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A signal denoising method based on goose optimization algorithm for optimal variational modal decomposition and improved wavelet thresholding function

delete2025-01-28
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PRE
AI
方立德 cover
方立德 (Lide Fang)
Z
Zhongliang Wang
Z
Zeyu Zhu
S
Sun, Jianzhang
王蜜 cover
王蜜 (Mi Wang) *
DOI:10.1063/5.0252648delete
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Abstract

Abstract

En 中文
Ultrasonic flowmeters are widely used in energy and control applications, providing accurate and fast measurement of fluid flow rates. This paper proposes a denoising method based on the goose optimization algorithm, a nature-inspired optimization method mimicking the foraging behavior of goose. GO optimizes the penalty factor and decomposition layer number of variational modal decomposition, resulting in the GO-VMD approach. Decomposed modal components are further denoised using an improved wavelet thresholding method. The algorithm is compared with existing methods, such as high-frequency ultrasonic signal processing, and experimental results show that it improves the signal-to-noise ratio by 8%, reduces root mean square error by 5%, retains more useful information, and achieves significant denoising results.
Keywords:
FEATURE-EXTRACTION
SAMPLE ENTROPY
APPROXIMATE
EMD

Journal

Physics of Fluids cover
Physics of Fluids
IF:
4.3
Papers:
2.9W
Citations:
8.0W

Organization

H
Hebei University
Scholars:
1.5W
Papers: 7.8K
Citations: 1.0W
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