A multi-level multi-domain digital twin modeling method for industrial robots

Abstract

Industrial robots (IRs) serve as critical equipment in advanced manufacturing systems. Building high-fidelity digital twin models of IRs is essential for various applications like precision simulation, and intelligent operation and maintenance. Despite technological potentials of digital twins, existing modeling methods for industrial robot digital twins (IRDTs) predominantly focus on isolated domains. This fails to address inherent multi-domain complexities of IRs that arise from their integrated mechanical-electrical-control characteristic. To bridge this gap, first, this study proposes a multi-level multi-domain (MLMD) digital twin modeling framework and method. The framework systematically integrates physical space, digital space, and their bidirectional interactions, while explicitly defining hierarchical structures and cross-domain mechanisms. Subsequently, a four-step method is established, which encompasses component analysis, parameter extraction, MLMD IRDT modeling based on function blocks (FBs), and model validation. Then, implementation details are illustrated through an SD3/500 IR case study, where domain-specific modeling techniques and cross-domain integration mechanisms are systematically analyzed. Finally, effectiveness and feasibility of the proposed method is validated through experiments.