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Research on Recognition and Location Method of Insulator in Infrared Image Based on Deep Learning

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Published under licence by IOP Publishing Ltd
, , Citation Hua Huang et al 2021 J. Phys.: Conf. Ser. 2087 012090 DOI 10.1088/1742-6596/2087/1/012090

1742-6596/2087/1/012090

Abstract

Infrared thermography technology is widely used in the thermal condition detection of insulators due to its advantages of non-contact, sensitive, online detection. To realize the automatic detection of the operating condition of insulators in complex environments, this paper proposes a method for the recognition and location of the insulator based on Region-based Fully Convolutional Networks (R-FCN). The model was trained and tested on the constructed insulator infrared data set, compared with the SSD model. The results showed that the R-FCN detecting insulators can not only accurately locate insulators, but have an AP (average precision) value as high as 89.2%. Therefore, the findings in this paper have verified that R-FCN has great advantages in the recognition and location of infrared images of insulators and has practical application value.

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10.1088/1742-6596/2087/1/012090