<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The performance of grain combine harvesters is determined by three factors: threshing power, losses and fuel consumption. Loss can be reduced by separating processes and providing a suitable mathematical model for each of them by examining and measuring the factors influencing loss and optimizing their function. This model is then to be used for the purposes of controlling the system. An important process that has a significant impact on combine loss is the cleaning system. This study modelled and optimized the function of a cleaning system using response surface methodology (RSM). Feed rate, fan speed, and upper sieve opening were considered independent variables; the percentage of grain passage, content of materials-other-than-grains (MOG), and semi threshed cluster (s.t.c.) passing through the upper sieve were viewed as dependent variables. The results showed a significant effect of all three independent variables on the percentage of free grains with a probability level of 0.01. However, not all interactions were significant. Moreover, it was found that only mechanical factors had a significant effect on the percentage of s.t.c. passing, while fan speed and all interactions showed no significant effect. All three independent variables significantly affected the MOG content passing. An appropriate exponential model was found for all three dependent variables. Subsequently, the optimal conditions were determined for the maximum passage of free grains through the upper sieve and the minimum MOG at 3.33 kg·s<sup>−1</sup> feed rate, 742 rpm fan speed, and an upper sieve with 10 mm openings with a desirability of 0.84, based on RSM modelling.</p>
</abstract>

The performance of grain combine harvesters is determined by three factors: threshing power, losses and fuel consumption. Loss can be reduced by separating processes and providing a suitable mathematical model for each of them by examining and measuring the factors influencing loss and optimizing their function. This model is then to be used for the purposes of controlling the system. An important process that has a significant impact on combine loss is the cleaning system. This study modelled and optimized the function of a cleaning system using response surface methodology (RSM). Feed rate, fan speed, and upper sieve opening were considered independent variables; the percentage of grain passage, content of materials-other-than-grains (MOG), and semi threshed cluster (s.t.c.) passing through the upper sieve were viewed as dependent variables. The results showed a significant effect of all three independent variables on the percentage of free grains with a probability level of 0.01. However, not all interactions were significant. Moreover, it was found that only mechanical factors had a significant effect on the percentage of s.t.c. passing, while fan speed and all interactions showed no significant effect. All three independent variables significantly affected the MOG content passing. An appropriate exponential model was found for all three dependent variables. Subsequently, the optimal conditions were determined for the maximum passage of free grains through the upper sieve and the minimum MOG at 3.33 kg·s−1 feed rate, 742 rpm fan speed, and an upper sieve with 10 mm openings with a desirability of 0.84, based on RSM modelling.

Optimized Mathematical Model of a Grain Cleaning System Functioning in a Combine Harvester using Response Surface Methodology

Acta Technologica Agriculturae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The performance of grain combine harvesters is determined by three factors: threshing power, losses and fuel consumption. Loss can be reduced by separating...

Optimized Mathematical Model of a Grain Cleaning System Functioning in a Combine Harvester using Response Surface Methodology

Publicado en línea: 03 mar 2022

Páginas: 20 - 26

DOI: https://doi.org/10.2478/ata-2022-0004

Palabras clave
loss, performance, optimization, RSM, MOG

© 2022 Ali Mirzazadeh et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Optimized Mathematical Model of a Grain Cleaning System Functioning in a Combine Harvester using Response Surface Methodology

Publicado en línea: 03 mar 2022

Páginas: 20 - 26

DOI: https://doi.org/10.2478/ata-2022-0004

Palabras claveloss, performance, optimization, RSM, MOG

© 2022 Ali Mirzazadeh et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Palabras clave
loss, performance, optimization, RSM, MOG