Degree Type

Thesis

Date of Award

2018

Degree Name

Master of Science

Department

Agricultural and Biosystems Engineering

Major

Agricultural and Biosystems Engineering

First Advisor

Matthew Darr

Abstract

This study focused on quantifying the engineering drivers for improving the accuracy of an optical beam-based yield monitor. The development of the single paddle test stand led to the quantification of the relationship between the output response of an optical beam-based mass flow sensor and a corresponding mass of grain traveling on an individual clean grain elevator paddle. The study optimized the design of the clean grain elevator paddle to reduce the variation in the output response from an optical beam-based mass flow sensor. The optimal location and adequate sampling frequency of the optical beam-based mass flow sensor, determined using the single paddle test stand, led to the development of two mass flow yield monitor algorithms. The study evaluated the two mass flow yield monitor algorithms against the Ag Leader and Raven Industries yield monitors. The results concluded that by applying a mass flow yield monitor algorithm utilizing a piecewise regression rather than a completely linear regression, a significant amount of error could be reduced across mass flow rates.

DOI

https://doi.org/10.31274/etd-180810-5999

Copyright Owner

Michael Hanigan

Language

en

File Format

application/pdf

File Size

101 pages

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