基于小波多分辨率分析的风力发电机的故障特征提取与识别

利用小波多分辨率分析的方法对风力发电机振动信号进行分析,并运用小波变换对测得的信号进行处理,达到对风力发电机组故障的诊断识别。将提取的振动信号映射到小波基函数上,经平移和伸缩具有正交性的小波函数,然后再经小波变换归一化得到小波分解序列的幅值,以此作为诊断识别的特征值,实现了在多尺度下特征信息的提取与故障识别,说明该方法行之有效。

Extraction and Recognition of Wind Turbines Based on Wavelet Analysis

The signal of the vibration on wind turbine can be preprocessed with the wavelet multi-resolution analysis, and the signal is processed by wavelet transform, the fault of the wind turbine diagnosis can be identified. The extraction of the vibra-tion signal is cast upon a set of basic orthogonal functions from a wavelet by extending, and then a set of wavelet decomposition sequences amplitude is got by the translation and scale, and it is used as characteristic parameter for diagnosis and fauh recog-nition, and it shows the multi-scale characteristic information for extraction and recognition of fault information. It is found that this method is effective.