Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/10009005,
  title    = {Empirical Mode Decomposition with Wavelet Transform Based Analytic Signal for Power Quality Assessment},
  author    = {Sudipta Majumdar and  Amarendra Kumar Mishra},
  country   = {India},
  institution={Delhi Technological University},
  abstract  = {This paper proposes empirical mode decomposition
(EMD) together with wavelet transform (WT) based analytic signal
for power quality (PQ) events assessment. EMD decomposes the
complex signals into several intrinsic mode functions (IMF). As
the PQ events are non stationary, instantaneous parameters have
been calculated from these IMFs using analytic signal obtained
form WT. We obtained three parameters from IMFs and then used
KNN classifier for classification of PQ disturbance. We compared
the classification of proposed method for PQ events by obtaining
the features using Hilbert transform (HT) method. The classification
efficiency using WT based analytic method is 97.5% and using HT
based analytic signal is 95.5%.},
    journal   = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},  volume    = {12},
  number    = {4},
  year      = {2018},
  pages     = {329 - 334},
  ee        = {http://waset.org/publications/10009005},
  url       = {http://waset.org/Publications?p=136},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 136, 2018},
}