【摘要】 将基于小波变换的隐式马尔科夫模型(HMM)方法改进并扩展至小波包域,用于去除发电机局部放电信号中的白噪声.采用实测的局部放电信号验证了方法的有效性.结果表明,对比传统的门限去噪算法,基于小波包的HMM方法有更好的去噪效果;而与基于小波变换的HMM方法相比,所建立的模型更能体现信号的特征,对于信号分析乃至进一步的模式识别有着更大的价值.更多还原

【Abstract】 Wavelet-domain hidden markov models (HMMs) have recently been introduced and applied to signal and image processing. The advantage of the method is that the HMMs measure the dependency between the wavelet coefficients and have no free parameters in denoising. A wavelet-package-based HMMs method was developed to reduce partial discharge (PD) white noise. The effectiveness of the method is demonstrated by using numerical simulations and real-world data of neutral point current of generator. Compared with Shrinkage method, the results shows that the HMMs method is better in enhancing signal-to-noise radio and reserves more PD impulses.更多还原