A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications
The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can decompose signals into several narrow-band components, which is advantageous to quantitatively evaluate signal characteristics. In this paper, we present a comparative study of four kinds of adaptive decompos...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-07-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/7/2120 |
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| author | Tao Liu Zhijun Luo Jiahong Huang Shaoze Yan |
| author_facet | Tao Liu Zhijun Luo Jiahong Huang Shaoze Yan |
| author_sort | Tao Liu |
| collection | DOAJ |
| description | The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can decompose signals into several narrow-band components, which is advantageous to quantitatively evaluate signal characteristics. In this paper, we present a comparative study of four kinds of adaptive decomposition algorithms, including some algorithms deriving from empirical mode decomposition (EMD), empirical wavelet transform (EWT), variational mode decomposition (VMD) and Vold–Kalman filter order tracking (VKF_OT). Their principles, advantages and disadvantages, and improvements and applications to signal analyses in dynamic analysis of mechanical system and machinery fault diagnosis are showed. Examples are provided to illustrate important influence performance factors and improvements of these algorithms. Finally, we summarize applicable scopes, inapplicable scopes and some further works of these methods in respect of precise filters and rough filters. It is hoped that the paper can provide a valuable reference for application and improvement of these methods in signal processing. |
| first_indexed | 2024-04-11T14:11:37Z |
| format | Article |
| id | doaj.art-af81c558e0ea44abbd3fcbf20526e90f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T14:11:37Z |
| publishDate | 2018-07-01 |
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| record_format | Article |
| series | Sensors |
| spelling | doaj.art-af81c558e0ea44abbd3fcbf20526e90f2022-12-22T04:19:41ZengMDPI AGSensors1424-82202018-07-01187212010.3390/s18072120s18072120A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their ApplicationsTao Liu0Zhijun Luo1Jiahong Huang2Shaoze Yan3State Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Tribology, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, ChinaThe adaptive decomposition algorithm is a powerful tool for signal analysis, because it can decompose signals into several narrow-band components, which is advantageous to quantitatively evaluate signal characteristics. In this paper, we present a comparative study of four kinds of adaptive decomposition algorithms, including some algorithms deriving from empirical mode decomposition (EMD), empirical wavelet transform (EWT), variational mode decomposition (VMD) and Vold–Kalman filter order tracking (VKF_OT). Their principles, advantages and disadvantages, and improvements and applications to signal analyses in dynamic analysis of mechanical system and machinery fault diagnosis are showed. Examples are provided to illustrate important influence performance factors and improvements of these algorithms. Finally, we summarize applicable scopes, inapplicable scopes and some further works of these methods in respect of precise filters and rough filters. It is hoped that the paper can provide a valuable reference for application and improvement of these methods in signal processing.http://www.mdpi.com/1424-8220/18/7/2120signal processingnon-stationary signalnarrow-band signaladaptive decomposition algorithm |
| spellingShingle | Tao Liu Zhijun Luo Jiahong Huang Shaoze Yan A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications Sensors signal processing non-stationary signal narrow-band signal adaptive decomposition algorithm |
| title | A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications |
| title_full | A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications |
| title_fullStr | A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications |
| title_full_unstemmed | A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications |
| title_short | A Comparative Study of Four Kinds of Adaptive Decomposition Algorithms and Their Applications |
| title_sort | comparative study of four kinds of adaptive decomposition algorithms and their applications |
| topic | signal processing non-stationary signal narrow-band signal adaptive decomposition algorithm |
| url | http://www.mdpi.com/1424-8220/18/7/2120 |
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