Detection of Small Current Fault Arc in Lightweight Network Based on Synthetic Time-frequency Distribution Graphs
In order to effectively solve the problem of arc fault detection,a method of low-current fault arc detection in lightweight networks based on time-frequency distribution graphs is proposed.An arc experiment was conducted based on related standard to collect arc experiment data,thereby constructing a training set and test set by convert-ing current data into synthetic time-frequency distribution graphs.STF-GhostNet model was used to identify arc fault and output the result.Experimental results show that the accuracy of arc fault detection using this method is about 94.1%,which is higher than the traditional BP model and AlexNet.
neural networktime-frequency analysisarc fault detectionsmall current arcSTF-GhostNet
NETL
NSTL
万方数据
