汽车电驱动系统多源异构信号融合分类研究

Research on the Fusion and Classification of Multi-source Heterogeneous Signals in the Electric Drive System of Automobiles

多源异构数据融合作为汽车电驱动系统领域中的重要数据处理手段备受瞩目,其在汽车电驱动系统领域中扮演着关键角色,为深入理解系统运行特征和解决复杂问题提供有效手段。该文通过对多源异构信号特点、融合层次分类的剖析,提出一种应用于汽车电驱动系统的多源异构数据融合方法,并利用采集到的电驱动多源异构数据对融合算法进行验证,结果表明,融合分析能够有效地区分汽车电驱动系统质量。

Multi source heterogeneous data fusion,as an important data processing method in the field of automotive electric drive systems,has attracted much attention.It plays a key role in the field of automotive electric drive systems,providing an effective means for a deeper understanding of system operation characteristics and solving complex problems.This paper proposes a multi-source heterogeneous data fusion method applied to automotive electric drive systems by analyzing the characteristics of multi-source heterogeneous signals and the classification of fusion levels.The fusion algorithm is validated using the collected multi-source heterogeneous data of electric drive systems,and the results show that fusion analysis can effectively distinguish the quality of automotive electric drive systems.