TY - GEN
T1 - Study on Keypoint Extraction Method of Phase-Resolved Partial Discharge Pattern in Power Transformer
AU - Wang, Yan Bo
AU - Chang, Ding Ge
AU - Shao, Xian Jun
AU - Qin, Shao Rui
AU - Chen, Yu Lun
AU - Zhang, Guan Jun
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - During the manufacture and installation of power transformers, or after long-term operation, there may be various partial discharge (PD) sources inside the power transformer. In order to accurately assess the insulation state, it requires accurate measurement and diagnostics of type and location of PD source. Therefore, it is necessary to find an accurate method to extract effective features from phase-resolved partial discharge (PRPD) patterns, which can effectively characterize the PD type. In this paper, four keypoint extraction algorithms (the scale invariant feature transform (SIFT), the speeded up robust features (SURF), oriented fast and rotated brief (ORB) and BRISK methods) are introduced. For different types of PDs, different methods were used to extract a fixed number of key points. Then, the key points of the PRPD pattern of same defect type were matched. Thus, keypoint extraction methods were compared according to the degree of matching. According to the matching results, the ORB algorithm and the SURF algorithm have better performance, and the SIFT has the worst result.
AB - During the manufacture and installation of power transformers, or after long-term operation, there may be various partial discharge (PD) sources inside the power transformer. In order to accurately assess the insulation state, it requires accurate measurement and diagnostics of type and location of PD source. Therefore, it is necessary to find an accurate method to extract effective features from phase-resolved partial discharge (PRPD) patterns, which can effectively characterize the PD type. In this paper, four keypoint extraction algorithms (the scale invariant feature transform (SIFT), the speeded up robust features (SURF), oriented fast and rotated brief (ORB) and BRISK methods) are introduced. For different types of PDs, different methods were used to extract a fixed number of key points. Then, the key points of the PRPD pattern of same defect type were matched. Thus, keypoint extraction methods were compared according to the degree of matching. According to the matching results, the ORB algorithm and the SURF algorithm have better performance, and the SIFT has the worst result.
UR - https://www.scopus.com/pages/publications/85081642906
U2 - 10.1109/CEIDP47102.2019.9009709
DO - 10.1109/CEIDP47102.2019.9009709
M3 - 会议稿件
AN - SCOPUS:85081642906
T3 - Annual Report - Conference on Electrical Insulation and Dielectric Phenomena, CEIDP
SP - 295
EP - 298
BT - 2019 IEEE Conference on Electrical Insulation and Dielectric Phenomena, CEIDP 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Conference on Electrical Insulation and Dielectric Phenomena, CEIDP 2019
Y2 - 20 October 2019 through 23 October 2019
ER -