Ontology-driven workshop unsafe state semantic reasoning method in digital twin environment

Abstract

The invention provides an ontology-driven workshop unsafe state semantic reasoning method in a digital twin environment. The method comprises the following steps: firstly, establishing a semantic ontology model of an unsafe state of a workshop production site through a network ontology language (OWL), and establishing inference rules of different types of workshop unsafe states by using a semantic web rule language (SWRL); then, encoding the established semantic ontology of the unsafe state of the workshop production site by using an ontology editor Protege; secondly, simulating the unsafe state virtual scene of the twin workshop in Unity 3D, and recording a high-fidelity simulation animation into a video as a data set source of subsequent target detection; then, identifying instances in an unsafe state of a workshop production site by using an instance segmentation algorithm, and mapping the instances into instances of the established ontology; and finally, executing an inference rule by using an inference engine to realize automatic inference of the potential danger state and related information of the workshop production site.

Description

technical field [0001] The invention relates to the technical field of digitalization and intelligentization of production management in a manufacturing workshop, in particular to an ontology-driven semantic reasoning method for an unsafe state in a workshop under a digital twin environment. Background technique [0002] The workshop is the basic unit of production and operation of a manufacturing enterprise, which is composed of factors such as people, equipment, materials and the environment. The safety management of the workshop production site is the basis for ensuring the smooth progress of all workshop production activities. The traditional workshop production site safety management is based on human experience and supplemented by safety reminders. For example, the safety of personnel, equipment, production lines, and the environment is ensured through camera monitoring, regular inspections by security officers, on-site safety warning signs, safety doors, light barrier...

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Problems solved by technology

[0005] For this reason, in view of the above problems, the present invention proposes an ontology-driven semantic reasoning method for workshop unsafe states in a digital twin environment, and establishes a semantic ontology model and reasoning rules for workshop production site unsafe states according to the workshop site in physical space; On this basis, use the twin workshops in the virtual space to simulate the realistic scene of the unsafe state of the workshop, record it as a video as the source of the data set, combine the instance segmentation algorithm to automatically identify the ontology instance set required for semantic reasoning from the data set; finally use the inference engine Execute pre-defined reasoning rules, automatically deduce the type of unsafe state in the workshop production site, the cause, the personnel involved and the hazards, etc., to make up for the shortcomings of the workshop production site safety management method based on human subjective experience, and Extreme production environment leads to high cost and high risk of safety training, avoiding irreversible production safety accidents

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