MCTSR: A super‐resolution method for defects in gas‐insulated switchgear X‐ray images based on multi‐scale contextual transformers

Abstract

As the core equipment of transmission and distribution hubs, the operational status of gas‐insulated switchgear (GIS) is closely linked to the safety of the power system. Recently, X‐ray digital imaging technology has been extensively used in GIS equipment fault detection. However, the X‐ray image of GIS is blurred, which is not conducive to the detection of tiny defects. Thus, a super‐resolution method for GIS X‐ray images based on multi‐scale context transformers is proposed in this study, namely MCTSR. Firstly, a second‐order image degradation model is introduced to generate GIS X‐ray low‐resolution images that more closely resemble the real world. Secondly, a contextual transformer gate module is constructed to improve attention to tiny defects in GIS X‐ray images. Thirdly, a U‐Net discriminator network based on multi‐scale contextual transformers is intended to enrich the information of the generated images. Finally, the proposed discriminator is combined with the existing generator to compose a super‐resolution method applicable to GIS X‐ray images. The experimental results demonstrate that the method outperforms other methods in peak signal‐to‐noise ratio and structural similarity on the constructed GIS X‐ray image dataset. In addition, the output image of the proposed method facilitates the subsequent defect detection.

Intelligent overheating fault diagnosis for overhead transmission line using semantic segmentation

“…Li et al investigated the combination of deep learning and adversarial networks, using a deep learning-based prediction model and adversarial training to address sensor fault issues in test scenarios, extracting invariant features from different entities and sensors using adversarial networks [12]. Liu et al introduce a super-resolution method for enhancing X-ray images of gas-insulated switchgear (GIS) using multi-scale context transformers, improving the detection of tiny defects and outperforming other methods in image quality, ultimately aiding in defect detection for GIS equipment [13]. Zhang et al divided the infrared shooting material into sections containing towers (SETs) and sections without towers (SNETs).…”

“…Liu et al. introduce a super‐resolution method for enhancing X‐ray images of gas‐insulated switchgear (GIS) using multi‐scale context transformers, improving the detection of tiny defects and outperforming other methods in image quality, ultimately aiding in defect detection for GIS equipment [13]. Zhang et al.…”