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Volume 47 Issue 8
Aug.  2022
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HUANG Zhihong, HONG Feng, HUANG Wei. Shape Adaptation Low Rank Representation for Thermal Fault Diagnosis of Power Equipments[J]. Infrared Technology , 2022, 44(8): 870-874.
Citation: HUANG Zhihong, HONG Feng, HUANG Wei. Shape Adaptation Low Rank Representation for Thermal Fault Diagnosis of Power Equipments[J]. Infrared Technology , 2022, 44(8): 870-874.
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Shape Adaptation Low Rank Representation for Thermal Fault Diagnosis of Power Equipments

  • 1.

    State Grid Hunan Electric Power Corporation Limited Research Institute, Changsha 410007, China

  • 2.

    State Grid Hunan Electric Power Corporation Limited, Changsha 410029, China

  • 3.

    Hunan Xiangdian Test and Research Institute Corporation Limited Research Institute 410007, China

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  • Received Date: February 09, 2022
  • Revised Date: February 14, 2022
    Graphical Abstract
    • Abstract
  • This work introduces a thermal fault diagnosis method that integrates superpixel segmentation and low-rank representation for diagnosis. The proposed method comprises two main steps. First, an input infrared image is transformed using a principal component analysis (PCA) algorithm, and a superpixel segmentation method is employed for the first principal component (PC). The first PC is divided into non-overlapping homogeneous superpixels. Then, the thermal fault region is detected by employing low-rank representation in a superpixel-by-superpixel manner. Experimental results show that the proposed diagnosis method has a better detection performance than that of current state-of-the-art detectors.
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    • References (17)
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