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Báo cáo hóa học: " Research Article Power Quality Analysis Using Bilinear Time-Frequency Distributions"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Power Quality Analysis Using Bilinear Time-Frequency Distributions | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 837360 18 pages doi 10.1155 2010 837360 Research Article Power Quality Analysis Using Bilinear Time-Frequency Distributions Abdul Rahim Abdullah1 and Ahmad Zuri Sha ameri2 1 Faculty of Electrical Engineering Technical university of Malaysia Malacca 76100 Malacca Malaysia 2 Faculty of Electrical Engineering Technical university of Malaysia 81310 Johor Malaysia Correspondence should be addressed to Abdul Rahim Abdullah abdulr@utem.edu.my Received 8 January 2010 Revised 4 June 2010 Accepted 8 December 2010 Academic Editor Ulrich Heute Copyright 2010 A. R. Abdullah and A. Z. Sha ameri. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Bilinear time-frequency distributions TFDs are powerful techniques that offer good time and frequency resolution of timefrequency representation TFR . It is very appropriate to analyze power quality signals which consist of nonstationary and multifrequency components. However the TFDs suffer from interference because of cross-terms. Many TFDs have been implemented and there is no fixed window or kernel that can remove the cross-terms for all types of signals. In this paper the bilinear TFDs are implemented to analyze power quality signals such as smooth-windowed Wigner-Ville distribution SWWVD Choi-Williams distribution CWD B-distribution BD and modified B-distribution MBD . The power quality signals focused are swell sag interruption harmonic interharmonic and transient based on IEEE Std 1159-1995. Aset of performance measures is defined and used to compare the TFRs. It shows that SWWVD presents the best performance and is selected for power quality signal analysis. Thus an adaptive optimal kernel SWWVD is designed to determine the separable kernel automatically from the input .