An intelligent infrared image fault diagnosis for electrical equipment

2020 ◽  
Author(s):  
Ying Lin ◽  
Weiwei Zhang ◽  
Hao Zhang ◽  
Demeng Bai ◽  
Jun Li ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Infrared Image ◽  
Electrical Equipment

scholarly journals Thermal Fault Diagnosis of Electrical Equipment in Substations Based on Image Fusion

2021 ◽  
Vol 38 (4) ◽  
pp. 1095-1102
Author(s):  
Mingshu Lu ◽  
Haiting Liu ◽  
Xipeng Yuan
Keyword(s):  
Fault Diagnosis ◽  
Image Fusion ◽  
Infrared Image ◽  
Electrical Equipment ◽  
True Temperature ◽  
Infrared Images ◽  
Fusion Algorithm ◽  
Infrared Thermal Imaging ◽  
Proposed Model ◽  
Target Extraction

Infrared thermal imaging can diagnose whether there are faults in electrical equipment during non-stop operation. However, the existing thermal fault diagnosis algorithms fail to consider an important fact: the infrared image of a single band cannot fully reflect the true temperature information of the target. As a result, these algorithms fail to achieve desired effects on target extraction from low-quality infrared images of electrical equipment. To solve the problem, this paper explores the thermal fault diagnosis of electrical equipment in substations based on image fusion. Specifically, a registration and fusion algorithm was proposed for infrared images of electrical equipment in substations; a segmentation and recognition model was established based on mask region-based convolutional neural network (R-CNN) for the said images; the steps of thermal fault diagnosis were detailed for electrical equipment in substations. The proposed model was proved effective through experiments.

Comparison of Infrared Image Pre-Processing Technique on Electronic Power Equipment

2013 ◽  
Vol 680 ◽  
pp. 339-344
Author(s):  
Hong Men ◽  
Xin Su ◽  
Peng Chen ◽  
Jia Xue Yu
Keyword(s):  
Fault Diagnosis ◽  
Target Identification ◽  
Infrared Image ◽  
Histogram Equalization ◽  
Processing Technique ◽  
Power Equipment ◽  
Low Snr ◽  
Fuzzy Image ◽  
High Pass ◽  
Subsequent Target

The disadvantages of infrared image are low resolution, bad stereoscopic sense, fuzzy image and low SNR, according to the application of infrared image in fault diagnosis of electronic power equipment, in this paper ,we make a comparative research on pre-processing technique of image de-noising and enhancement, and propose an infrared image enhancement algorithm based on platform histogram equalization combined with enhanced high-pass filtering, the algorithm can effectively improve the contrast by comparison, it is obvious to the noise effect, highlighting the objectives and details, and makes a good foundation for the subsequent target identification and fault diagnosis.

Infrared image of electrical equipment enhancement using grey wolf adaptive nonlocal mean denoising and adaptive fuzzy enhancement

2021 ◽  
Author(s):  
Xin Zhang ◽  
Xikui Sheng ◽  
Chunsheng Li ◽  
Jiaxiang Zhu ◽  
Shanshan Li ◽  
...  
Keyword(s):  
Infrared Image ◽  
Electrical Equipment ◽  
Grey Wolf ◽  
Adaptive Fuzzy ◽  
Fuzzy Enhancement
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