Calibration Analysis of High-G MEMS Accelerometer Sensor Based on Wavelet and Wavelet Packet Denoising

High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezor...

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Published inSensors (Basel, Switzerland) Vol. 21; no. 4; p. 1231
Main Authors Shi, Yunbo, Zhang, Juanjuan, Jiao, Jingjing, Zhao, Rui, Cao, Huiliang
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 09.02.2021
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Abstract High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.
AbstractList High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.
High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.
Author Cao, Huiliang
Jiao, Jingjing
Shi, Yunbo
Zhao, Rui
Zhang, Juanjuan
AuthorAffiliation Science and Technology on Electronic Test & Measurement Laboratory, North University of China, Taiyuan 030051, China; shiyunbo@nuc.edu.cn (Y.S.); s1906105@st.nuc.edu.cn (J.Z.); s1706152@st.nuc.edu.cn (J.J.); zhaorui@nuc.edu.cn (R.Z.)
AuthorAffiliation_xml – name: Science and Technology on Electronic Test & Measurement Laboratory, North University of China, Taiyuan 030051, China; shiyunbo@nuc.edu.cn (Y.S.); s1906105@st.nuc.edu.cn (J.Z.); s1706152@st.nuc.edu.cn (J.J.); zhaorui@nuc.edu.cn (R.Z.)
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MEMS accelerometer
wavelet packet denoising
high-G calibration
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SubjectTerms Accelerometers
Algorithms
Decomposition
high-G calibration
MEMS accelerometer
Microelectromechanical systems
Neural networks
noise reduction
Sensors
Signal to noise ratio
Time series
wavelet denoising
wavelet packet denoising
Wavelet transforms
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Title Calibration Analysis of High-G MEMS Accelerometer Sensor Based on Wavelet and Wavelet Packet Denoising
URI https://www.ncbi.nlm.nih.gov/pubmed/33572421
https://www.proquest.com/docview/2489069025
https://www.proquest.com/docview/2489262257
https://pubmed.ncbi.nlm.nih.gov/PMC7916207
https://doaj.org/article/98f9a811313d45779897152b2874f221
Volume 21
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