A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge

Rui Tang

doi:doi:10.11648/j.aas.20210604.15

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A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge

Rui Tang

Published in Advances in Applied Sciences (Volume 6, Issue 4)

Received: 11 October 2021 Accepted: 2 November 2021 Published: 10 November 2021

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Abstract

Multi-component signal decomposition method with noise has become a research hotspot of equipment condition monitoring. Aiming at the iterative divergence problem of traditional wavelet ridge extraction algorithm for multi-component harmonic signals widely existing in mechanical and electrical systems, in order to achieve the goal of high decomposition accuracy and anti-noise performance of multi-component signals, the relationship between the initial scale and the extracted components is analyzed. Compared with the time domain of noisy harmonic signals, an improved wavelet ridge extraction algorithm is proposed （WRSD） After the instantaneous frequency of a component is obtained by this extraction algorithm, the component can be separated from the original signal and its instantaneous amplitude can be obtained by using the synchronous demodulation method. This method has high accuracy and certain anti-noise performance for instantaneous frequency estimation. Through simulation analysis and engineering application, the key zero point in intelligent manufacturing equipment of high-performance composite parts can be realized Fault detection of components.

Published in	Advances in Applied Sciences (Volume 6, Issue 4)
DOI	10.11648/j.aas.20210604.15
Page(s)	106-109
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Wavelet Ridge Extraction Algorithm, Neural Network, Signal Denoising, Fault Diagnosis, Measurement and Control System

References

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[4]	S. Mallat. A wavelet tour on signal processing [M]. New York, Academic Press, 1998.
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[6]	Y. Qin, B. P. Tang, J. X. Wang. Higher-density dyadic wavelet transform and its application [J]. Mech. Syst. Signal Process. 2010, 24 (3): 823-834.
[7]	N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, N. C. Yen, C. C. Tung, H. H. Liu. The empirical mode decomposition and Hilbert spectrum for nonlinear andnonstationary time series analysis [J]. Proc. Royal Soc. London-Ser. A, 1998, 454: 903–995.
[8]	Y. Qin, J. X. Wang, Y. F. Mao. Dense framelets with two generators and their application inmechanical fault diagnosis [J]. Mech. Syst. Signal Process. 2013, 40 (2): 483-498.
[9]	R. T. Rato, M. D. Ortigueira, A. G. Batista. On the HHT, its problems, and some solutions [J]. Mech. Syst. Signal Process. 2008, 22 (6): 1374-1394.
[10]	M. Feldman. Time-varying vibration decomposition and analysis based on the Hilberttransform [J]. J. Sound Vib., 2006, 295 (3-5): 518-530.
[11]	N. P. Delprat, B. Escudie, P. Guillemain, et al. Asymptotic wavelet and Gabor analysis: extraction of instantaneous frequencies [J]. IEEE Transactions on Information Theory, 1992, 38 (2): 644-664.
[12]	M. Feldman. Hilbert transform applications in mechanical vibration [M]. New York, John Wiley & Sons, 2011.
[13]	Dada Saheb Ramteke; Ram Bilas Pachori; Anand Parey, Automated Gearbox Fault Diagnosis Using Entropy-Based Features in Flexible Analytic Wavelet Transform (FAWT) Domain [J] Journal of Vibration Engineering & Technologies 2021, 05 (27): 1-11.
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Rui Tang. (2021). A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge. Advances in Applied Sciences, 6(4), 106-109. https://doi.org/10.11648/j.aas.20210604.15

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ACS Style

Rui Tang. A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge. Adv. Appl. Sci. 2021, 6(4), 106-109. doi: 10.11648/j.aas.20210604.15

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AMA Style

Rui Tang. A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge. Adv Appl Sci. 2021;6(4):106-109. doi: 10.11648/j.aas.20210604.15

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@article{10.11648/j.aas.20210604.15,
  author = {Rui Tang},
  title = {A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge},
  journal = {Advances in Applied Sciences},
  volume = {6},
  number = {4},
  pages = {106-109},
  doi = {10.11648/j.aas.20210604.15},
  url = {https://doi.org/10.11648/j.aas.20210604.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20210604.15},
  abstract = {Multi-component signal decomposition method with noise has become a research hotspot of equipment condition monitoring. Aiming at the iterative divergence problem of traditional wavelet ridge extraction algorithm for multi-component harmonic signals widely existing in mechanical and electrical systems, in order to achieve the goal of high decomposition accuracy and anti-noise performance of multi-component signals, the relationship between the initial scale and the extracted components is analyzed. Compared with the time domain of noisy harmonic signals, an improved wavelet ridge extraction algorithm is proposed （WRSD） After the instantaneous frequency of a component is obtained by this extraction algorithm, the component can be separated from the original signal and its instantaneous amplitude can be obtained by using the synchronous demodulation method. This method has high accuracy and certain anti-noise performance for instantaneous frequency estimation. Through simulation analysis and engineering application, the key zero point in intelligent manufacturing equipment of high-performance composite parts can be realized Fault detection of components.},
 year = {2021}
}

