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The physical characteristics of fault arc complex, and circuits in the presence of waveform and the fault arc is similar to the load, so the traditional method to detect arc fault error rate. This paper presents a multi sensor data fusion algorithm, is used to improve the detection accuracy of fault arc. The algorithm includes the adaptive weighted fusion algorithm and neural network fusion algorithm of data fusion, sensor signal acquisition of temperature sensor, sound sensor and arc light intensity sensor. The adaptive weighted fusion algorithm to overcome the uncertainty of single sensor, extract the fault arc characteristics of homogeneous sensor in the test sample, provide accurate data for neural network fusion algorithm; neural network fusion algorithm can adjust the weight of all kinds of heterogeneous sensors, so that the identification probability of fault arc more accurately. The experimental results show that, the algorithm can effectively extract the characteristics of fault arc, the identification accuracy of more than 98%, the fault arc detection and warning of high precision.

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