State Perception and Prediction of Digital Twin Based on Proxy Model

Abstract

The maintenance of critical components plays a crucial role in ensuring the overall stable operation of equipment and minimizing damages caused by functional errors. However, Traditional operation and maintenance (O&M) modes suffer from problems such as reliance on empirical judgment, lack of data support, insufficient preventive maintenance, and inadequate collaborative management. To address these issues, a viable approach is to adopt more intelligent O&M modes. Based on the characteristics of digital twin technology, such as virtual interaction and real-time feedback, a digital twin framework for critical component maintenance of equipment is proposed, providing a new approach for the practical application of digital twin in intelligent maintenance processes. This framework consists of two key components: the digital twin maintenance model and the proxy model. The process of establishing the digital twin model is elaborated in detail, and a mechanism that integrates digital twin technology and the proxy model is proposed, along with a prediction process based on the fusion of simulation and monitoring data. Finally, based on the summary of the modeling process and the proxy model, a visualization interface for intelligent maintenance of components is built using relevant engineering software.