The definition of RPDIV in impulsive testing and the effect of the electrical conditioning on the variability of the results

Caprara, Andrea; Ciotti, Giacomo; Cavallini, A.; Rumi, Alberto

doi:10.1109/eic47619.2020.9158761

Cited by 5 publications

(1 citation statement)

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“…The current definition of RPDIV in international standards does not account for PD bursts. To address this issue, conditioning the insulation system above the RPDIV level is proposed as a suitable approach to reduce the likelihood of observing PD bursts [13,14]. This study provides recommendations for performing more accurate RPDIV measurements by combining the understanding of PD activity behavior with the impact of conditioning.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning and Long-Duration PRPD Analysis to Uncover Weak Partial Discharge Signals for Defect Identification

Chen,

Chou

2023

Applied Sciences

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This study focuses on improving the defect recognition accuracy under weak partial discharges (PDs) in epoxy resin through phase-resolved partial discharge (PRPD) analysis. The method is to refine the data rather than enhance the algorithm. Two measurement conditions are compared until PRPD pattern saturation is achieved: one-minute and one-hour durations. The PD data specifically target three void types located at different positions within the epoxy material. The aim is to evaluate how the presence of weak PDs at the PD extinction voltage (PDEV) influences defect recognition accuracy. This research sheds light on the potential implications of neglecting the significance of weak PD signals in defect detection. A convolutional neural network (CNN) model is trained using PRPD data recorded at the repetitive PD inception voltage (RPDIV) and tested using the new PRPD data from both conditions recorded from a lower PDIV to a PDEV. The trained CNN model achieves a defect recognition accuracy of 100% for a one-hour duration, highlighting the importance of not neglecting weak PD signals. This emphasizes the significance of extended measurement duration and pattern saturation in capturing and analyzing weak PD signals for an improved defect recognition. This study contributes to the advancement of practical applications by understanding the behavior of the epoxy material and enhancing defect detection techniques.

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Section: Introductionmentioning

confidence: 99%