采用集合经验模态分解方法（EEMD），对不同放电阶段的声发射信号进行分解，得到其本征模态分量，再对本征模态分量进行Hilbert变换得到声发射信号的时频谱。在此基础上，计算声发射信号的边际谱，以声发射信号的边际谱熵和重心频率作为声发射信号的特征值，最终实现对绝缘子不同放电阶段的模式识别。结合大量的绝缘子污秽放电试验，运用声发射信号的特征值进行污秽放电模式识别分析。结果表明：该新方法能有效区分污秽绝缘子污秽放电的三种不同放电阶段，为判断绝缘子的外绝缘状态及实现污闪预警提供了技术支持。
The acoustic emission signals under different discharge steps were decomposed by ensemble empirical mode decomposition (EEMD), the intrinsic mode function was obtained, and the instantaneous frequency of acoustic emission signals was gained by Hilbert transform on intrinsic mode function. On this basis, the marginal spectrum of acoustic emission signals was calculated, and the marginal spectrum entropy and gravity frequency of acoustic emission signals were used as characteristic value to realize pattern recognition of contamination discharge. Combining large number of contamination discharge experiments of insulators, the characteristic value of acoustic emission signal was used to analyze the contamination discharge pattern. The results show that the proposed method can effectively distinguish the three discharge steps in contamination discharge of insulator. This provides technical support to judge the insulation status of contamination insulators and realize flashover warning.
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