Development of automatic wheat seeding quantity control system based on Doppler radar speed measurement

With advancements in agricultural technology, the full mechanization of rice straw wheat planting has been achieved. However, issues such as missed seeding, uneven row spacing, and poor uniformity of row replenishment often arise due to wheel slippage in wheeled wheat seeders. These problems manual replanting after emergence, reducing efficiency and increasing labor costs. To address these challenges, a speed-adaptive wheat seeding control system based on speed radar was developed. This system comprises a pneumatic wheat seeding device, an automatic speed-following control system, a human-machine interface, and a stepper motor. Leveraging an embedded controller, the system dynamically adjusts motor speed based on real-time forward speed to ensure precise seeding. Using fuzzy PID control, the system dynamically adjusts motor speed, achieving row spacing consistency below 3.9 % and seeding stability within 1.3 %, even at varying speeds. This system addresses critical challenges in precision agriculture, enhancing planting efficiency and reducing labor costs. This innovation enhances planting efficiency, reduces labor costs, and ensures adaptability to varying tractor speeds, meeting the precision requirements of wheat planting. • An automatic speed-following control system for wheat displacement using an embedded system and air-assisted supply. • Mathematical modelling of the relationship between agronomic parameters, motor speed and forward speed of the unit. • The mathematical model was optimized using fuzzy PID control algorithm. • The automatic speed control system is able to meet the agronomic requirements of the rice stubble-wheat cropping pattern.

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Publication Details

Journal
Artificial Intelligence in Agriculture
Published
2024-12-24
DOI
https://doi.org/10.1016/j.aiia.2024.12.001
Citations
4
Primary Topic
Soil Mechanics and Vehicle Dynamics
Type
article
Field-Weighted Citation Impact
1.04
Controls
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article

Development of automatic wheat seeding quantity control system based on Doppler radar speed measurement

Ce Liu, Weiwei Wang, Liqing Chen, Lu Liu et al.
4 citations
Artificial Intelligence in Agriculture
Soil Mechanics and Vehicle Dynamics
1.04
article

Development of automatic wheat seeding quantity control system based on Doppler radar speed measurement

Ce Liu, Weiwei Wang, Liqing Chen, Lu Liu, Wenbing Shi, Yuwei Wang
article en
4 citations

Abstract

With advancements in agricultural technology, the full mechanization of rice straw wheat planting has been achieved. However, issues such as missed seeding, uneven row spacing, and poor uniformity of row replenishment often arise due to wheel slippage in wheeled wheat seeders. These problems manual replanting after emergence, reducing efficiency and increasing labor costs. To address these challenges, a speed-adaptive wheat seeding control system based on speed radar was developed. This system comprises a pneumatic wheat seeding device, an automatic speed-following control system, a human-machine interface, and a stepper motor. Leveraging an embedded controller, the system dynamically adjusts motor speed based on real-time forward speed to ensure precise seeding. Using fuzzy PID control, the system dynamically adjusts motor speed, achieving row spacing consistency below 3.9 % and seeding stability within 1.3 %, even at varying speeds. This system addresses critical challenges in precision agriculture, enhancing planting efficiency and reducing labor costs. This innovation enhances planting efficiency, reduces labor costs, and ensures adaptability to varying tractor speeds, meeting the precision requirements of wheat planting. • An automatic speed-following control system for wheat displacement using an embedded system and air-assisted supply. • Mathematical modelling of the relationship between agronomic parameters, motor speed and forward speed of the unit. • The mathematical model was optimized using fuzzy PID control algorithm. • The automatic speed control system is able to meet the agronomic requirements of the rice stubble-wheat cropping pattern.

Artificial Intelligence in AgricultureVol. 15(1)
Anhui Agricultural University (CN)
Affordable and clean energy
Openalex Percentile: Top 24%
Soil Mechanics and Vehicle Dynamics
1.04
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