基于小波包域双谱的风力机振动信号监测方法研究

文章主要基于小波域双谱的方法对风力机振动信号监测技术进行研究,以风电场多台1.5兆瓦直驱机型的大量轴承振动信号为基础,运用了一种小波包域双谱的方法对振动信号分析,并与传统双谱进行对比,实验结果表明:小波包域双谱优于双谱分析,能够准确的判断轴承正常和故障运行情况,该方法不但有效抑制噪声和其他高频成分的干扰,而且具有双重消噪的效果,有效地避免了小波分析和传统双谱分析的缺点,为在线监测异常状况预警提供了很好的依据。

Based on wavelet packet domain bispectrum of wind turbine research of on-line monitoring method

In recent years, the wind power has developed rapidly, but the proportion of wind turbine operation and maintenance costs large, so the wind turbine installation and application-line monitoring system is essential. This paper mainly studies the wind turbine on-line monitoring methods, a large number of bearing vibration signal from 1.5 MW direct-drive models in wind farms were extracted. Select a group normal and fault data, use wavelet packet domain bispectrum analysis, and compared with the traditional bispectrum method. Experimental results show that wavelet packet domain bispectrum was significantly better than the traditional bispectrum, and it can well suppress non-Gaussian noise, and can effectively avoid the disadvantages of the wavelet analysis. It provides a good basis for the online monitoring reflection of further information and early warning of abnormal conditions.