Abstract: An intelligent identification and warning method for an uncertain object of a production line in a digital twin environment, includes: establishing a model library for uncertain physical objects from a non-production line system; adding attribute data to the uncertain physical objects from the non-production line system; importing an established model library and added attribute data for the uncertain physical objects from the non-production line system into a model library of an existing DT production line system; performing auto-detection on an uncertain physical object entering a production line system; performing auto-detection on an actual size of the uncertain physical object entering the production line system; warning a danger for an unsafe object by means of voice prompting, system alarming and information pushing; matching a corresponding three-dimensional (3D) model in the established model library for a safe object; and loading a matched 3D model to the DT production line system.

Abstract: An intelligent identification and warning method for an uncertain object of a production line in a digital twin environment, includes: establishing a model library for uncertain physical objects from a non-production line system; adding attribute data to the uncertain physical objects from the non-production line system; importing an established model library and added attribute data for the uncertain physical objects from the non-production line system into a model library of an existing DT production line system; performing auto-detection on an uncertain physical object entering a production line system; performing auto-detection on an actual size of the uncertain physical object entering the production line system; warning a danger for an unsafe object by means of voice prompting, system alarming and information pushing; matching a corresponding three-dimensional (3D) model in the established model library for a safe object; and loading a matched 3D model to the DT production line system.

Abstract: An intelligent material completeness detection and configuration method based on digital twin and augmented reality (AR) includes: constructing a digital twin model base and knowledge base of an incomplete material; importing the digital twin model base and knowledge base of the incomplete material respectively into a model database and a knowledge database in a digital twin system database; sending materials to be detected into a vision-based material completeness detection platform, sorting out an incomplete material, acquiring corresponding data, and importing the data into an incomplete material information database; performing, based on an AR device, perception and reconstruction of incomplete material configuration; matching a configuration plan of the incomplete material in a digital twin relational database, and performing a virtual-real fusion in the AR device; and allowing, a worker to rapidly and accurately find a location and problem type of the incomplete material and configuration the incomplete