E3S Web Conf.
Volume 175, 2020XIII International Scientific and Practical Conference “State and Prospects for the Development of Agribusiness – INTERAGROMASH 2020”
|Number of page(s)||10|
|Published online||29 June 2020|
Improving the adjustment process of the technological parameters of agricultural machines
Don State Technical University, 1, Gagarina sq, 344003, Rostov-on-Don, Russia
* Corresponding author: firstname.lastname@example.org
In the process of performing technological operations, any agricultural machinery is exposed to a large number of changing factors. The result of technological operations, in most cases, is performed by an organoleptic method, which is characterized by a significant error (up to 40%) and labor input. Given the complexity and labor input of assessing the performance quality indicators of agricultural machines, even partial automation of this process in practice gives a tangible (tens of percent) economic effect and becomes the basis for the formation of digital agriculture. We have analyzed existing methods for monitoring the quality indicators of technological operations using the example of the grain harvesting process. In particular, the possibilities of improving the methods for monitoring the performance quality indicators of a combine harvester have been considered. The correlation between the external signs of the quality violation of the technological process (losses) and adjustable parameters has been demonstrated using the example of a combine harvester thresher. A technique for adjusting the technological settings of the combine on the basis of electronic means of grain losses control, as an element of introducing the Precision Farming technologies, has been developed.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.