| 2 | Design and evaluation of a maize monitoring system for precision planting显示文摘To increase the accuracy and real-time performance of on-line assessment of maize planting,a CAN bus based maize monitoring system for precision planting was designed and tested both in laboratory and field.The system was mainly comprised of:(a)seeding rate sensors based on opposite-type infrared photoelectric cell for counting the dropping seeds;(b)a decimeter GPS receiver for acquiring planter position and operation speed;(c)a vehicle monitoring terminal based on ARM Cotex-m4 core chip to acquire and process the whole-system data;(d)a touchscreen monitor to display the planter performance for the operator;and(e)a buzzer alarm to sound a warning when skip and double seeding happened.Taking the applicability,dependability and feasibility of the monitoring system into consideration,the opposite-type infrared photoelectric sensors were selected and their deployment strategies in the 6-port seed tube were analyzed.To decrease the average response time,a distributed information communication structure was adopted.In this information communication mode,collectors were designed for each individual sensor and communicated with sensors through two-wire CAN bus.A sensor together with the designed collector is called a sensor node,and each of them worked individually and took the responsibility for acquiring,processing,and transiting the on-going information.Laboratory test results showed that the random error distribution was approximately normal,and by liner analysis,the system observed value and the true value had as a liner relationship with coefficient of determination R^(2)=0.9991.Series of field tests showed that the seeding rate maximum relative error of the 6-port seed tube was 2.92%,and the maximum root mean square error(RMSE)was about 1.64%.The monitoring system,including sensor nodes,vehicle monitoring terminal and a touch-screen monitor,was proved to be dependable and stable with more than 14 d of continuous experiments in field. | Yanxin Yin Liping Chen Zhijun Meng Bin Li Changhai Luo Weiqiang Fu Hebo Mei Wuchang Qin | 2018 | International Journal of Agricultural and Biological Engineering2018，11，4： | 0 |
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