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Mechanical Vibration Signal Denoising Using Quantum-Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model
Joint Authors
Xu, Aidong
Huang, Wenqi
Li, Peng
Chen, Huajun
Meng, Jiaxiao
Guo, Xiaobin
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-27
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Aiming at improving noise reduction effect for mechanical vibration signal, a Gaussian mixture model (SGMM) and a quantum-inspired standard deviation (QSD) are proposed and applied to the denoising method using the thresholding function in wavelet domain.
Firstly, the SGMM is presented and utilized as a local distribution to approximate the wavelet coefficients distribution in each subband.
Then, within Bayesian framework, the maximum a posteriori (MAP) estimator is employed to derive a thresholding function with conventional standard deviation (CSD) which is calculated by the expectation-maximization (EM) algorithm.
However, the CSD has a disadvantage of ignoring the interscale dependency between wavelet coefficients.
Considering this limit for the CSD, the quantum theory is adopted to analyze the interscale dependency between coefficients in adjacent subbands, and the QSD for noise-free wavelet coefficients is presented based on quantum mechanics.
Next, the QSD is constituted for the CSD in the thresholding function to shrink noisy coefficients.
Finally, an application in the mechanical vibration signal processing is used to illustrate the denoising technique.
The experimental study shows the SGMM can model the distribution of wavelet coefficients accurately and QSD can depict interscale dependency of wavelet coefficients of true signal quite successfully.
Therefore, the denoising method utilizing the SGMM and QSD performs better than others.
American Psychological Association (APA)
Xu, Aidong& Huang, Wenqi& Li, Peng& Chen, Huajun& Meng, Jiaxiao& Guo, Xiaobin. 2018. Mechanical Vibration Signal Denoising Using Quantum-Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model. Shock and Vibration،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1215306
Modern Language Association (MLA)
Xu, Aidong…[et al.]. Mechanical Vibration Signal Denoising Using Quantum-Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model. Shock and Vibration No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1215306
American Medical Association (AMA)
Xu, Aidong& Huang, Wenqi& Li, Peng& Chen, Huajun& Meng, Jiaxiao& Guo, Xiaobin. Mechanical Vibration Signal Denoising Using Quantum-Inspired Standard Deviation Based on Subband Based Gaussian Mixture Model. Shock and Vibration. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1215306
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1215306