A Digital Twin Method for Marine Engines Based on PSO Algorithm

The main feature of digital twins is that the model obtains real-time data of physical entities through sensors and evolves along with the physical entities, enabling real-time updates and dynamic evolution. When the engine is running normally, the digital twin model remains consistent with the physical entity; When the engine degrades, the operating state of the engine will deviate from the running digital twin model. At this time, it is necessary to update the twin model to maintain consistency with the physical entity. This study established a digital twin model for marine engines and proposed a digital twin method for marine engines based on the PSO algorithm. Update the twin model through optimization techniques to achieve state synchronization with physical entities. Finally, the accuracy of the twin model and the proposed method were validated. The results indicate that the PSO algorithm can quickly update the twin model, which is beneficial for the twin model to quickly respond and synchronize with the physical entity state.