Page 48 - 《真空与低温》2025年第5期

第 31 卷 第 5 期 真空与低温
2025 年 9 月 Vacuum and Cryogenics 587

主 成 分 和 相 关 性 分 析 在 热 泵 系 统 运 行 数 据 挖 掘 中 的
融 合 应 用

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苗毅珂 ，胡露露 1,2* ，袁攀岗 ，王 悦 ，黄海燕 2
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（1. 江苏理工学院机械工程学院，江苏 常州 213001；
2. 浙江正理生能科技有限公司，浙江 乐清 325600）
摘要：空气源热泵系统作为一种高效节能的供暖和制冷设备，在我国广泛应用。然而，其运行数据复杂多变，
如何有效分析这些数据并挖掘关键信息，对于提高热泵系统的运行效率至关重要。论文采用主成分分析（PCA）
和相关性分析，对空气源热泵系统的运行数据进行深入挖掘。PCA 分析提取了热泵系统在温度变化、功率消耗、
电气性能、换热效率和环境因素等方面的特征；皮尔逊线性相关分析表明，输入功率与相电流呈强相关性，换热量
与换热器出口温差密切相关，性能系数（COP）与换热量也表现出显著关联，进一步凸显了传热强化对能效提升的
重要性；Spearman 秩相关分析中，输入功率与相电流、换热量与换热器出口温差的秩相关系数高于 0.8，性能系数
与换热量的秩相关系数高于 0.7，高秩相关系数表明，即使在复杂的非线性系统中，这些参数间的关联程度依然显
著。研究结果表明，PCA 和相关性分析为热泵系统的关键信息提取提供了有效工具，能够显著提高性能预测和故
障诊断的效率与准确性。
关键词：热泵系统；主成分分析；相关性分析；数据挖掘
中图分类号：TB69；TP274 文献标志码：A 文章编号：1006−7086（2025）05−0587−09
DOI：10.12446/j.issn.1006-7086.2025.05.006

The Integrated Application of Principal Component Analysis and Correlation Analysis in
Data Mining of Heat Pump System Operation

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MIAO Yike ，HU Lulu 1,2* ，YUAN Pangang ，WANG Yue ，HUANG Haiyan 2
（1. School of Mechanical Engineering，Jiangsu University of Technology，Changzhou 213001，Jiangsu，China；
2. Zhejiang AMA & HIEN Technology Co.，Ltd.，Yueqing 325600，Zhejiang，China）
Abstract： The air-source heat pump system， known for its high energy efficiency and low environmental impact， is
widely used in China for heating and cooling applications. However， the operational data of such systems is complex and
variable that make it crucial to effectively analyze and extract key information in order to enhance the system's operational ef-
ficiency. This study employed Principal Component Analysis （PCA） and correlation analysis to deeply mine the operational
data of the air-source heat pump system. PCA was used to extract the key features of the system，including temperature varia-
tion，power consumption，electrical performance，heat exchange efficiency，and environmental factors. The analysis helped
identify the most influential factors affecting the system’s performance. The results of Pearson linear correlation analysis re-
vealed strong correlations between input power and phase current，as well as a close relationship between heat exchange and
the temperature difference at the heat exchanger outlet. Furthermore，the Coefficient of Performance （COP） showed a signif-
icant correlation with the heat exchange process，emphasizing the importance of enhancing heat transfer to improve energy
efficiency. Spearman rank correlation analysis was also conducted，revealing that the rank correlation coefficients between in-
put power and phase current，as well as between heat exchange rate and the temperature difference at the heat exchanger out-
let，were both greater than 0.8. Additionally，the rank correlation coefficient for COP and heat exchange rate exceeded 0.7.
These high rank correlation coefficients indicated that， even within a complex and nonlinear system， the relationships be-
tween these parameters remained highly significant. The results of this research demonstrate that PCA and correlation analy-

收稿日期：2025−03−03
基金项目：中国博士后科学基金（2024M762957）；江苏省研究生科研与实践创新计划项目（SJCX24_1785）
作者简介：苗毅珂，硕士研究生。E-mail：1150184457@qq.com
通信作者：胡露露，博士，高级工程师。E-mail：hululu8586@163.com