Arc Fault Detection in Low Voltage DC System Using Wavelet Transform

The main objective of this paper to detect an arc fault occurring in a low voltage dc system using wavelet transform. As we know arc faults plays a major role in an electrical power system, due to this fire, shocking hazard or system failure of the electrical system or equipment can be happen. It’s very challenging to detect arc fault in a dc system because unlike a ac system a dc system cannot be based on zero crossing value rely on Fourier transform which is the pattern recognition of the signal either in time domain or frequency domain which cannot gives a accurate results. So for this deficiency a new technique called wavelet transform (WT) is used to detect fault in electrical system. Wavelet transform is based on multi resolution analogy in which signal can be tested in both time and frequency domain. This time-frequency domain wave shape determining method is very useful in ac as well as in dc, which gives approximate value of the fault occurring in the system. The process of detecting an arc fault involves signal analysis and then feature identification. The focus of this paper is on the former. Simulation models are synthesized to study the theoretical results of the proposed methodology and compare with the previous results analysis on arcing faults. A practical approach is also mentioned in it.