Optimization Algorithm of Association Rule Mining for EMU Operation and Maintenance Efficiency

With the increase of EMU operation time and mileage, EMU operation and maintenance system has accumulated a large amount of data. Using the high-performance association rule mining algorithms to quickly find useful information from the EMU operation and maintenance data, is of significant importance for improving the operation and maintenance efficiency of the key components of the EMU. In the view of the characteristics of EMU operation and maintenance data—huge volume and low value density, we design the AMPHP algorithm based on the approximate minimal perfect Hash function. Compared with the traditional DHP algorithm, it can filter out all the infrequent item sets without additional database scanning. In order to break the limitation of the single machine algorithm and further improve the performance of the algorithm, we use the idea of SON algorithm for reference to parallelize the AMPHP algorithm and finally propose the AMPHP-SON algorithm. Some experiments have been performed on the operation and maintenance data of EMU traction motor. The experimental result shows that the AMPHP-SON algorithm has good time performance and the rules dug out can be effectively used to guide the optimization of the repair class and repair system of EMU, so as to improve the efficiency of EMU operation and maintenance.