Defect detection and analysis in composite insulators based on ultrasonic flaw detection technology
Composite insulators are widely employed in high-voltage transmission systems due to their excellent resistance to pollution flashover. However, with extended operational time, internal defects such as voids and cracks may develop, posing a serious threat to the safety and reliability of power systems. This study utilizes ultrasonic flaw detection technology to experimentally investigate and analyze typical defects in composite insulators. The aim is to evaluate the applicability and accuracy of ultrasonic probes operating at different frequencies in detecting cracks and voids in composite insulators. For this purpose, FXBW-10/70 composite suspension insulators were selected, and a series of samples with various defect types were fabricated. Digital ultrasonic flaw detectors operating at frequencies of 5 MHz and 10 MHz were employed for testing. The results indicate that at a frequency of 10 MHz, the ultrasonic probe demonstrates superior resolution and positioning accuracy when detecting cracks and voids, allowing for more precise identification and localization of defects. An error analysis of defect positioning shows that the 10 MHz probe yields significantly lower errors compared to the 5 MHz probe, particularly in the detection of smaller defects, where its advantage is most pronounced. This study provides empirical evidence and technical guidance for the non-destructive testing of composite insulators, contributing significantly to enhancing the operational safety and reliability of power equipment.
Authors
- Jinsheng Huang (ORCID: https://orcid.org/0000-0002-3580-344X)
- Jianfeng Yang (ORCID: https://orcid.org/0000-0003-4411-0706)
- Tongwei Zhang (ORCID: https://orcid.org/0000-0002-9326-6144)
- Xiaoyan Wei (ORCID: https://orcid.org/0000-0002-4754-3737)
- Jia Yang (ORCID: https://orcid.org/0000-0001-8268-2081)
- Jiachen Li (ORCID: https://orcid.org/0000-0001-9137-6262)
Institutions
- Southwest Minzu University (CN)
Publication Details
- Published
- 2025-04-28
- DOI
- https://doi.org/10.1117/12.3067338
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00