A PLC–Vision Bilateral Stage Consistency Verification Method for Virtual Commissioning of Discrete Assembly Lines
Virtual commissioning of discrete assembly lines lacks a unified stage representation and an integrated verification mechanism for PLC control states, virtual execution results, and physical workpiece states, making it difficult to determine whether the control program drives the actual equipment according to the prescribed process sequence. To address this issue, a PLC–vision bilateral stage consistency verification method is proposed. Structured PLC control states are mapped to virtual actions in Unity, and execution-confirmed virtual execution stages are generated based on action-completion feedback. On the physical side, YOLO11 object detection is integrated with process-region mapping and temporal constraints to generate vision-derived physical-stage events. The virtual and physical stages are then compared using unified stage semantics to identify consistent operation, physical-state lag, physical-state lead, missing visual events, and invalid stage transitions. Experiments were conducted at a representative station of a discrete assembly line using a single workpiece and a fixed operating path. The visual-stage event recognition method achieved an F1-score of 98.33%, with an average event-generation latency of 104.21 ms. In 140 tests covering normal and controlled abnormal operating conditions, all system decisions agreed with the predefined condition labels. The proposed method extends conventional one-way verification of PLC-driven virtual models to bilateral verification between virtual execution results and physical workpiece states, thereby providing an effective technical approach for control-program commissioning and operating-state verification in discrete assembly lines.
Authors
- Wei Liang (ORCID: https://orcid.org/0000-0003-3542-2257)
- Yuxin Li (ORCID: https://orcid.org/0000-0002-1681-192X)
- Hang Jia (ORCID: https://orcid.org/0009-0005-0814-306X)
- Xin Zhao
Institutions
- Changchun University of Science and Technology (CN)
Publication Details
- Journal
- Machines
- Published
- 2026-10-07
- DOI
- https://doi.org/10.3390/machines14101159
- Primary Topic
- Industrial Automation and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00