# Prediction System for Overhead Cranes Based on Digital Twin Technology
## 1 Introduction  
Digital twin technology is used to map the real world to the virtual world through perception and calculation to realize virtual-real fusion and cognitive prediction. It is an important approach to realize \"simulation\" [1]. Application of digital twin technology to predictive maintenance of overhead cranes requires building an accurate model of an overhead crane and monitoring and tracking it. The working status of each component of the overhead crane can be fully grasped through formulating corresponding standards. This method can detect the operating status of the overhead crane and predict the service life of the main components, so it is significant for the normal operation and safety precautions of overhead cranes [2]. Digital twin simulation is to keep in sync with its reflected data of the overhead crane in terms of appearance, content, and movement speed, and the state will be the same [3]. Though the simulated crane is a virtual 3D software product, it can truly represent the performance of the physical body. In actual experimental operations, it can remotely monitor the running status of a crane from a safe distance and issue work instructions such as start, stop, forward, and backward. Traditionally, the operating experience of machinery and equipment is vague, difficult to grasp, and indispensable for judgment [4]. In contrast, application of simulation digital twin technology can digitally manage experience that could not be saved before, as well as save, modify, copy, and migrate the experience [5]. Based on currently achieved program simulation, the thinking imagination can be further broadened. Meanwhile, a complete database of crane operating parameters can be established through repeated experiments to achieve data collection, storage, and analysis. In addition, through using new-generation technologies such as artificial intelligence, big data, and edge computing, all the states in each step of the overhead crane can be predicted, and evaluation and warnings of its potential risks can be made in advance [6].  
The rest of this paper is organized as follows. Section 2 describes the research progress of advanced digital twin technology. Section 3 introduces the design of the basic digitaltwin software. In Section 4, the remaining service life of a bridge crane is predicted using an algorithm. In Section 5, the simulation experiment and the virtual-real synchronization experiment of the digital twin for the crane are conducted. Section 6 makes a technical summary of the crane digital twin software.  
The contributions of this paper are as follows:  
1. The digital twin model is established to read the real-time lifting operation information of the physical overhead crane, realize synchronous mapping of the lifting operation scenario of the physical overhead crane in the virtual environment, and simulate lifting operation tasks that have been set to verify the feasibility of lifting operations.
2. To monitor the physical bridge-crane-lifting operation, the virtual bridge crane can synchronize and monitor the lifting operation of the physical bridge crane in real time, thus assisting the physical bridge crane to achieve predictive maintenance.
3. A good human-computer interaction interface is provided, making it easy for the operator to give control instructions to the digital twin model and obtain the bridge crane's real-time operational data.
4. The life of the overhead crane is predicted using the stress and strain of the main beam of the overhead crane.