Research On Methods In The Recognition Of Arc-Fault Patterns

With the development of economy, various appliances of popularization and theemergence of new appliances, electrical fire frequency is more and more high, the damageis becoming more and bigger. Which series electric arc fault is a one of the importantreasons for the fires. And the protection of the traditional electrical short circuit fault andeffectively to ground fault protection, is in view of the large current over-current protection.Series and the characteristics of arc fault is small, usually less than the short-circuit current,and high temperature, short duration. So when arc fault occurs, the traditional over-currentprotection electric appliance is not effective on line protection. Therefore, the series of arcfault detection and recognition is very important.At present, the domestic study of low-voltage arc fault is still lack, the researchmethods are mainly based on the analysis of arc fault current and voltage waveformcharacteristics, using wavelet singularity detection, Fourier analysis, peak and slopeidentification arc fault. However, due to the diversity of the electrical equipment, make theload current and a fault current characteristic of the arc is very similar. In addition, mostscholars analyze the characteristics of arc fault current is used when a single load, the studyof mixed load. This paper set up the experimental platform of arc fault collection, collecteda variety of load in a separate operation and mixed operation, has not occurred and thecurrent signal of arc fault occurs.Analyzes the load when the normal operation of the current waveform and arc of thedifference of the current waveform. And then using Matlab software to current signal indiscrete Fourier analysis, extract load in normal and harmonic current signal in thepresence of arc, the two cases of harmonic comparative study, found that when arc faultoccurs, the load of the harmonic distortion has the certain regularity, this paper putsforward a kind of based on the harmonic coefficient of variation of arc fault patternrecognition method for the detection of arc fault provides a reliable reference basis.