Electroluminescent Sensing Coating for On-Line Detection of Zero-Value Insulators in High-Voltage Systems
In high-voltage transmission lines, insulators subjected to prolonged electromechanical stress are prone to zero-value defects, leading to insulation failure and posing significant risks to power grid reliability. The conventional detection method of spark gap is vulnerable to environmental interfer...
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Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-07-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/14/7965 |
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Summary: | In high-voltage transmission lines, insulators subjected to prolonged electromechanical stress are prone to zero-value defects, leading to insulation failure and posing significant risks to power grid reliability. The conventional detection method of spark gap is vulnerable to environmental interference, while the emerging electric field distribution-based techniques require complex instrumentation, limiting its applications in scenes of complex structures and atop tower climbing. To address these challenges, this study proposes an electroluminescent sensing strategy for zero-value insulator identification based on the electroluminescence of ZnS:Cu. Based on the stimulation of electrical stress, real-time monitoring of the health status of insulators was achieved by applying the composite of epoxy and ZnS:Cu onto the connection area between the insulator steel cap and the shed. Experimental results demonstrate that healthy insulators exhibit characteristic luminescence, whereas zero-value insulators show no luminescence due to a reduced drop in electrical potential. Compared with conventional detection methods requiring access of electric signals, such non-contact optical detection method offers high fault-recognition accuracy and real-time response capability within milliseconds. This work establishes a novel intelligent sensing paradigm for visualized condition monitoring of electrical equipment, demonstrating significant potential for fault diagnosis in advanced power systems. |
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ISSN: | 2076-3417 |