Hybrid signal processing and machine intelligence techniques for detection, quantification and classification of power quality disturbances

Engineering Applications of Artificial Intelligence

Volumn 22, Issue 3, 2009, Pages 442-454

  Panigrahi, B K ^a   Dash, P K ^b   Reddy, J B V ^c  

^a INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

^b Centre for Research in Electrical Sciences Bhubaneswar   (India)

^c DEPARTMENT OF SCIENCE AND TECHNOLOGY   (India)

Author keywords

Feature extraction; Multi class pattern recognition; Power quality disturbances S transform; Support vector machine; Wavelet transform

Indexed keywords

AUTOMATIC INDEXING; ELECTRIC MEASURING INSTRUMENTS; ELECTRIC NETWORK ANALYSIS; FOURIER TRANSFORMS; IMAGE RETRIEVAL; POWER QUALITY; SETTLING TANKS; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES; WAVELET TRANSFORMS;

ADVANCED SIGNAL PROCESSING; AUTOMATIC CLASSIFICATIONS; COMPUTATION TIME; DISTURBANCE SIGNALS; HYBRID SIGNAL PROCESSING; MACHINE INTELLIGENCES; MEMORY SPACES; MULTI-CLASS PATTERN RECOGNITION; POWER QUALITY DISTURBANCES S-TRANSFORM; POWER SYSTEM DISTURBANCES; SIMULATION RESULTS; SUPPORT VECTOR MACHINE; TIME-FREQUENCY RESOLUTIONS;

FEATURE EXTRACTION;

EID: 61349148635     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2008.10.003     Document Type: Article

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