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提出了基于小波去噪、降采样和HHT变换的方法。该方法先利用小波进行信号去噪,克服噪声对EMD分解的影响。其次,为获得正确的IMF分量和Hilbert谱,采用降采样方法对信号进行重采样,继而得到适当的采样率。最后,进行EMD分解提取具有明确物理意义的水轮机振动模式分量信号,再对各分量信号进行Hilbert谱分析,从而识别信号的异常频率和发生时间。并将该方法应用于某电站1号机组振动信号分析,结果表明,基于小波预处理的水轮机振动信号Hilbert-Huang变换方法能对机组性能做出良好评价,值得推广应用。
A method based on wavelet denoising, downsampling and HHT transform is proposed. In this method, the signal is denoised by wavelet to overcome the influence of noise on EMD decomposition. Secondly, in order to obtain the correct IMF component and Hilbert spectrum, the down-sampling method is adopted to resample the signal and obtain the appropriate sampling rate. Finally, EMD is decomposed to extract the signal of vibration mode component with clear physical meaning, and Hilbert spectrum analysis of each component signal is carried out to identify the abnormal frequency and time of signal. The method is applied to the vibration signal analysis of Unit 1 in a power plant. The results show that the Hilbert-Huang transform method of turbine vibration signal based on the wavelet preprocessing can make a good evaluation of the unit performance and is worth popularizing and applying.