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Volumn , Issue , 2014, Pages 803-807

Power quality disturbances segmentation based on wavelet decomposition and adaptive thresholds

Author keywords

Adaptive Threshold; Power Quality; Signal Segmentation; Wavelet Transform

Indexed keywords

POWER QUALITY; SIGNAL PROCESSING; WAVELET DECOMPOSITION; WAVELET TRANSFORMS;

EID: 84904332389     PISSN: 15406008     EISSN: 21640610     Source Type: Conference Proceeding    
DOI: 10.1109/ICHQP.2014.6842906     Document Type: Conference Paper
Times cited : (3)

References (8)
  • 4
    • 78650180946 scopus 로고    scopus 로고
    • A new and fast method for detection of power quality disturbances using wavelet transform
    • A. Mahmoudi.; S. H. Hosseinian and A. Doroudi, "A new and fast method for detection of power quality disturbances using wavelet transform," In: 2010 1st Power Quality Conference, pp. 1-6.
    • (2010) 1st Power Quality Conference , pp. 1-6
    • Mahmoudi, A.1    Hosseinian, S.H.2    Doroudi, A.3
  • 5
    • 58349095738 scopus 로고    scopus 로고
    • An expert system based on s-transform and neural network for automatic classification of power quality disturbances
    • M. Uyar, S. Yildirim and M. T. Gencoglu, "An expert system based on s-transform and neural network for automatic classification of power quality disturbances", Expert Systems with Applications, vol. 36, pp. 5962-5975, 2009.
    • (2009) Expert Systems with Applications , vol.36 , pp. 5962-5975
    • Uyar, M.1    Yildirim, S.2    Gencoglu, M.T.3
  • 7
    • 70350129753 scopus 로고    scopus 로고
    • Wavelet entropy measure definition and its application for transmission line fault detection and identification
    • H. Zheng-you, C. Xiaoqing and L. Guoming, "Wavelet Entropy Measure Definition and Its Application for Transmission Line Fault Detection and Identification," In: 2006 International Conference on Power System Technology, pp. 1-5.
    • (2006) International Conference on Power System Technology , pp. 1-5
    • Zheng-You, H.1    Xiaoqing, C.2    Guoming, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.