TY - GEN
T1 - Cast-resin dry-type transformer partial discharge signal analysis using spectral correlated empirical mode decomposition method
AU - Tang, Ya Wen
AU - Su, Ching Chau
AU - Tai, Cheng Chi
AU - Chen, Jiann Fuh
PY - 2013/8/23
Y1 - 2013/8/23
N2 - Cast-resin dry-type transformers are widely used in high power applications. Long-term operation increases the extent of damages if no proper safeguards are taken. The major cause of transformer damages is insulation deterioration, which is correlated with partial discharge (PD) occurrence. Recent PD research studies have focused on how to locate the PD occurrence and improve the accuracy of PD detection. The best way to improve the accuracy is to locate the elements affected by the PD. Based on the empirical mode decomposition (EMD) method, the correlated-EMD method (CEMD) was proposed to filter out the uncorrelated intrinsic-mode functions (IMFs), and reveal a PD-affected signal as the filtered result. The spectral CEMD method proposed herein improves the screening process especially for those IMFs with low-frequency vibrations. The results of the spectral CEMD method showed the clearer pattern for PD detection than that of the CEMD method. This algorithm can provide useful information for PD analyses and improve PD identification.
AB - Cast-resin dry-type transformers are widely used in high power applications. Long-term operation increases the extent of damages if no proper safeguards are taken. The major cause of transformer damages is insulation deterioration, which is correlated with partial discharge (PD) occurrence. Recent PD research studies have focused on how to locate the PD occurrence and improve the accuracy of PD detection. The best way to improve the accuracy is to locate the elements affected by the PD. Based on the empirical mode decomposition (EMD) method, the correlated-EMD method (CEMD) was proposed to filter out the uncorrelated intrinsic-mode functions (IMFs), and reveal a PD-affected signal as the filtered result. The spectral CEMD method proposed herein improves the screening process especially for those IMFs with low-frequency vibrations. The results of the spectral CEMD method showed the clearer pattern for PD detection than that of the CEMD method. This algorithm can provide useful information for PD analyses and improve PD identification.
UR - http://www.scopus.com/inward/record.url?scp=84882267517&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84882267517&partnerID=8YFLogxK
U2 - 10.1109/I2MTC.2013.6555472
DO - 10.1109/I2MTC.2013.6555472
M3 - Conference contribution
AN - SCOPUS:84882267517
SN - 9781467346221
T3 - Conference Record - IEEE Instrumentation and Measurement Technology Conference
SP - 523
EP - 527
BT - 2013 IEEE International Instrumentation and Measurement Technology Conference
T2 - 2013 IEEE International Instrumentation and Measurement Technology Conference: Instrumentation and Measurement for Life, I2MTC 2013
Y2 - 6 May 2013 through 9 May 2013
ER -