Shape Adaptation Low Rank Representation for Thermal Fault Diagnosis of Power Equipments

HUANG Zhihong; HONG Feng; HUANG Wei

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.

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

Received Date: 2022-02-10
Rev Recd Date: 2022-02-15
Publish Date: 2022-08-20

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.
- power equipment,
- infrared image,
- thermal fault diagnosis,
- superpixel segmentation,
- low-rank represent

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References(17)

References

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