Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis
Department of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro 1 gil, Jung-gu, Seoul 04620, Korea
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Sensors 2018, 18(4), 1278; https://doi.org/10.3390/s18041278
Received: 8 March 2018
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Revised: 19 April 2018
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Accepted: 19 April 2018
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Published: 21 April 2018
(This article belongs to the Special Issue Sensors for Fault Detection)
This paper presents the local mean decomposition (LMD) integrated with multi-scale permutation entropy (MPE), also known as LMD-MPE, to investigate the rolling element bearing (REB) fault diagnosis from measured vibration signals. First, the LMD decomposed the vibration data or acceleration measurement into separate product functions that are composed of both amplitude and frequency modulation. MPE then calculated the statistical permutation entropy from the product functions to extract the nonlinear features to assess and classify the condition of the healthy and damaged REB system. The comparative experimental results of the conventional LMD-based multi-scale entropy and MPE were presented to verify the authenticity of the proposed technique. The study found that LMD-MPE’s integrated approach provides reliable, damage-sensitive features when analyzing the bearing condition. The results of REB experimental datasets show that the proposed approach yields more vigorous outcomes than existing methods.
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Keywords:
rolling element bearing (REB); fault detection and diagnosis (FDD); local mean decomposition (LMD); multi-scale entropy (MSE); sample entropy; permutation entropy (PE); multi-scale permutation entropy (MPE)
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MDPI and ACS Style
Yasir, M.N.; Koh, B.-H. Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis. Sensors 2018, 18, 1278. https://doi.org/10.3390/s18041278
AMA Style
Yasir MN, Koh B-H. Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis. Sensors. 2018; 18(4):1278. https://doi.org/10.3390/s18041278
Chicago/Turabian StyleYasir, Muhammad N., and Bong-Hwan Koh. 2018. "Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis" Sensors 18, no. 4: 1278. https://doi.org/10.3390/s18041278
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