In order to actively promote the construction of new power systems and the digital transformation and upgrading of power grid companies, and explore the application of artificial intelligence technology, the power grid company has currently built an artificial intelligence "two libraries and one platform", namely an artificial intelligence platform, a sample library, and a model library, and has carried out a lot of work in the application of artificial intelligence technology in business fields such as equipment management, safety operations, and marketing customer service, accumulating rich results in samples, algorithms, and models. With the increasing demand for intelligent application services, various business departments have an increasing demand for samples and models. Against the backdrop of the growing demand for electrical component recognition, scarce scenario defect detection, model training, and diverse requirements for model deployment and application, it is urgent to introduce electrical component intelligent recognition and scarce scenario defect detection capabilities on top of existing artificial intelligence basic support capabilities to achieve model training, iteration, optimization, and accuracy improvement. By deeply integrating artificial intelligence basic capabilities with core power grid business applications, we can further enhance our ability to empower professionals and serve grassroots.

Gao Fengxi, He Xin, Wu Zhuohang, Liang Yi, Han Zhentao, Sun Mingze, Liu Hao. Analysis of Defect Recognition in Transmission Drones Based on Artificial Intelligence. International Journal of New Developments in Engineering and Society (2025), Vol. 9, Issue 2: 96-101. https://doi.org/10.25236/IJNDES.2025.090216.

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