A Digital Twin-Based Operation Status Monitoring System for Port Cranes

Abstract

To address the problems of the lack of an online data simulation test environment, the poor openness of data collection, and the low degree of data visualization in the online control process of port cranes, an operation state monitoring system framework for port cranes based on digital twins is proposed. In this framework, the digital twin port crane is used as the core, and the multi-sensor data acquisition method, OPC UA information model, and plug-in programming method are combined to realize multi-source heterogeneous virtual and real data fusion. The digital twin crane monitoring system based on this framework can fulfil the following functions: crane historical operation process reproduction, control program simulation testing, synchronous mapping simulation, and remote control. In order to verify the proposed method, a digital twin-based physical platform for monitoring a rail-mounted gantry crane (RMGC) was built, in which a virtual test of anti-swing control and a digital twin monitoring experiment were carried out. The results show that the virtual RMGC can test the control algorithm and map the movement process of the physical RMGC, and the crane operation monitoring system has high real-time performance and good visualization effect. In addition, the remote control of the software platform is accurate and effective.

Digital Twins for Ports: Derived from Smart City and Supply Chain Twinning Experience

“…The review of previous studies demonstrates that the potential efficiency gains of port DTs, especially in terminal operations, is acknowledged [17], [16], [134], and this will help to reduce costs [135], perform preventive maintenance [68], contribute towards port resilience [136], and increase operational safety [18]. However, the discussion of DTs in the port context in terms of energy savings through energy-aware scheduling of equipment, optimal use of port facilities, and due to operational efficiency gains through implementation of the best operating scenarios has been little explored in research.…”

“…A growing number of DT studies illustrate the potential of DT implementation to increase the effectiveness of certain port operations. These studies cover a wide range of different terminal operations and problems, including DT applications in automated storage yard scheduling [101], operating status monitoring for port cranes [13], and assisting truck dispatchers [16]. For example, the experimental results of a machine learning based DT implementation of the largest container terminal in Shanghai by Li et al in paper [17] illustrate the potential of DT-based terminal operation.…”

“…In [13], Zhou et al implement a DT port crane framework based on multi-sensor data, which is able to reproduce the historical crane operation process, simulate the control program, simulate the synchronous mapping and take remote control. Zhou et al further propose in [14] a decision support system with a DT-based resilience analysis that assesses a port's resilience to potential disruptive events, taking into account its design, operations and possible predefined post-event recovery measures to mitigate the impact of the disruption.…”

Real-Time Monitoring and Optimal Resource Allocation for Automated Container Terminals: A Digital Twin Application at the Yangshan Port

“…Recently, DTs have been highlighted as one of the most important areas for terminal operations by major container terminal operators. Many works have emphasized the importance of DTs for decision making in the context of container terminals [9][10][11], while the practical application is still scarce. In related studies, a DT is often used as a digital representation of the real-world system for simulation purposes in order to verify that optimization results are applicable in a more complex environment.…”

Design and development of equipment data management visualization system for intelligent KPI evaluation

“…At present, most scholars have focused their research on equipment data management focuses on the real-time acquisition and storage of equipment data. Han [1] established the informatization model of the lithium-ion battery manufacturing workshop, achieving interconnection of production, material, equipment and quality management data; Vaclavova [2] implements an IIoT device based on OPC UA, and improves the equipment detection and data acquisition mechanism; Song [3] proposed the integration scheme of OPC UA and industrial robot operating system ROS, which realized the integration and unified management of equipment information in intelligent workshops; Yu [4] developed an industrial gateway system using ZooKeeper distributed clusters for efficient management of device data, enabling data acquisition for different devices, and predictive maintenance of devices; Zheng [5] uses the hash table and principal component analysis method to complete the cleaning and dimensionality reduction of equipment resource data, which simplifies the difficulty of further analysis of equipment data; Zhou [6] applied the OPC UA information model to a digital twin harbour crane to achieve virtual and real data collection and fusion of heterogeneous data from multiple sources. However, there are still few researches on applying OPC UA to data acquisition of heterogeneous equipment in discrete manufacturing, and then visual analysis after data integration.…”