Extraction of Sound Signals from Power Cable Impulse Discharge

JIAN-WEI MI, KUN WANG, QIAN LIU, MING-XING ZHANG

Abstract


In the fault detection of buried power cables, random noise in the shock discharge sound signal is difficult to remove by existing filtering methods. A fifth-order convergent independent component analysis (ICA) method based on empirical mode decomposition (EMD) is proposed to extract the impact discharge sound signal. The fifth-order convergence ICA is adopted, so that the eigenmode components decomposed by the EMD and the remaining signals are independent of each other. Using the strong correlation between the frequency spectrum of the discharge sound signal, the eigenmode component with the largest correlation between the frequency spectrum and the high signal-to-noise ratio shock discharge sound signal spectrum is automatically extracted. Finally, the shock discharge sound signal of unknown failure point is obtained. This method has the advantages of less constraints, small dependencies, and fast convergence. The simulation and experimental results further show that the discharge sound signal in the mixed signal can be effectively extracted.

Keywords


Independent component analysis, Empirical mode decomposition, Correlation, Signal extraction, Fault location.Text


DOI
10.12783/dteees/peems2019/33997

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