Abstract: This paper designed an intelligent operation and maintenance system for EMUs based on digital twin technology to address the limitations of the traditional operation and maintenance mode in terms of dynamic operational condition responsiveness, fault diagnosis accuracy, and maintenance timeliness performance. It constructed a five-layer architecture consisting of "physical entity layer – data resource layer – twin virtual layer – intelligent service layer – business decision layer" to implement multi-source integration and virtual-real collaborative mapping of EMU whole lifecycle data, and elaborated on key technologies such as high-precision 3D modeling, dynamic behavior simulation, and real-time transmission and fusion of multi-source heterogeneous data, as well as core functions such as real-time monitoring, fault warning, simulation, and maintenance guidance. Practical application results show that the system enhances the transparency of EMU condition monitoring processes and fault prediction capabilities via real-time data interaction and visualization technologies, thus providing a reliable basis for scientific decision-making and demonstrating significant engineering application value for EMU operation and maintenance practices.