Research on live detection technology of distribution network cable insulation deterioration state based on harmonic components Article Swipe
Ran Hu
,
Haisong Xu
,
Xu Lu
,
Anzhe Wang
,
Zhifeng Xu
,
Yuli Wang
,
Daning Zhang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1049/gtd2.13238
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1049/gtd2.13238
Due to the limitations imposed by urban power grid outages for maintenance, on‐line harmonic current detection technology for distribution network cables is expected to become an effective supplement to traditional offline diagnostic methods, enhancing the real‐time diagnosis of distribution network cable insulation conditions. This study established a 10 kV distribution network cable test platform and prepared typical defective cables subjected to moisture and long‐term thermal aging. Using COMSOL finite element electromagnetic simulation, the magnetic flux evolution laws of the cable insulation under typical defects were obtained. Experimental tests provided the harmonic current characteristics and statistical features of cables with typical defects. Based on these data, a method for analysing the degradation degree of distribution network cables was constructed using least absolute shrinkage and selection operator (LASSO) regression analysis. Furthermore, a defect‐type identification method based on cluster analysis was proposed. Results indicate that the odd harmonics and the 4th harmonic of the distribution network cable's harmonic current are closely related to the cable's degradation state. A model integrating principal component analysis (PCA) data dimensionality reduction and expectation‐maximization clustering analysis achieved a recognition accuracy of up to 75.64% in distinguishing between moisture‐affected and normal cable states. The proposed on‐line detection and evaluation methods can effectively identify high‐risk cables with latent defects.
Related Topics
Concepts
Harmonic
Harmonics
Power cable
Engineering
Cluster analysis
Electronic engineering
Harmonic analysis
Principal component analysis
Transient (computer programming)
Computer science
Reliability engineering
Voltage
Electrical engineering
Acoustics
Artificial intelligence
Materials science
Composite material
Physics
Layer (electronics)
Operating system
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1049/gtd2.13238
- OA Status
- gold
- Cited By
- 2
- References
- 21
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4401645706
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4401645706Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1049/gtd2.13238Digital Object Identifier
- Title
-
Research on live detection technology of distribution network cable insulation deterioration state based on harmonic componentsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-08-16Full publication date if available
- Authors
-
Ran Hu, Haisong Xu, Xu Lu, Anzhe Wang, Zhifeng Xu, Yuli Wang, Daning ZhangList of authors in order
- Landing page
-
https://doi.org/10.1049/gtd2.13238Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1049/gtd2.13238Direct OA link when available
- Concepts
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Harmonic, Harmonics, Power cable, Engineering, Cluster analysis, Electronic engineering, Harmonic analysis, Principal component analysis, Transient (computer programming), Computer science, Reliability engineering, Voltage, Electrical engineering, Acoustics, Artificial intelligence, Materials science, Composite material, Physics, Layer (electronics), Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2Per-year citation counts (last 5 years)
- References (count)
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21Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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