基于集成学习的设备流场性能分析与应用

Performance Analysis and Application of Equipment Flow Field Based on Ensemble Learning

为解决某高速设备试验中流场性能实时分析的问题,对该设备的数据采集与分析技术展开研究。阐述某高速试验设备数据特点和性能分析的需求,对采集的数据进行可信度校验;针对其各核心系统模块中不平衡样本数据,基于Bagging集成学习对各个核心系统进行建模分析,实现对该设备的流场性能分析。实际应用结果表明:该方法能完成对核心系统的流场性能分析,提高对该设备的智能管控水平。

In order to solve the problem of real-time analysis of flow field performance in a high-speed equipment test,the data acquisition and analysis technology of the equipment was studied. The data characteristics and performance analysis requirements of a high-speed test equipment were described, and the credibility of the collected data was verified.Aiming at the unbalanced sample data in each core system module, the modeling analysis of each core system was carried out based on bagging ensemble learning, and the flow field performance analysis of the equipment was realized. The practical application results show that the method completes the flow field performance analysis of the core system and improves the intelligent management and control level of the equipment.