Abstract

Based on Empirical Mode Decomposition (EMD) and feature energy entropy, a method for the fault severity recognition of piston pumps is proposed in this paper. The discharge pressure signals of piston pumps are decomposed into a series of Intrinsic Mode Function (IMF) components by using EMD. Then, some useful IMF components are selected by calculating correlation coefficient between the signal reconstructed by the selected IMFs and the original signal. The characteristic vector is constructed by computing the normalized energy of every selected IMF, and the feature energy entropy can be obtained. The experimental results indicate that the proposed method can recognize the fault severity of pumps effectively.

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