Effect of X-ray irradiation on partial discharge inception and extinction voltage characteristics of cast resin transformer insulation system

Makki, Shohei; Kozako, Masahiro; Hikita, Masayuki; Nakamura, Yusuke; Hirose, Takahisa; Maeda, Teruhiko; Iida, K.; Umemura, Tokihiro; Nakamura, Shuhei; Higashiyama, Masakazu

doi:10.1109/icsd.2013.6619669

Cited by 7 publications

(3 citation statements)

References 7 publications

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“…However, cast-resin transformers have a risk of accidents leading to insulation breakdown due to manufacturing defects such as cracks, heat accumulation, and voids [5], [6]. Initial defects can significantly shorten the lifetime of cast-resin transformer and greatly affect its reliability [7]. Recently, while the incidence of accidents due to manufacturing defects has decreased, there is an increase in degradation due to thermal, mechanical, and electrical caused by continuous loads [8], [9].…”

Section: Introductionmentioning

confidence: 99%

Classification of PRPD Pattern in Cast- Resin Transformers Using CNN and Implementation of Explainable AI (XAI) With Grad-CAM

Kim,

Jung,

Hwang

et al. 2024

IEEE Access

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Cast-resin transformers are affected by deterioration due to manufacturing defects and continuous load. Studying PD, which is capable of detecting defects or degradation in advance, is important. With the rapid advancement of AI technologies, research on PD classification using CNN models is being actively conducted. However, due to the black box problem, it is impossible to explain the reasoning behind the learning outcomes. Therefore, relying solely on predictive outcomes of learning for PD classification raises issues of reliability. Recent studies in various fields are progressing with the application of XAI to address the black box issue of CNNs, aiming to identify the criteria used for making predictions. However, research on applying XAI in AI-based PD classification is currently insufficient. Therefore, further study on the implementation of XAI is necessary. In this paper, an excellent CNN model was applied to image classification for PD classification of cast-resin transformers, and the grad-cam model was used for XAI. This approach proposes a method for humans to comprehend the rationale behind the learning outcomes. The data used for training consists of artificial defects under laboratory conditions and noise measured in castresin transformers via UHF sensors. PD and noise classification due to defects was performed, and the reasons for successful and failed results were analyzed through XAI. Consequently, it was observed that the application of XAI to CNN models leads to the construction of a more reliable model. INDEX TERMSCast-resin transformer, PD, pattern classification, convolution neural network (CNN), explainable artificial intelligence (XAI), gradient weighted class activation mapping (Grad-CAM)

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Section: Introductionmentioning

confidence: 99%

Classification of PRPD Pattern in Cast- Resin Transformers Using CNN and Implementation of Explainable AI (XAI) With Grad-CAM

Kim,

Jung,

Hwang

et al. 2024

IEEE Access

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“…So far, there are many reports on PD in a single cavity in solid insulating material [1][2][3][4][5][6][7][8][9][10][11][12][13], while only a few report on PD in material with multi cavities. In this paper, we investigate discharge phenomena in micro cellular resin including multi cavities with micrometer order size by measuring partial discharge inception voltage (PDIV) and breakdown voltage (BDV).…”

Section: Introductionmentioning

confidence: 99%

“…X-ray irirradiation to the sample was carried out to resolve this problem. An X-ray module with 10 W output power was used to supply an initial electron to the cavity which minimizes the time lag of discharge occuring in the cavity [6].…”

Section: Introductionmentioning

confidence: 99%

Partial discharge inception voltage and breakdown voltage of micro cellular resin

Yanaze

Kozako

Hikita

et al. 2015

2015 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP)

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This paper deals with partial discharge inception voltage (PDIV) and breakdown voltage (BDV) of novel insulating material including multi micro size cavities to reduce its permittivity and wight as well for insulation performance test of high voltage cable and equipment. PDIV of specimen including multi voids with average diameter of decrease with X-ray irradiation. The result suggests that PD would occur in the specimen with average diameter of . In addition to BDV and PDIV increases with the decrease of the cavity size.

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Partial discharge inception voltage measurement and location identification of enamel coating ribbon wire used for low-voltage motors

Yanaze

Nakaya²,

Kozako³

et al. 2014

2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena (CEIDP)

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Effect of X-ray irradiation on partial discharge inception and extinction voltage characteristics of cast resin transformer insulation system

Cited by 7 publications

References 7 publications

Classification of PRPD Pattern in Cast- Resin Transformers Using CNN and Implementation of Explainable AI (XAI) With Grad-CAM

Classification of PRPD Pattern in Cast- Resin Transformers Using CNN and Implementation of Explainable AI (XAI) With Grad-CAM

Partial discharge inception voltage and breakdown voltage of micro cellular resin

Partial discharge inception voltage measurement and location identification of enamel coating ribbon wire used for low-voltage motors

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