TAILIEUCHUNG - Báo cáo hóa học: " Research Article Detection of Disturbances in Voltage Signals for Power Quality Analysis Using HOS"

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 Detection of Disturbances in Voltage Signals for Power Quality Analysis Using HOS | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 59786 13 pages doi 2007 59786 Research Article Detection of Disturbances in Voltage Signals for Power Quality Analysis Using HOS Moises V. Ribeiro 1 Cristiano Augusto G. Marques 1 Carlos A. Duque 1 Augusto S. Cerqueira 1 and Josts Luiz R. Pereira2 1 Department of Electrical Circuit Federal University ofJuiz de Fora 36 036 330 Juiz de Fora MG Brazil 2 Department of Electrical Energy Federal University ofJuiz de Fora 36 036 330 Juiz de Fora MG Brazil Received 1 May 2006 Accepted 4 February 2007 Recommended by M. Reza Iravani This paper outlines a higher-order statistics HOS -based technique for detecting abnormal conditions in voltage signals. The main advantage introduced by the proposed technique refers to its capability to detect voltage disturbances and their start and end points in a frame whose length corresponds to at least N 16 samples or 1 16 of the fundamental component if a sampling rate equal to fs 256 X 60 Hz is considered. This feature allows the detection of disturbances in submultiples or multiples of one-cycle fundamental component if an appropriate sampling rate is considered. From the computational results one can note that almost all abnormal and normal conditions are correctly detected if N s256 128 64 32 and 16 and the SNR is higher than 25 dB. In addition the proposed technique is compared to a root mean square rms -based technique which was recently developed to detect the presence of some voltage events as well as their sources in a frame whose length ranges from 1 8 up to one-cycle fundamental component. The numerical results reveal that the proposed technique shows an improved performance when applied not only to synthetic data but also to real one. Copyright 2007 Moises V. Ribeiro et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and .

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