Identification of Low Voltage AC Series Arc Faults by using Kalman Filtering Algorithm
AbstractArc faults often occur in residential low voltage AC supply environment. It is dangerous because the sparks accompanying with arc faults may lead to electric fire even safety hazard. Effective methods of arc faults diagnosis in circuits are essential for safety interrupters in household. A novel method for low voltage AC series arc faults identification based on time-domain feature extraction by using Kalman filtering algorithm is proposed in this paper. This method monitors the instantaneous value of series current in circuits, calculates an elaborate pre-designed eigenvalue each power cycle by using Kalman filter with acquired current samples, and compares the eigenvalue with a reference value. Once the deviation between them exceeded a predefined threshold in continuous eight power cycles, the method reports an arc fault. Experimental research was studied in laboratory with typical electrical loads using the proposed arc faults identification method. Results show that it is applicable to detect arc faults within eight power cycles. The response time of the method could fit the minimum requirements of the standard UL1699.
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