Elimination of vibration noise from an impact-type grain mass flow sensor

Elimination of vibration noise from an impact-type grain mass flow sensor Intensive vibration caused by uneven field terrain and imbalance of working components in a combine harvester is commonly experienced by yield monitors, causing a significant influence on the performance of impact-type grain flow sensors. A yield monitor test stand was constructed based on a commercial combine harvester, and a method was developed to eliminate the effects of vibration disturbance on impact-type flow sensors. The vibration caused by combine harvesters was simulated well in the experiment, and moreover the actual grain flow rate could be adjusted and measured precisely by the weighing sensors fixed under the grain feed tank in real time. An impact-type grain flow sensor was manufactured using two parallel-beam load cells: one was impacted by the grain flow, and the other was applied as a reference beam that was only excited by the vibration of the sensor frame. A harmonic extraction method was introduced to exploit the essential characteristics involved in the collision process between the grain and the impact plate driven by the elevator paddles of the combine harvester. Then adaptive interference cancellation was utilized to eliminate the vibration noise from the measurement of the impact force of the grain flow according to data from the reference parallel-beam load cell. The experimental results showed that the relative error was less than 2.2 % when the reference parallel-beam load cell was used alone, and relative error was reduced further to less than 1.6 % when both the data from the reference load cell and the harmonic extraction method were applied. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Elimination of vibration noise from an impact-type grain mass flow sensor

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Springer US
Copyright © 2014 by Springer Science+Business Media New York
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
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