基于小波分析的风电机组故障信息提取

Fault Information Extraction of Wind Turbines Based on Wavelet Analysis

针对风力发电机组在运行工况下故障预诊断难以实现的问题,提出了基于小波分析的故障信息提取方法。机组故障运行时其声音品质特性将发生变化,由此对风电机组进行声发射实验,对噪音信号进行测量,利用小波分析法从中提取故障信息,对机组实施故障预处理和保护措施。经过对现场信号的测量、分析与仿真实验,表明该方法较简单易行,可有效提取故障信息,对工程实践有应用价值。

In view of the difficult problem of diagnosing fault in the running wind power generation system,a fault information extraction method based on wavelet analysis is put forward.When wind turbines are running with fault,their voice quality characteristics will change.It will make the acoustic emission experiment.So we present to analyze measured noise signal by wavelet analysis method,extract the fault information.Further,fault pretreatment and protection measures can be made.Though measured signal on wind farm,analyzing and simulating results show that the method is simple and effectively to extract the fault information.It has a great application value for the engineering practice.