DocumentCode :
3158485
Title :
Detection and classification of voltage sag causes based on empirical mode decomposition
Author :
Manjula, M. ; Sarma, A.V.R.S. ; Mishra, Sukumar
Author_Institution :
Osmania Univ., Hyderabad, India
fYear :
2011
fDate :
16-18 Dec. 2011
Firstpage :
1
Lastpage :
5
Abstract :
Voltage sag is one of the common cause for mal operation of most the equipment. This paper presents an algorithm to detect and classify voltage sag causes based on Empirical Mode Decomposition (EMD). EMD is a method which decomposes a non stationary signal into different mono component signals. These mono component signals are called Intrinsic Mode Functions (IMFs). The magnitude plot of the Hilbert Transform (HT) of the first IMF has the ability to detect the disturbance. The features of the first three IMFs of each disturbance are used as inputs to Probabilistic Neural Network (PNN) for identification of voltage sag causes. Three voltage sag causes are (i) Fault induced voltage sag (ii) Starting of induction motor and (iii) Three phase transformer energization. A comparison is made with wavelet transform. Simulation results show that the EMD method is more efficient in classifying the voltage sag causes.
Keywords :
Hilbert transforms; induction motors; neural nets; power engineering computing; power supply quality; power transformers; wavelet transforms; EMD method; HT; Hilbert transform; IMF; PNN; empirical mode decomposition; equipment maloperation; fault-induced voltage sag; intrinsic mode functions; monocomponent signals; nonstationary signal decomposition; probabilistic neural network; three-phase transformer energization; voltage sag classification; voltage sag detection; wavelet transform; Feature extraction; Induction motors; Power quality; Probabilistic logic; Voltage fluctuations; Wavelet transforms; Empirical mode decomposition; hilbert transform; intrinsic mode functions; probabilistic neural network; voltage sag causes; wavelet transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
India Conference (INDICON), 2011 Annual IEEE
Conference_Location :
Hyderabad
Print_ISBN :
978-1-4577-1110-7
Type :
conf
DOI :
10.1109/INDCON.2011.6139581
Filename :
6139581
Link To Document :
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