The Huang Hilbert Transform for evaluating the instantaneous frequency evolution of transient signals in non-linear systems

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• 作者：Aldo Baccigalupi ^{aldo.baccigalupi@unina.it" class="auth_mail" title="E-mail the corresponding author} ; Annalisa Liccardo ; ^{annalisa.liccardo@unina.it" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Instantaneous frequency ; Transient analysis ; Non-linear systems ; Huang Hilbert Transform ; Empirical mode decomposition ; Intrinsic mode functions
• 刊名：Measurement
• 出版年：2016
• 出版时间：May 2016
• 年：2016
• 卷：86
• 期：Complete
• 页码：1-13
• 全文大小：2658 K

文摘

Traditional approaches for the analysis of transient signals are generally based on the apriori knowledge of the system under test for choosing a preliminary set of waveforms; consequently, they use a mathematical algorithm to decompose the signal itself into a suitable combination of the chosen waveforms. Conversely, this work is aimed to investigate the possibility of extracting the features of transient signals through the evaluation of their instantaneous frequency evolution. For this aim, the Huang Hilbert Transform (HHT) has been exploited (i) to decompose the input signal into a set of Intrinsic Mode Functions (IMFs), (ii) to extract the IMFs analytical signals, (iii) to evaluate their amplitude and phase evolutions, (iv) to compute the instantaneous frequency of the input signal and (v) to extract the signal information searched for. In order to evaluate its performance, the proposed approach has been firstly applied to a synthesized signal with known instantaneous amplitude and frequency evolution. Successively, in order to assess the reliability of HHT results with signals acquired on experimental circuits, the current flowing in an actual RLC circuit during its free natural oscillation has been analyzed. With the aim of analyzing the performance gained also in the presence of evident non-linearities, a saturable inductor has been introduced in the test circuit. Also in this case, by comparing the achieved results with those shown by different traditional approaches, great advantages have been experienced in terms of accuracy. Furthermore, beyond the accurate frequency representation, the experimental results evidenced the intrinsic ability of the proposed approach to extract meaningful information related to the knowledge of the underlying process. Finally, it is worth noting that the results reported in this paper requested no apriori knowledge about the signal/process under test.