Design and Test on No-tillage Planter Reseeding System for Miss-seeding
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    Abstract:

    An adaptive miss-seeding reseed device of no-tillage planter was developed to solve miss-seeding problems when working, and the mathematical model of the reseed device driver was established to implement the simulation analysis on the dynamic response performance of the compensation system device. Through the reseeding control algorithm, the distance (S) of reseeding device to main seed-metering device and the height (H) of seed-metering device to ground were determined and the relationship curves among reseed-metering plate speed (n), the seeding machine moving speed (vm) and the seed distance(Ll) were achieved, which further achieved the self-adaption performance of the reseeding machine. The bench test results on reseeding detection accuracy showed that the miss-seeding detection accuracy was 93.23%, the rate of reseeding of the system was 95.11%, the actual reseeding rate of reseeding was 91.95%, the detection error rate was 3.16%, the reseeding success rate of the system was 96.38%, the actual reseeding success rate was 89.89%, and the detection error rate was 6.49%. The tests of quadratic orthogonal regression on the height (H) of seed-metering device to ground, the seed distance (Ll) and the seeding machine moving speed (vm) showed that the performance of the reseeding device was the best with the height (H) of seed-metering device to ground of 15.33cm, the seed distance (Ll) of 25.16cm and the seeding machine moving speed (vm) of 3.52km/h, and the reseeding success rate was 96.5%. The field test results on reseeding performance showed that the average seeding qualification rate was 98.72%, which had an increase of 4.56% at speed of 3km/h to 6km/h. The research effectively improved the seeding quality and also provided reference for further study on seeding performance improvement of no-tillage planter as well as the promotion of agriculture mechanization level with information technology.

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History
  • Received:April 16,2017
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  • Online: July 10,2017
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