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Entropy 2018, 20(5), 361; https://doi.org/10.3390/e20050361

A Hybrid De-Noising Algorithm for the Gear Transmission System Based on CEEMDAN-PE-TFPF

1
College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
2
College of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China
*
Author to whom correspondence should be addressed.
Received: 6 April 2018 / Revised: 10 May 2018 / Accepted: 10 May 2018 / Published: 11 May 2018
(This article belongs to the Section Complexity)
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Abstract

In order to remove noise and preserve the important features of a signal, a hybrid de-noising algorithm based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Permutation Entropy (PE), and Time-Frequency Peak Filtering (TFPF) is proposed. In view of the limitations of the conventional TFPF method regarding the fixed window length problem, CEEMDAN and PE are applied to compensate for this, so that the signal is balanced with respect to both noise suppression and signal fidelity. First, the Intrinsic Mode Functions (IMFs) of the original spectra are obtained using the CEEMDAN algorithm, and the PE value of each IMF is calculated to classify whether the IMF requires filtering, then, for different IMFs, we select different window lengths to filter them using TFPF; finally, the signal is reconstructed as the sum of the filtered and residual IMFs. The filtering results of a simulated and an actual gearbox vibration signal verify that the de-noising results of CEEMDAN-PE-TFPF outperforms other signal de-noising methods, and the proposed method can reveal fault characteristic information effectively. View Full-Text
Keywords: CEEMDAN; permutation entropy; TFPF; de-noising CEEMDAN; permutation entropy; TFPF; de-noising
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Bai, L.; Han, Z.; Li, Y.; Ning, S. A Hybrid De-Noising Algorithm for the Gear Transmission System Based on CEEMDAN-PE-TFPF. Entropy 2018, 20, 361.

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