College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang City, China.
PLoS One. 2021 Jul 15;16(7):e0254544. doi: 10.1371/journal.pone.0254544. eCollection 2021.
To realize the regulation of the position of corn seed planting in precision farming, an intelligent monitoring system is designed for corn seeding based on machine vision and the Genetic Algorithm-optimized Back Propagation (GABP) algorithm.
Based on the research on precision positioning seeding technology, comprehensive application of sensors, Proportional Integral Derivative (PID) controllers, and other technologies, combined with modern optimization algorithms, the online dynamic calibration controls of line spacing and plant spacing are implemented. Based on the machine vision and GABP algorithm, a test platform for the seeding effect detection system is designed to provide a reference for further precision seeding operations. GA can obtain better initial network weights and thresholds and find the optimal individual through selection, crossover, and mutation operations; that is, the optimal initial weight of the Back Propagation (BP) neural network. Field experiments verify the seeding performance of the precision corn planter and the accuracy of the seeding monitoring system.
The intelligent corn seeder designed based on precision positioning seeding technology can reduce the seeding rate of the seeder and ensure the stability of the seed spacing effectively. Based on the machine vision and GABP algorithm, the seeding effect detection system can provide a reference for the further realization of precision seeding operations.
为实现精量播种中玉米播种位置的调控,设计了一种基于机器视觉和遗传算法-反向传播(GABP)算法的玉米播种智能监测系统。
在精确定位播种技术研究的基础上,综合应用传感器、比例积分微分(PID)控制器等技术,结合现代优化算法,实现了行间距和株距的在线动态校准控制。基于机器视觉和 GABP 算法,设计了播种效果检测系统的测试平台,为进一步实现精量播种作业提供参考。GA 可以通过选择、交叉和变异操作获得更好的初始网络权重和阈值,并找到最优个体,即反向传播(BP)神经网络的最优初始权重。田间试验验证了精密玉米播种机的播种性能和播种监测系统的准确性。
基于精确定位播种技术设计的智能玉米播种机能有效降低播种机的播种率,保证株距的稳定性。基于机器视觉和 GABP 算法的播种效果检测系统可以为进一步实现精量播种作业提供参考。