Work

Power grid inspection based on multimodal foundation models

Year: 2025

Type: article

Abstract: INTRODUCTION: With the development of large foundation models, power grid inspection is transmitting from traditional deep learning to multimodal foundation models.OBJECTIVES: This paper aims to boost the application of multimodal foundation models for power grid inspection.METHODS: Current research on foundation models and multimodal large language models (LLMs) is introduced respectively. Three application forms of multimodal foundation models in power grid inspection are explored. The reliability of these models is discussed as well.RESULTS: These techniques can significantly reduce the time and cost of inspection by automating the analysis of large amounts of sensor data. They can also improve the accuracy and reliability of inspection by leveraging the understanding and reasoning abilities of LLMs.CONCLUSION: These advanced techniques have shown great application potential in power grid inspection. But it is important to note that they should not entirely replace human inspectors who can validate automatic findings and address possible issues not captured by these models alone.

Source: EAI Endorsed Transactions on Energy Web

DOI: 10.4108/ew.9087

Authors: Jingbo Hao, Yang Tao

Institutions: Nanchang Institute of Science & Technology, Nanchang Vocational University

Language: English

Topic: Power Line Inspection Robots

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: diamond

Funder: Education Department of Jiangxi Province