Dynamic multiscale pressure fluctuation features extraction of mixed-flow pump as turbine (PAT) and flow state recognition of the outlet passage using variational mode decomposition and refined composite variable-step multiscale multimapping dispersion entropy

Shuaihao Lei, Li Cheng, Weixing Yang, Wentao Xu, Lei Yu, Can Luo, Weixuan Jiao and Jiantao Shen

Energy, 2024, vol. 305, issue C

Abstract: The feature extraction of pressure fluctuation signal (PFS) and flow state recognition of outlet passage have crucial engineering significance to guarantee the safe and reliable operation in mixed-flow pump as turbine (PAT). To accurately extract the dynamic multiscale features of PFS, a method based on variational mode decomposition (VMD) and refined composite variable-step multiscale multimapping dispersion entropy (RCVMMDE) is proposed. By applying VMD to PFS, intrinsic mode functions (IMFs) are obtained, and the RCVMMDE values for each IMF is then calculated. Model parameters based on the RCVMMDE indicator are then established and used as feature vectors for flow state recognition. Using the PFS at the outlet passage inlet as an example, this method extracts dynamic multiscale feature information of the outlet passage, which is validated through experimental and numerical simulations. The results show that this method achieves high accuracy, providing well-defined feature vectors and effectively capturing the dynamic multiscale features of the PAT and turbine systems.

Keywords: Mixed-flow pump as turbine; Pressure fluctuation; Feature extraction; Variational mode decomposition; Refined composite variable-step multiscale multimapping dispersion entropy (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:305:y:2024:i:c:s0360544224020048

DOI: 10.1016/j.energy.2024.132230

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