Digital twin based intelligent coating film thickness monitoring system

Abstract

Aiming at the problems of large ship segment automated spraying workshop spraying operation when the paint mist is diffuse, it is difficult to carry out real-time monitoring of the spraying situation, as well as the film thickness cannot be measured in real time and feedback leads to the spraying control parameters cannot be adjusted in time, resulting in the poor quality of the film formation, and so on. An intelligent monitoring method based on digital twin technology is proposed in this study, and a twin body model of the key elements of the digital twin workshop is established. Focusing on the construction of physical model and rule model, through the construction of physical model, the physical entity of the key elements is transformed into a digital model to make up for the shortcomings of the under-sensor digital twin system. The rule model establishes the implicit relationship between the data and the characterization phenomenon, enabling real-time prediction of the film thickness during data-driven spraying of the spray gun. Additionally, the study explores the technology related to the construction of the twin system in the automated spraying workshop, including the construction of the virtual scene and the data communication method using the OPC UA protocol. The researchers successfully build a digital twin system using Unity 3D and verify the reliability of the spray particle deposition film thickness monitoring function through experiments.