Crawler crane is a key equipment in large-scale infrastructure. In order to ensure operation safety, digital twin technology can be applied to crawler crane to monitor the working state of crawler crane in real time. Firstly, the physical model and virtual model of crawler crane were built, and the surface reduction optimization of the model was carried out by the edge collapse algorithm, so as to construct the reduced-order model. Secondly, the working condition data of the crawler crane is collected in real time through the pose sensor. Finally, the digital twin system was tested. The results show that by collecting the real-time working condition data of the experimental prototype and sending it to the crawled crane digital twin system, the virtual model can be driven to do the corresponding movement, and the real-time monitoring of the working attitude and data can be realized.