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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40660

Title: Time Series Analysis UsingComposite Multiscale Entropy
Authors: Shuen-De Wu
Chiu-Wen Wu
Shiou-Gwo Lin
Chun-Chieh Wang
Kung-Yen Lee
Contributors: 國立臺灣海洋大學:通訊與導航工程學系
Keywords: composite multiscale entropy
fault diagnosis
multiscale entropy
Date: 2013
Issue Date: 2017-02-06T03:17:18Z
Publisher: Entropy
Abstract: Abstract: Multiscale entropy (MSE) was recently developed to evaluate the complexity of time series over different time scales. Although the MSE algorithm has been successfully applied in a number of different fields, it encounters a problem in that the statistical reliability of the sample entropy (SampEn) of a coarse-grained series is reduced as a time scale factor is increased. Therefore, in this paper, the concept of a composite multiscale entropy (CMSE) is introduced to overcome this difficulty. Simulation results on both white noise and 1/f noise show that the CMSE provides higher entropy reliablity than the MSE approach for large time scale factors. On real data analysis, both the MSE and CMSE are applied to extract features from fault bearing vibration signals. Experimental results demonstrate that the proposed CMSE-based feature extractor provides higher separability than the MSE-based feature extractor. View Full-Text
Relation: 15(3)
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40660
Appears in Collections:[通訊與導航工程學系] 期刊論文

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