Research on Marker Recognition Method for Substation Engineering Progress Monitoring Based on Grounding DINO

The traditional progress monitoring method for substation engineering mainly relies on manual work, which is time-consuming and laborious. Based on this, this paper proposes a new marker recognition method for substation engineering progress monitoring based on Grounding DINO. This method uses Grounding DINO to recognize the key markers of substation engineering and combines the weights of the markers to monitor the construction progress of substation engineering. Grounding DINO is a large-scale visual object detection model with strong generalization in feature extraction ability. We further use LoRA (Low-Rank Adaptation) method to fine-tune and optimize its feature extraction network, so that it can improve the recognition accuracy and reliability of key markers in different stages of substation engineering infrastructure at a small data cost. Thus, the construction progress of substation engineering can be carefully monitored. We selected 24 kinds of key markers of substation engineering to carry out experiments, and the results showed that the average recognition accuracy of key markers can reach 95.13%, which effectively proved the effectiveness of the improved Grounding DINO model. In addition, this article used the proposed method to analyze the construction progress of the Xiantao Xianxi 200kV substation engineering, and the results showed that our method could effectively monitor the construction progress of the substation engineering. It proved that our method had great application market and potential.