Supplementary Materials for the article: Multi-operating condition pattern recognition of centrifugal pump impeller hydraulic radial force based on multi-dimensional features and hierarchical clustering.

DOI:10.4121/12e73a6e-10bd-4e58-b24a-4c6b1912247b.v1
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DOI: 10.4121/12e73a6e-10bd-4e58-b24a-4c6b1912247b

Datacite citation style

Zhang, Hehui; Li, Kang; Liu, Ting; Liu, Yichu; Hu, Jianxin et. al. (2025): Supplementary Materials for the article: Multi-operating condition pattern recognition of centrifugal pump impeller hydraulic radial force based on multi-dimensional features and hierarchical clustering. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/12e73a6e-10bd-4e58-b24a-4c6b1912247b.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Supplementary data for the article: "Multi-operating condition pattern recognition of centrifugal pump impeller hydraulic radial force based on multi-dimensional features and hierarchical clustering". This dataset includes supplementary matlab source code. This article proposes an unsupervised learning framework through Pearson correlation analysis and the clustering hierarchical Clustering (AHC) algorithm, providing a data-driven approach for the hydraulic optimization and intelligent diagnosis of centrifugal pumps. It reveals the multi-condition classification mode of hydraulic radial force, which has engineering significance for improving equipment reliability and operational efficiency.

History

  • 2025-07-07 first online, published, posted

Publisher

4TU.ResearchData

Format

Matlab/.m

Organizations

Xiangtan University, School of Mechanical Engineering and Mechanics

DATA

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