Design and experiment of seeding performance monitoring system for suction corn planter

Liu, Kun; Yi, Shujuan

doi:10.25165/j.ijabe.20191204.4185

Cited by 14 publications

(12 citation statements)

References 9 publications

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“…Among AI technologies, machine learning, computer vision, big data analysis, and cloud computing are the most widely used ones. As an important food crop and cash crop in China, corn is widely distributed and covers the main food-producing areas in China [3][4][5]. Therefore, research on corn planting is of great significance to the development of primary and secondary industries in China.…”

Section: Introductionmentioning

confidence: 99%

Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning

Sang

et al. 2021

PLoS ONE

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Objective 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. Methods 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. Results 1. The deviation between the average value of the six precision positioning seeding experiments of corn under the random disturbance signal and the ideal value of the distance is less than or equal to 0.5 cm; the deviation between the average value of the six precision positioning seeding experiments of corn under the sine wave disturbance signal (1 Hz) is less than or equal to 0.4 cm; the qualified rate of grain distance reaches 100%. 2. The precision control index, replay index, and missed index of the designed corn precision seeding intelligent control system have all reached the national standard. During the operation of the seeder, an alarm of the seeder leaking occurred, and the buzzer sounded and the screen displayed 100 times each; therefore, the reliability of the alarm system is 100%. Conclusion 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.

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Section: Introductionmentioning

confidence: 99%

Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning

Sang

et al. 2021

PLoS ONE

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“…Дотепер усі просапні сільськогосподарські машинно-тракторні агрегати використовували і нині використовують у симетричному варіанті [9,10] Під впливом зазначених зовнішніх сил розглядуваний посівний машинно-тракторний агрегат (колісний трактор разом із задньонавісною просапною сівалкою) повертається у рухомій системі координат YOX на кут ϕ, а його центр мас (точка S) зміщується у поперечному напрямку на величину, що визначається координатою X s .…”

Section: вісник аграрної наукиunclassified

Theoretical study of the stability of asymmetric movement sowing machine-tractor aggregate

Adamchuk,

Bulgakov,

Nadykto

et al. 2023

Visnyk agrarnoi nauky

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“…But the seeder is huge and expensive, which is not suitable for the domestic market [12][13][14] . In China, the combined suction hole type seed-metering device had been experimental research [15][16][17][18] . Bai et al [19] designed an air suction pressure precision seed-metering device.…”

Section: Introductionmentioning

confidence: 99%

Parameter optimization and experiment of the negative pressure precision seed-metering device for wheat

Feng,

Zhao,

et al. 2024

International Journal of Agricultural and Biological Engineering

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In order to ensure the most reasonable distribution of wheat seeds in the field to improve seeding quality and uniformity, a set of negative pressure precision seed-metering device was designed, which shares a hollow shaft. Every seedmetering device can sow two rows of wheat. By the STAR-CCM+, the analysis of nephogram, vectogram and streamline graph showed that more ideal structural parameters of the seed-metering device are 0.5 mm width of the slit sucking seed (WSS), 150-200 mm diameter of the seed-metering disc (DSD), 2.0 mm axial depth of air chamber in the seed-metering disc (ADS), and arcshaped cross-section shape of the ring groove sucking seed (CSGS). Single-factor test on the JPS-12 test-bed analyzed the influence of the CSGS, WSS, DSD, and ADS on the qualified index (I q ), multiple index (I mul ), miss index (I miss ) and coefficient of variation of qualified seed spacing (CV). Through the orthogonal on the JPS-12 test-bed, it is found that the influence of vacuum negative pressure and seed-metering device shaft speed is significant on the I q , I miss and I mul . Based on these, the structural parameters of the seed-metering device were optimized. The DSD is 180 mm, the WSS is 0.7 mm, the ADS is 2.5 mm, and the CSGS is arc-shaped. The optimization seed-metering device was tested on the JPS-12 test-bed. The I q is 86.66%, the I miss is 5.09%, the I mul is 8.25%, and the CV is 24.50%. These testing results fully coincide with the standard JB/T 10293-2013 Specifications of single seed drill (precision drill). The seed-metering device meets fully the requirements for wheat precision seeding.

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Design and experiment of seeding performance monitoring system for suction corn planter

Cited by 14 publications

References 9 publications

Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning

Designing an intelligent monitoring system for corn seeding by machine vision and Genetic Algorithm-optimized Back Propagation algorithm under precision positioning

Theoretical study of the stability of asymmetric movement sowing machine-tractor aggregate

Parameter optimization and experiment of the negative pressure precision seed-metering device for wheat

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