制冷技术2025，Vol.45Issue(6)：8-17,10.DOI:10.3969/j.issn.2095-4468.2025.06.102
应用提升算法对地铁空调系统并发故障的高精度诊断研究
High-Accuracy Diagnosis of Concurrent Faults in Subway Air Conditioning Systems Using Boosting Algorithms
摘要
Abstract
This study delves into the efficient diagnosis of concurrent faults in subway air conditioning systems,emphasizing their significance for passenger comfort,as well as the safety and efficient operation of subway networks.Leveraging machine learning techniques,particularly boosting algorithms,overcomes the limitations of neural network models in fault diagnosis and significantly improves diagnostic accuracy.Specifically,six boosting algorithms:Gradient Boosting,XGBoost,LightGBM,CatBoost,Extreme Random Trees,and AdaBoost are applied and evaluated for their performance on both training and testing datasets,showcasing their advantages and application potential.Achieving near-perfect accuracy of 1.0 on the training set and nearly reaching 1.0 accuracy on the testing set,the algorithms demonstrate their effectiveness in enhancing the precision of fault diagnosis in subway air conditioning systems.关键词
地铁空调系统/并发故障诊断/提升算法/故障拟合/智能维护Key words
Subway air conditioning system/Concurrent fault diagnosis/Boosting algorithms/Fault fitting/Intelligent maintenance分类
建筑与水利引用本文复制引用
陈可为,杨闯,陈焕新,杨宇..应用提升算法对地铁空调系统并发故障的高精度诊断研究[J].制冷技术,2025,45(6):8-17,10.基金项目
国家自然科学基金(No.51876070). （No.51876070）
