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

• Published in: Physics of fluids (1994) Vol. 37; no. 1
• Main Authors: Fang, Lide, Wang, Zhongliang, Sun, Yiqian, Zhu, Zeyu, Sun, Jianzhang, Wang, Mi
• Format: Journal Article
• Language: English
• Published: Melville American Institute of Physics 01.01.2025
• Subjects: Algorithms; Decomposition; Flowmeters; Fluid flow; Noise reduction; Optimization; Signal processing; Signal to noise ratio
• ISSN: 1070-6631; 1089-7666
• DOI: 10.1063/5.0252648

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.