Composite Multivariate Multi-Scale Permutation Entropy and Laplacian Score Based Fault Diagnosis of Rolling Bearing [PDF]
Entropy, 2022 As a powerful tool for measuring complexity and randomness, multivariate multi-scale permutation entropy (MMPE) has been widely applied to the feature representation and extraction of multi-channel signals.
Wanming Ying +5 more
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Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis [PDF]
Sensors, 2018 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.
Muhammad Naveed Yasir, Bong-Hwan Koh
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The Optimized Multi-Scale Permutation Entropy and Its Application in Compound Fault Diagnosis of Rotating Machinery [PDF]
Entropy, 2019 Multi-scale permutation entropy (MPE) is a statistic indicator to detect nonlinear dynamic changes in time series, which has merits of high calculation efficiency, good robust ability, and independence from prior knowledge, etc.
Xianzhi Wang +3 more
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Graph Multi-Scale Permutation Entropy for Bearing Fault Diagnosis [PDF]
Sensors, 2023 Bearing faults are one kind of primary failure in rotatory machines. To avoid economic loss and casualties, it is important to diagnose bearing faults accurately. Vibration-based monitoring technology is widely used to detect bearing faults. Graph signal
Qingwen Fan +3 more
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Research on a Fault Diagnosis Method for Crankshafts Based on Improved Multi-Scale Permutation Entropy [PDF]
SensorsAs the crucial part of a transmission assembly, the monitoring of the status of the crankshaft is essential for the normal working of a reciprocating machinery system.
Fengfeng Bie +7 more
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Multivariate Multi-Scale Permutation Entropy for Complexity Analysis of Alzheimer’s Disease EEG [PDF]
Entropy, 2012 An original multivariate multi-scale methodology for assessing the complexity of physiological signals is proposed. The technique is able to incorporate the simultaneous analysis of multi-channel data as a unique block within a multi-scale framework. The
Isabella Palamara +5 more
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Coal and Rock Hardness Identification Based on EEMD and Multi-Scale Permutation Entropy [PDF]
Entropy, 2021 This study offers an efficient hardness identification approach to address the problem of poor real-time performance and accuracy in coal and rock hardness detection.
Tao Liu, Chao Lu, Qingyun Liu, Yiwen Zha
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Time-Shift Multi-scale Weighted Permutation Entropy and GWO-SVM Based Fault Diagnosis Approach for Rolling Bearing [PDF]
Entropy, 2019 Multi-scale permutation entropy (MPE) is an effective nonlinear dynamic approach for complexity measurement of time series and it has been widely applied to fault feature representation of rolling bearing.
Zhilin Dong +4 more
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Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise [PDF]
Entropy, 2021 Ship-radiated noise is one of the important signal types under the complex ocean background, which can well reflect physical properties of ships. As one of the valid measures to characterize the complexity of ship-radiated noise, permutation entropy (PE)
Yuxing Li, Bo Geng, Shangbin Jiao
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Fault Recognition of Rolling Bearings Based on Parameter Optimized Multi-Scale Permutation Entropy and Gath-Geva [PDF]
Entropy, 2021 To extract fault features of rolling bearing vibration signals precisely, a fault diagnosis method based on parameter optimized multi-scale permutation entropy (MPE) and Gath-Geva (GG) clustering is proposed.
Haiming Wang +3 more
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