Arc Fault and Flash Detection in Photovoltaic Systems Using Wavelet Transform and Support Vector Machines Conference Paper

abstract

• 2016 IEEE. Arc faults pose significant reliability and safety issues in today's photovoltaic (PV) systems. This paper presents an effective method based on wavelet transform and support vector machines (SVM) for detection of arc faults in DC PV systems. Because of its advantages in time-frequency signal processing, wavelet transform is applied to extract the characteristic features from system voltage/current signals. SVM is then used to identify arc faults. The performance of the proposed technique is compared with traditional Fourier transform based approaches.

name of conference

• 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC)

authors

• Balog, Robert

published proceedings

• 2016 IEEE 43RD PHOTOVOLTAIC SPECIALISTS CONFERENCE (PVSC)

author list (cited authors)

• Wang, Z., & Balog, R. S.

citation count

• 21

complete list of authors

• Wang, Zhan||Balog, Robert S

publication date

• June 2016

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Conference Record IEEE Photovoltaic Specialists Conference  Journal

Digital Object Identifier (DOI)

• 10.1109/pvsc.2016.7750271

International Standard Book Number (ISBN) 13

• 9781509027248

start page

• 3275

end page

• 3280

volume

• 2016-November

URL

• http://dx.doi.org/10.1109/pvsc.2016.7750271