Gearbox Fault Diagnosis Using Complementary Ensemble Empirical Mode Decomposition and Permutation Entropy

This paper presents an improved gearbox fault diagnosis approach by integrating complementary ensemble empirical mode decomposition (CEEMD) with permutation entropy (PE). The presented approach identifies faults appearing in a gearbox system based on PE values calculated from selected intrinsic mode...

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Main Authors: Liye Zhao, Wei Yu, Ruqiang Yan
Format: Article
Language:English
Published: Wiley 2016-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2016/3891429
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author Liye Zhao
Wei Yu
Ruqiang Yan
author_facet Liye Zhao
Wei Yu
Ruqiang Yan
author_sort Liye Zhao
collection DOAJ
description This paper presents an improved gearbox fault diagnosis approach by integrating complementary ensemble empirical mode decomposition (CEEMD) with permutation entropy (PE). The presented approach identifies faults appearing in a gearbox system based on PE values calculated from selected intrinsic mode functions (IMFs) of vibration signals decomposed by CEEMD. Specifically, CEEMD is first used to decompose vibration signals characterizing various defect severities into a series of IMFs. Then, filtered vibration signals are obtained from appropriate selection of IMFs, and correlation coefficients between the filtered signal and each IMF are used as the basis for useful IMFs selection. Subsequently, PE values of those selected IMFs are utilized as input features to a support vector machine (SVM) classifier for characterizing the defect severity of a gearbox. Case study conducted on a gearbox system indicates the effectiveness of the proposed approach for identifying the gearbox faults.
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series Shock and Vibration
spelling doaj-art-cbb7090c7ede493a8ff39bfe4d57d93e2025-08-20T03:23:37ZengWileyShock and Vibration1070-96221875-92032016-01-01201610.1155/2016/38914293891429Gearbox Fault Diagnosis Using Complementary Ensemble Empirical Mode Decomposition and Permutation EntropyLiye Zhao0Wei Yu1Ruqiang Yan2School of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaThis paper presents an improved gearbox fault diagnosis approach by integrating complementary ensemble empirical mode decomposition (CEEMD) with permutation entropy (PE). The presented approach identifies faults appearing in a gearbox system based on PE values calculated from selected intrinsic mode functions (IMFs) of vibration signals decomposed by CEEMD. Specifically, CEEMD is first used to decompose vibration signals characterizing various defect severities into a series of IMFs. Then, filtered vibration signals are obtained from appropriate selection of IMFs, and correlation coefficients between the filtered signal and each IMF are used as the basis for useful IMFs selection. Subsequently, PE values of those selected IMFs are utilized as input features to a support vector machine (SVM) classifier for characterizing the defect severity of a gearbox. Case study conducted on a gearbox system indicates the effectiveness of the proposed approach for identifying the gearbox faults.http://dx.doi.org/10.1155/2016/3891429
spellingShingle Liye Zhao
Wei Yu
Ruqiang Yan
Gearbox Fault Diagnosis Using Complementary Ensemble Empirical Mode Decomposition and Permutation Entropy
Shock and Vibration
title Gearbox Fault Diagnosis Using Complementary Ensemble Empirical Mode Decomposition and Permutation Entropy
title_full Gearbox Fault Diagnosis Using Complementary Ensemble Empirical Mode Decomposition and Permutation Entropy
title_fullStr Gearbox Fault Diagnosis Using Complementary Ensemble Empirical Mode Decomposition and Permutation Entropy
title_full_unstemmed Gearbox Fault Diagnosis Using Complementary Ensemble Empirical Mode Decomposition and Permutation Entropy
title_short Gearbox Fault Diagnosis Using Complementary Ensemble Empirical Mode Decomposition and Permutation Entropy
title_sort gearbox fault diagnosis using complementary ensemble empirical mode decomposition and permutation entropy
url http://dx.doi.org/10.1155/2016/3891429
work_keys_str_mv AT liyezhao gearboxfaultdiagnosisusingcomplementaryensembleempiricalmodedecompositionandpermutationentropy
AT weiyu gearboxfaultdiagnosisusingcomplementaryensembleempiricalmodedecompositionandpermutationentropy
AT ruqiangyan gearboxfaultdiagnosisusingcomplementaryensembleempiricalmodedecompositionandpermutationentropy