进行监测。分析结果表明,这种特征提取方法可以更加明显地表现异常振动的变化,具有故障反映灵敏度高的特点,并可以有效抑制测量振动信号中的高斯噪声,可以为自动故障诊断提供更有效的特征参数。

Fault Feature Extraction of Large Steam Turbine Based on Bispectra Analysis of Vibration Signal

Shaft vibration of large steam turbine has a characteristic of sub-Gausian signal with predominant component of rotating speed and its harmonics. Most of faults occurred on shaft indicate the change of harmonics with nonlinear coupling reciprocity from each other, that makes it difficulty to identify the fault source and extract the fault feature from vibration signals by means of power spectra analysis based on second-order statistical analysis. This paper took a non-stable vibration phenomenon of a large ...