An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis

Currently, study on the relevant methods of variational mode decomposition (VMD) is mainly focused on the selection of the number of decomposed modes and the bandwidth parameter using various optimization algorithms. Most of these methods utilize the genetic-like algorithms to quantitatively analyze...

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Main Authors: Haien Wang, Xingxing Jiang, Wenjun Guo, Juanjuan Shi, Zhongkui Zhu
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/5162916
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author Haien Wang
Xingxing Jiang
Wenjun Guo
Juanjuan Shi
Zhongkui Zhu
author_facet Haien Wang
Xingxing Jiang
Wenjun Guo
Juanjuan Shi
Zhongkui Zhu
author_sort Haien Wang
collection DOAJ
description Currently, study on the relevant methods of variational mode decomposition (VMD) is mainly focused on the selection of the number of decomposed modes and the bandwidth parameter using various optimization algorithms. Most of these methods utilize the genetic-like algorithms to quantitatively analyze these parameters, which increase the additional initial parameters and inevitably the computational burden due to ignoring the inherent characteristics of the VMD. From the perspective to locate the initial center frequency (ICF) during the VMD decomposition process, we propose an enhanced VMD with the guidance of envelope negentropy spectrum for bearing fault diagnosis, thus effectively avoiding the drawbacks of the current VMD-based algorithms. First, the ICF is coarsely located by envelope negentropy spectrum (ENS) and the fault-related modes are fast extracted by incorporating the ICF into the VMD. Then, the fault-related modes are adaptively optimized by adjusting the bandwidth parameters. Lastly, in order to identify fault-related features, the Hilbert envelope demodulation technique is used to analyze the optimal mode obtained by the proposed method. Analysis results of simulated and experimental data indicate that the proposed method is effective to extract the weak faulty characteristics of bearings and has advantage over some advanced methods. Moreover, a discussion on the extension of the proposed method is put forward to identify multicomponents for broadening its applied scope.
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spelling doaj-art-25b20136ee5f411da3df1c5b98b6c6b82025-08-20T02:04:27ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/51629165162916An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault DiagnosisHaien Wang0Xingxing Jiang1Wenjun Guo2Juanjuan Shi3Zhongkui Zhu4School of Rail Transportation, Soochow University, Suzhou 215131, ChinaSchool of Rail Transportation, Soochow University, Suzhou 215131, ChinaSchool of Rail Transportation, Soochow University, Suzhou 215131, ChinaSchool of Rail Transportation, Soochow University, Suzhou 215131, ChinaSchool of Rail Transportation, Soochow University, Suzhou 215131, ChinaCurrently, study on the relevant methods of variational mode decomposition (VMD) is mainly focused on the selection of the number of decomposed modes and the bandwidth parameter using various optimization algorithms. Most of these methods utilize the genetic-like algorithms to quantitatively analyze these parameters, which increase the additional initial parameters and inevitably the computational burden due to ignoring the inherent characteristics of the VMD. From the perspective to locate the initial center frequency (ICF) during the VMD decomposition process, we propose an enhanced VMD with the guidance of envelope negentropy spectrum for bearing fault diagnosis, thus effectively avoiding the drawbacks of the current VMD-based algorithms. First, the ICF is coarsely located by envelope negentropy spectrum (ENS) and the fault-related modes are fast extracted by incorporating the ICF into the VMD. Then, the fault-related modes are adaptively optimized by adjusting the bandwidth parameters. Lastly, in order to identify fault-related features, the Hilbert envelope demodulation technique is used to analyze the optimal mode obtained by the proposed method. Analysis results of simulated and experimental data indicate that the proposed method is effective to extract the weak faulty characteristics of bearings and has advantage over some advanced methods. Moreover, a discussion on the extension of the proposed method is put forward to identify multicomponents for broadening its applied scope.http://dx.doi.org/10.1155/2020/5162916
spellingShingle Haien Wang
Xingxing Jiang
Wenjun Guo
Juanjuan Shi
Zhongkui Zhu
An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis
Complexity
title An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis
title_full An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis
title_fullStr An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis
title_full_unstemmed An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis
title_short An Enhanced VMD with the Guidance of Envelope Negentropy Spectrum for Bearing Fault Diagnosis
title_sort enhanced vmd with the guidance of envelope negentropy spectrum for bearing fault diagnosis
url http://dx.doi.org/10.1155/2020/5162916
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