基于数字孪生的产线设备实时监控方法与实现

Real-time monitoring method and implementation of production line equipment based on digital twins

摘要:

为推动国家智能制造发展，面向生产过程中设备实时监控困难、透明性差、管控效率低、跨学科交叉情况复杂等问题，融合MBSE思想，提出一种基于数字孪生的产线设备监控方法并实现。首先，提出基于数字孪生的监控方法架构；基于SysML建模语言对产线系统和设备进行统一描述建模，建立结构图和行为图，形成数据模型；通过SysML模型与OPC UA联合，以位移数据和任务数据双通道驱动的方式进行虚实映射，并建立异常报警追溯机制；以仓储系统中核心设备堆垛机为例，构建其SysML模型、数字孪生模型，并以仓储产线实时缓存数据库redis为数据源，通过OPC UA获取并实时更新数据驱动数字孪生模型，实现其三维可视化监控，验证了方法的可行性和实时性

Abstract:

In order to promote the development of national intelligent manufacturing, facing the difficulties of real-time monitoring of equipment in the production process, poor transparency, low efficiency of management and control, and complex cross-disciplinary situation, a production line equipment monitoring method based on digital twins is proposed and implemented by integrating MBSE ideas. Firstly, a monitoring method architecture based on digital twins is proposed; Based on SysML modeling language, the production line system and equipment are uniformly described and modeled, and the structure diagram and behavior diagram are established to form a data model; Through the combination of SysML model and OPC UA, the virtual and real mapping is carried out in the way of dual-channel driving of displacement data and task data, and the abnormal alarm tracing mechanism is established; Taking the stacker, the core equipment in the storage system, as an example, its SysML model and digital twin model are constructed, and the real-time cache database redis of the storage production line is used as the data source. The data-driven digital twin model is obtained and updated in real time through OPC UA to realize its three-dimensional visual monitoring, which verifies the feasibility and timeliness of the method