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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Main Authors: He Wang, Hua Song
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Symmetry
Subjects:
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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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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