With no zero-crossing characteristic, DC arc is difficult to extinguish by itself, and is inclined to cause electrical fire, threatening the safety of DC power distribution. The differences of arc characteristics under different voltages are analyzed by building an experimental platform for arc simulation, collecting arc signals under different voltages, and studying the characteristics of arc resistance and voltage. Based on the preferred value of the nominal voltage of the medium and low voltage DC distribution network in GB/T 35727—2017, the differences of the detected arc characteristics at three different voltage levels of 220 V, 750 V and 1500 V are studied, with the frequency domain characteristics such as Fourier transform, wavelet transform and singular value decomposition, as well as the time domain characteristics such as maximum, minimum, average and standard deviation compared, to obtain high-quality criteria for arc detection at different voltage levels, which proves that the frequency domain characteristics at different times are applicable to varied voltage levels. Combined with the neural network model, the arc detection algorithm suitable for 750 V system is designed, and the detection accuracy of the algorithm is 99.12%.