Muzamir Isa, Mohamad Nur Khairul Hafizi Rohani, Faizah Abu Bakar

Partial Discharge Recognition Using Artificial Neural Network

• Broschiertes Buch

Produktbeschreibung

Partial discharge (PD) seriously affects the reliability of the distribution system due to electrical stress and the duration of the installation. Recent technology advance brings the analysis of the PD act as the guideline and maintenance strategy can be carried out when a parameter exceeding the predefined level. This book presents an artificial neural network (ANN) modelling in detecting the PD signal. PD signals are generated from experimental laboratory and simulation by using electromagnetic transient program-alternative transient program (EMTP-ATP). There are two analyses are carried out; classification and de-noising of PD signal. The first analysis used the straight forward procedure in PD signal classification. Second analysis presents the de-noising of PD signal using three different techniques; ANN, fast Fourier transforms (FFT) and discrete wavelet transform (DWT). The de-noising algorithm is implemented to discover a clean PD signal from disrupted signal. The performance of the de-nosing techniques was evaluated by comparing the signal to noise ratio (SNR). The result of this analysis shows ANN is the best de-noising technique compare to others.

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Produktdetails

• Verlag: LAP LAMBERT Academic Publishing
• Seitenzahl: 80
• Erscheinungstermin: 10. Juli 2020
• Englisch
• Abmessung: 220mm x 150mm x 5mm
• Gewicht: 137g
• ISBN-13: 9786202678742
• ISBN-10: 6202678747
• Artikelnr.: 62407328

Autorenporträt

Muzamir Isa was born in Padang Besar, Malaysia in 1979. He received the B.Eng. in electrical engineering (with Honors) from the Universiti Teknologi Malaysia (UTM), Malaysia in 2001, the M.Sc. from the Universiti Tun Hussein Onn Malaysia (UTHM), Malaysia in 2004 and received the Ph.D degree from Aalto University, Helsinki, Finland in 2012.