A Filtering Method for Grain Flow Signals Using EMD Thresholds Optimized by Artificial Bee Colony Algorithm
For the purpose of reducing noise from grain flow signal, this paper proposes a filtering method that is on the basis of empirical mode decomposition (EMD) and artificial bee colony (ABC) algorithm. At first, decomposing noise signal is performed adaptively into intrinsic mode functions (IMFs). Then...
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MDPI AG
2018-11-01
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Series: | Symmetry |
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Online Access: | https://www.mdpi.com/2073-8994/10/11/575 |
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author | He Wang Hua Song |
author_facet | He Wang Hua Song |
author_sort | He Wang |
collection | DOAJ |
description | For the purpose of reducing noise from grain flow signal, this paper proposes a filtering method that is on the basis of empirical mode decomposition (EMD) and artificial bee colony (ABC) algorithm. At first, decomposing noise signal is performed adaptively into intrinsic mode functions (IMFs). Then, ABC algorithm is utilized to determine a proper threshold shrinking IMF coefficients instead of traditional threshold function. Furthermore, a neighborhood search strategy is introduced into ABC algorithm to balance its exploration and exploitation ability. Simulation experiments are conducted on four benchmark signals, and a comparative study for the proposed method and state-of-the-art methods are carried out. The compared results demonstrate that signal to noise ratio (SNR) and root mean square error (RMSE) are obtained by the proposed method. The conduction of which is finished on actual grain flow signal that is with noise for the demonstration of the effect in actual practice. |
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institution | Directory Open Access Journal |
issn | 2073-8994 |
language | English |
last_indexed | 2024-04-13T00:41:54Z |
publishDate | 2018-11-01 |
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series | Symmetry |
spelling | doaj.art-2b73ac4b572940d4bf0fd926c60e3dd92022-12-22T03:10:07ZengMDPI AGSymmetry2073-89942018-11-01101157510.3390/sym10110575sym10110575A Filtering Method for Grain Flow Signals Using EMD Thresholds Optimized by Artificial Bee Colony AlgorithmHe Wang0Hua Song1School of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, ChinaSchool of Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, ChinaFor the purpose of reducing noise from grain flow signal, this paper proposes a filtering method that is on the basis of empirical mode decomposition (EMD) and artificial bee colony (ABC) algorithm. At first, decomposing noise signal is performed adaptively into intrinsic mode functions (IMFs). Then, ABC algorithm is utilized to determine a proper threshold shrinking IMF coefficients instead of traditional threshold function. Furthermore, a neighborhood search strategy is introduced into ABC algorithm to balance its exploration and exploitation ability. Simulation experiments are conducted on four benchmark signals, and a comparative study for the proposed method and state-of-the-art methods are carried out. The compared results demonstrate that signal to noise ratio (SNR) and root mean square error (RMSE) are obtained by the proposed method. The conduction of which is finished on actual grain flow signal that is with noise for the demonstration of the effect in actual practice.https://www.mdpi.com/2073-8994/10/11/575Grain flow signalfiltering methodempirical mode decompositionartificial bee colony algorithm |
spellingShingle | He Wang Hua Song A Filtering Method for Grain Flow Signals Using EMD Thresholds Optimized by Artificial Bee Colony Algorithm Symmetry Grain flow signal filtering method empirical mode decomposition artificial bee colony algorithm |
title | A Filtering Method for Grain Flow Signals Using EMD Thresholds Optimized by Artificial Bee Colony Algorithm |
title_full | A Filtering Method for Grain Flow Signals Using EMD Thresholds Optimized by Artificial Bee Colony Algorithm |
title_fullStr | A Filtering Method for Grain Flow Signals Using EMD Thresholds Optimized by Artificial Bee Colony Algorithm |
title_full_unstemmed | A Filtering Method for Grain Flow Signals Using EMD Thresholds Optimized by Artificial Bee Colony Algorithm |
title_short | A Filtering Method for Grain Flow Signals Using EMD Thresholds Optimized by Artificial Bee Colony Algorithm |
title_sort | filtering method for grain flow signals using emd thresholds optimized by artificial bee colony algorithm |
topic | Grain flow signal filtering method empirical mode decomposition artificial bee colony algorithm |
url | https://www.mdpi.com/2073-8994/10/11/575 |
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