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.

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.

本数据集为论文《基于多维特征与层次聚类（hierarchical clustering）的离心泵叶轮液压径向力多工况模式识别》的补充数据，包含配套的Matlab源代码。该论文提出了一种融合皮尔逊相关分析（Pearson correlation analysis）与聚合层次聚类（AHC）算法的无监督学习框架（unsupervised learning framework），为离心泵的液压优化与智能诊断提供了数据驱动的研究路径。该框架揭示了液压径向力的多工况分类模式，对于提升设备可靠性与运行效率具有重要的工程应用价值。