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TY  - JOUR
T1  - A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge
AU  - Rui Tang
Y1  - 2021/11/10
PY  - 2021
N1  - https://doi.org/10.11648/j.aas.20210604.15
DO  - 10.11648/j.aas.20210604.15
T2  - Advances in Applied Sciences
JF  - Advances in Applied Sciences
JO  - Advances in Applied Sciences
SP  - 106
EP  - 109
PB  - Science Publishing Group
SN  - 2575-1514
UR  - https://doi.org/10.11648/j.aas.20210604.15
AB  - Multi-component signal decomposition method with noise has become a research hotspot of equipment condition monitoring. Aiming at the iterative divergence problem of traditional wavelet ridge extraction algorithm for multi-component harmonic signals widely existing in mechanical and electrical systems, in order to achieve the goal of high decomposition accuracy and anti-noise performance of multi-component signals, the relationship between the initial scale and the extracted components is analyzed. Compared with the time domain of noisy harmonic signals, an improved wavelet ridge extraction algorithm is proposed （WRSD） After the instantaneous frequency of a component is obtained by this extraction algorithm, the component can be separated from the original signal and its instantaneous amplitude can be obtained by using the synchronous demodulation method. This method has high accuracy and certain anti-noise performance for instantaneous frequency estimation. Through simulation analysis and engineering application, the key zero point in intelligent manufacturing equipment of high-performance composite parts can be realized Fault detection of components.
VL  - 6
IS  - 4
ER  -

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Author Information

Rui Tang

Aviation Engineering Institute, Civil Aviation Flight University of China, Guanghan, China

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APA Style

Rui Tang. (2021). A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge. Advances in Applied Sciences, 6(4), 106-109. https://doi.org/10.11648/j.aas.20210604.15

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ACS Style

Rui Tang. A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge. Adv. Appl. Sci. 2021, 6(4), 106-109. doi: 10.11648/j.aas.20210604.15

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AMA Style

Rui Tang. A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge. Adv Appl Sci. 2021;6(4):106-109. doi: 10.11648/j.aas.20210604.15

Copy | Download

@article{10.11648/j.aas.20210604.15,
  author = {Rui Tang},
  title = {A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge},
  journal = {Advances in Applied Sciences},
  volume = {6},
  number = {4},
  pages = {106-109},
  doi = {10.11648/j.aas.20210604.15},
  url = {https://doi.org/10.11648/j.aas.20210604.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aas.20210604.15},
  abstract = {Multi-component signal decomposition method with noise has become a research hotspot of equipment condition monitoring. Aiming at the iterative divergence problem of traditional wavelet ridge extraction algorithm for multi-component harmonic signals widely existing in mechanical and electrical systems, in order to achieve the goal of high decomposition accuracy and anti-noise performance of multi-component signals, the relationship between the initial scale and the extracted components is analyzed. Compared with the time domain of noisy harmonic signals, an improved wavelet ridge extraction algorithm is proposed （WRSD） After the instantaneous frequency of a component is obtained by this extraction algorithm, the component can be separated from the original signal and its instantaneous amplitude can be obtained by using the synchronous demodulation method. This method has high accuracy and certain anti-noise performance for instantaneous frequency estimation. Through simulation analysis and engineering application, the key zero point in intelligent manufacturing equipment of high-performance composite parts can be realized Fault detection of components.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - A Multi-component Signal Decomposition Application Research on Improved Algorithm Based on Improved Wavelet Ridge
AU  - Rui Tang
Y1  - 2021/11/10
PY  - 2021
N1  - https://doi.org/10.11648/j.aas.20210604.15
DO  - 10.11648/j.aas.20210604.15
T2  - Advances in Applied Sciences
JF  - Advances in Applied Sciences
JO  - Advances in Applied Sciences
SP  - 106
EP  - 109
PB  - Science Publishing Group
SN  - 2575-1514
UR  - https://doi.org/10.11648/j.aas.20210604.15
AB  - Multi-component signal decomposition method with noise has become a research hotspot of equipment condition monitoring. Aiming at the iterative divergence problem of traditional wavelet ridge extraction algorithm for multi-component harmonic signals widely existing in mechanical and electrical systems, in order to achieve the goal of high decomposition accuracy and anti-noise performance of multi-component signals, the relationship between the initial scale and the extracted components is analyzed. Compared with the time domain of noisy harmonic signals, an improved wavelet ridge extraction algorithm is proposed （WRSD） After the instantaneous frequency of a component is obtained by this extraction algorithm, the component can be separated from the original signal and its instantaneous amplitude can be obtained by using the synchronous demodulation method. This method has high accuracy and certain anti-noise performance for instantaneous frequency estimation. Through simulation analysis and engineering application, the key zero point in intelligent manufacturing equipment of high-performance composite parts can be realized Fault detection of components.
VL  - 6
IS  - 4
ER  -

Copy | Download