Abstract
Russian and foreign literature on the development of diagnostic systems and scanning of objects using a vision system with deep machine learning programs has been analyzed during the study. The features of the technological process of feeding cattle have been studied. A system of non-contact assessment of the dry matter content/humidity of the components of the feed mixture of natural cultivation on the example of a corn silo using technical vision systems was proposed. A database of images of corn silage was collected and the dependences on the intensity of the reflecting light flux of the silage were revealed taking into account changes in humidity. The research was conducted in 2020 on the basis of the Federal Scientific Agroengineering Center VIM (FNAC VIM), using experimental equipment of the Institute of General Physics of the Russian Academy of Sciences named after A. M. Prokhorov and FNAC VIM. A stand with a technical vision system has been developed that allows to classify the components of a cattle feed mixture by color characteristics. The obtained dependences of the reflecting intensity of corn silage allow us to assert the prospect of using a vision system for express-evaluation of the quality indicators of feed mixture components. Taking into account the level of robotization of technological processes of feeding cattle, the problem of assessing the quality indicators (in particular, the dry matter/moisture content) of the components of a feed mixture is relevant.
Highlights
В ходе исследования проанализирована российская и зарубежная литература, посвященная разработке систем диагностики и сканирования объектов с использованием системы технического зрения с программами глубокого машинного обучения
Russian and foreign literature on the development of diagnostic systems and scanning of objects using a vision system with deep machine learning programs has been analyzed during the study
A stand with a technical vision system has been developed that allows to classify the components of a cattle feed mixture by color characteristics
Summary
В ходе исследования проанализирована российская и зарубежная литература, посвященная разработке систем диагностики и сканирования объектов с использованием системы технического зрения с программами глубокого машинного обучения. Предложена система бесконтактной оценки содержания сухого вещества/влажности компонентов кормовой смеси естественного выращивания на примере кукурузного силоса с применением систем технического зрения. Полученные зависимости отражающей интенсивности кукурузного силоса позволяют утверждать о перспективе применения системы технического зрения для экспресс-оценки качественных показателей компонентов кормовой смеси.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
