Discriminating Feed Rate of Combine Harvester by Using Association Rule Mining

The feed rate is an important evaluation index of combine harvester performance. quick identification the amount that enters during harvesting great significance for efficiency and operational quality harvester. To address this issue, study proposes a discrimination method based on association rule mining. A self-designed data acquisition system was designed, taking wheat as object, collected seven speed signals three torque when 6 kg/s~8 kg/s, 8 kg/s~10 10 kg/s~11 respectively. time series were discretized so to facilitate construction transaction sets. Then, rules in constructed set mined by FP-Growth, with weak or no correlation increase filtered using min-support, min-confidence, min-lift 1.3, 0.8, 3, respectively, obtain strong rules. classifiers. test results showed accuracy classifier kg/s rates 100 %, 96 98.7 Research can provide basis adjustment working state