Search

ABSTRACT China's socialized service industry of agricultural machinery emerged as the times required, which resolved the institutional contradiction between small farm households and large-scale agriculture. However, as cross-operation harvesters are still monitored based on phone calls, the monitoring efficiency and real-time performance are relatively poor. To improve the dynamic monitoring accuracy of harvester working areas, we proposed a working progress monitoring method based on harvester traveling trajectory and header status identification. The position and gap bridge angle information of harvesters was synchronously acquired in real-time. The height of the header above ground was calculated to determine whether the harvester was harvesting on a valid trajectory. Finally, the valid trajectory of the harvester was selected for area calculation. Field experiments showed that the header heights at the working and non-working tracing points collected by the system were discretely distributed at intervals of [0m, 0.5m] and (0.5m, 2m), respectively. The working progress monitoring algorithm proposed in this paper effectively improved the monitoring accuracy of harvester working areas. The mean error between the working areas calculated with identifying the header status and the actual cultivated land area in the five test plots was 0.09 hm2, with a mean error rate of 3.10%, 8.59% lower than that without identifying the harvester header status.