Physical equipment digital twin modeling simulation prediction method based on online learning

Abstract

The invention relates to a physical equipment digital twin modeling simulation prediction method based on online learning, and belongs to the technical field of computer simulation and intelligent manufacturing. According to the method, learning parameters are continuously updated in an interactive form based on static initial training data and dynamic data sources. A multi-layer neural network and an online learning method are utilized to construct a digital twinborn model, and the model is utilized to perform simulation prediction on the operation state of the entity equipment, so that real-time accurate prediction about the entity equipment is obtained. According to the online learning method based on Thompson sampling, various prediction parameters are dynamically updated, and the consistency of the digital twin model and the entity model can be kept. The method can accurately capture the dynamic change in the entity operation process, resists interference factors changing along with time in the entity operation, and can adapt to the dynamic change disturbance of the entity. The method has the advantages of online learning and updating, the data acquisition mode is more convenient, the requirement for the initial data size is low, operation is easy and convenient, practical operability is high, and application is wide.

Description

technical field [0001] The invention relates to an online learning-based digital twin modeling, simulation and prediction method for entity equipment, and belongs to the technical field of computer simulation and intelligent manufacturing. Background technique [0002] Digital Twins is a simulation process that integrates multi-disciplinary, multi-physical, multi-scale and multi-probability by making full use of physical model, sensor update, operation history and other data, and completes the mapping in virtual space to reflect the corresponding entity. The whole life cycle process of equipment (such as aircraft, machinery, machine tools, etc.) has been widely used in many fields such as product design, product manufacturing, medical analysis, and engineering construction. Through the simulation analysis and prediction of the new generation of information technology such as big data analysis and artificial intelligence in the virtual world, the operation of the physical wor...

AI Technical Summary

Problems solved by technology

In addition, in view of the technical problem that the simulation prediction accuracy based on the traditional static digital twin model is not high in a dynamic environment, the online learning method based on Thompson sampling in the present invention can dynamically update various prediction parameters, and can maintain the consistency between the digital twin model and the physical model

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