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The Feature Recognition of Motor Noise Based on the Improved EEMD Model

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The noise generated by the machine is closely related to the running state of the machine, so the product can be effectively detected by analyzing the noise signal. The noise… Click to show full abstract

The noise generated by the machine is closely related to the running state of the machine, so the product can be effectively detected by analyzing the noise signal. The noise identification and control methods based on the EEMD model are widely used in motor noise control. However, the EEMD only considers the influence of noise amplitude on the decomposition results, and the added white noise cannot be completely neutralized. In this paper, an improved EEMD method is proposed by analyzing the influence of the maximum frequency on the decomposition results, in which the noise with different maximum frequency and amplitude is added to decompose the signal, and the decomposition effect is judged by the orthogonality coefficient of the decomposition result. Finally, the simulation signal and the measured signal are compared and analyzed, and the results show that the improved EEMD method has some advantages over the original method in suppressing mode confusion and fault diagnosis.

Keywords: improved eemd; noise; eemd model; motor noise

Journal Title: Computational Intelligence and Neuroscience
Year Published: 2022

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