Bearing Fault Diagnosis Based on Multiscale Permutation Entropy and Support Vector Machine [PDF]
Entropy, 2012 Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features.
Jian-Jiun Ding +4 more
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Composite Multiscale Transition Permutation Entropy-Based Fault Diagnosis of Bearings
Sensors, 2022 When considering the transition probability matrix of ordinal patterns, transition permutation entropy (TPE) can effectively extract fault features by quantifying the irregularity and complexity of signals.
Jing Guo +4 more
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Fault Diagnosis for Rolling Element Bearings Based on Feature Space Reconstruction and Multiscale Permutation Entropy [PDF]
Entropy, 2019 Aimed at distinguishing different fault categories of severity of rolling bearings, a novel method based on feature space reconstruction and multiscale permutation entropy is proposed in the study.
Weibo Zhang, Jianzhong Zhou
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A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring. [PDF]
PLoS ONE, 2016 OBJECTIVE:Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the ...
Cui Su +5 more
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Multiscale permutation Rényi entropy and its application for EEG signals. [PDF]
PLoS ONE, 2018 There is considerable interest in analyzing the complexity of electroencephalography (EEG) signals. However, some traditional complexity measure algorithms only quantify the complexities of signals, but cannot discriminate different signals very well. To
Yinghuang Yin, Kehui Sun, Shaobo He
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Multiscale Weighted Permutation Entropy Analysis of Schizophrenia Magnetoencephalograms [PDF]
Entropy, 2022 Schizophrenia is a neuropsychiatric disease that affects the nonlinear dynamics of brain activity. The primary objective of this study was to explore the complexity of magnetoencephalograms (MEG) in patients with schizophrenia.
Dengxuan Bai +3 more
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Entropy, 2023 The study focuses on the fault signals of rolling bearings, which are characterized by nonlinearity, periodic impact, and low signal-to-noise ratio.
Qiang Yuan +5 more
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Adaptive Multiscale Weighted Permutation Entropy for Rolling Bearing Fault Diagnosis [PDF]
IEEE Access, 2020 Fault diagnosis of rolling bearing is of great importance to ensure high reliability and safety in the industrial machinery system. Entropy measures are useful non-linear indicators for time series complexity analysis and have been widely applied in ...
Zhiqiang Huo +3 more
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Multiscale Permutation Entropy Based Rolling Bearing Fault Diagnosis [PDF]
Shock and Vibration, 2014 A new rolling bearing fault diagnosis approach based on multiscale permutation entropy (MPE), Laplacian score (LS), and support vector machines (SVMs) is proposed in this paper.
Jinde Zheng, Junsheng Cheng, Yu Yang
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Rolling Bearing Diagnosis Based on Composite Multiscale Weighted Permutation Entropy [PDF]
Entropy, 2018 In this paper, composite multiscale weighted permutation entropy (CMWPE) is proposed to evaluate the complexity of nonlinear time series, and the advantage of the CMWPE method is verified through analyzing the simulated signal. Meanwhile, considering the
Xiong Gan +3 more
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