A dynamic grain flow model for a mass flow yield sensor on a combine

Ryan Reinke, Harry Dankowicz, Jim Phelan, Wonmo Kang

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

A model is developed to describe the flow of grain through a clean grain elevator system on a combine in order to facilitate accurate mass flow rate estimation. The relationship between mass flow rate and impact force described by the model depends upon machine operational characteristics, mechanical interactions of the grain and the machine geometry, and material properties of the grain. The model was designed to be adaptable to varying grain conditions, such as those influenced by moisture content, by allowing free parameters of the model to be estimated through a nonlinear regression algorithm. Simulations were performed using discrete element modeling software and data was obtained from experiments conducted on a clean grain elevator system at the University of Kentucky Combine Yield Monitor Test Facility to determine the ability of the model to accurately estimate mass flow rate. The model estimated mass flow rate with a normalized root mean squared residual (NRMSR) less than 2% for discrete element modeling simulations. For experiments involving machine components, NRMSR values were less than 3% for corn at 14% moisture, less than 3% for corn at 21% moisture, and less than 5% for corn at 26% moisture.

Original languageEnglish (US)
Pages (from-to)732-749
Number of pages18
JournalPrecision Agriculture
Volume12
Issue number5
DOIs
StatePublished - Oct 2011
Externally publishedYes

Keywords

  • Discrete element modeling
  • Experiments
  • Flow sensor
  • Impact plate
  • Nonlinear regression

ASJC Scopus subject areas

  • General Agricultural and Biological Sciences

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