State perception and prediction of digital twin based on proxy model
Published in IEEE Access, 2023
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.
Keywords: Digital twins; Data models; Predictive models; Maintenance engineering; Analytical models; Real-time systems
您可以访问文章页获取具体信息：doi.org/10.1109/ACCESS.2023.3264543
Recommended citation: Wang L, Wang C, Li X, et al. State perception and prediction of digital twin based on proxy model[J]. IEEE Access, 2023, 11: 36064-36072.
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