Research on the Fault Characteristic Extraction of Hydropower Units Based on Hilbert-Huang Transform

Abstract

In order to effectively extract nonstationary and nonlinear fault signature of hydropower units’ signals, a new method, based on Hilbert–Huang transform (HHT), is proposed. This method is used to carry out EMD (Empirical Mode Decomposition) analysis and Hilbert transform of signals firstly and then extract Hilbert spectrum to provide a basis for signal feature extraction. The vibration signal of upper brackets in hydropower units has been put forward with experimental analysis. The results suggest that the EMD can decompose vibration components in different frequency domain, which has intuitive physical meaning. Moreover, Hilbert spectrum also has a good resolution in time domain and frequency domain. Thus, HHT can be used to depict the fault signals effectively and lay the foundation of the fault pattern recognition.

Time-Frequency Characteristics of Fluctuating Pressure on the Bottom of the Stilling Basin with Step-Down Floor Based on Hilbert–Huang Transform

“…e HHT method first decomposes the signal into several intrinsic mode functions (IMFs) through empirical mode decomposition (EMD) and then performs a Hilbert transform on each IMF component to obtain the instantaneous frequency and instantaneous amplitude of each IMF, thereby constructing the output of the time-frequency energy distribution of the signal, that is, the Hilbert spectrum. e decomposition basis of the HHT method depends on the signal itself, so it has good adaptability, and because the method is decomposed with EMD, it also has the physical meaning of the EMD method and high time-frequency resolution [11]. Compared with the Fourier transform and wavelet transform, the HHT method can decompose the signal according to the inherent characteristics of the signal without artificially setting the basis function, and its high efficiency and adaptability are very suitable for processing nonlinear and nonstationary signals.…”