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Keywords

cable terminations, infrared images, deep learning network, Mean-Shift algorithm, overheating regions

Abstract

The extraction of abnormal heating regions in infrared images is the important prerequisite for the intelligence diagnosis of thermal state in the electrical equipment. For cable terminations, an automatic extraction method is proposed in this paper. Firstly, an adaptive wavelet threshold denoising method based on Maximum a Posteriori Estimation (MAP) is applied to remove the noise and improve the quality of infrared images. Then, the cable terminations in the images are identified and located by the deep learning network, and the interference information is eliminated. Finally, the Mean-Shift algorithm is employed to cluster the pixels of cable terminations. The abnormal heating regions are extracted on the basis of clustering results. It is shown that the proposed method is suitable for infrared images at different backgrounds and different shooting angles. After identifying and locating the cable terminations, the overheating regions can be extracted accurately. Comparing with some existing methods in efficiency and accuracy, the proposed method achieves a better performance.

DOI

10.19781/j.issn.1673-9140.2022.02.002

First Page

12

Last Page

21

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