Research on Transmission Line Fault Detection Method based on M-Apriori Algorithm

Ensuring the stability of transmission line is the key to ensure the normal operation of the whole power grid system. In order to realize intelligent detection of transmission line fault and big data analysis, a transmission line fault detection method based on improved M-Apriori optimization algorithm is proposed. Firstly, the transmission line fault detection index system is constructed, and the M-Apriori algorithm is optimized and improved based on the traditional Apriori algorithm. In order to verify the comprehensive performance of the algorithm, five common transmission line fault types are selected for simulation this time, and the execution time of Apriori and M-Apriori algorithms are compared and analyzed respectively when the number of things with the same support is different, the system degree is different, and the number of things is the same. The simulation results show that the improved M-apriori has better algorithm efficiency, better recognition rate than BP neural network algorithm, and can realize the automatic monitoring of transmission line fault.