Mathematical Modelling of the Process of Renewal of the Fleet of Combine Harvesters

Bulgakov, Volodymyr; Аdаmchuk, Valerii; Arak, Margus; Olt, Jüri

doi:10.1016/j.aaspro.2015.12.027

Cited by 10 publications

(6 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among the technical reasons for reducing the performance of technological processes of combine harvesting, it is possible to single out the indicators related to the aspects of managing the technical condition of combine harvesters -repair and maintenance of machines [4][5][6]. Maintenance is an integral part of the operation system of machines, without which it is impossible to ensure their proper functioning throughout the service life of the machine.…”

Section: Research Status and Work Relevancementioning

confidence: 99%

Performance analysis of the process of combine harvesting of grain crops

et al. 2020

View full text Add to dashboard Cite

The effectiveness of combine harvesting processes is one of the most important indicators of planting enterprises, as it largely determines the efficiency of the entire organization. One of the problems in assessing the effectiveness of combine harvesters is the determination of the planned performance of machines with rated productivity. The paper considers approaches to determining the planned and actual performance of the processes of combine harvesting of grain crops. The factors affecting the decrease in the performance of combines have been studied. The analysis of data on the wheat harvesting process in local organizations of the South of Russia during 2014-2019 has been carried out. The results of calculating the planned and actual performance of wheat harvesting processes in these farms are presented.

show abstract

Section: Research Status and Work Relevancementioning

confidence: 99%

Performance analysis of the process of combine harvesting of grain crops

et al. 2020

View full text Add to dashboard Cite

show abstract

“…To search for the local minimum point, it is possible to use various optimization methods for the function of many variables. However, the specifics of the subject area impose the following restrictions: the terrain of the objective function is unknown, which makes it difficult to choose the most suitable optimization method; the harvesting conditions imply minimizing the number of iterations of optimization algorithms [11,12]. Therefore, to search for the points of local minima of the objective function, it is advisable to use the coordinate-wise descent method (Gauss's method) with some changes.…”

Section: Figmentioning

confidence: 99%

Improving the adjustment process of the technological parameters of agricultural machines

et al. 2020

View full text Add to dashboard Cite

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.

show abstract

“…Sea buck-thorn blooms in April-May; fruits ripen in July-August, sometimes at the end of June, remaining until the spring of the following year. The flowering duration is only 10-12 days [1,2].…”

Section: Introductionmentioning

confidence: 99%

Monitoring the Gene Pool of Sea-Buckthorn Cultivars (Hippophae Rhamnoides L.) for Breeding in the Conditions of the Nonchernozem Zone of Russia

Sorokopudov,

Zubik,

Simahin

et al. 2023

BIO Web Conf.

View full text Add to dashboard Cite

The research materials of Hippophaerhamnoides L. cultivars in the Nonchernozem zone of Russia are presented in this paper. The issues of phenology, productivity and resistance to ecological factors of the environment are considered. It was found that the phenophases of the beginning of vegetation, ripening of berries, leaf fall, duration of fruiting and vegetation have a slight variation, i.e., the cultivars slightly differ in the calendar phenophase onset dates. At the beginning of the growing season, this phenophase can be divided into 3 groups: early (18-22 days – Botanicheskaya Aromatnaya, Botanicheskaya and Perchik), medium (23-26 Moskovskaya Ananasnaya, Botanicheskaya Lyubitelskaya, Gibrid Perchika and Lomonosov) and later (27-30 – Podarok Sadu and Vorobyovskaya) bud breaks. There are 3 groups of cultivars according to the duration of vegetation: short (171-174 days – Podarok Sadu, Moskovskaya Ananasnaya and Botanicheskaya), medium (175-178 – Botanicheskaya Lyubitelskaya, Gibrid Perchika, Vorobyevskaya, Otradnaya and Lomonosovskaya) and long (179-182 – Botanicheskaya Aromatnaya). The analysis of the sea-buckthorn cultivars yield showed that, on the average, it amounted to 85±21 c/ha with the variation of 88% over the years. The cultivars with the highest yield in c/ha units were identified as Botanicheskaya (109.48±30.06), Moskovskaya Ananasnaya (121.24±28.46) and Botanicheskaya Aromatnaya (151.74±34.58); the lowest in yield cultivars were Otradnaya (32.98±6.24), Podarok Sadu (52.48±14.72) and Gibrid Perchika (64.24±17.50). It was revealed that the cultivars berry mass in different years has a weak (0-17%) and average (22-27%) variation. Cultivars Lomonosovskaya (0.51±0.0 g) and Vorobyevskaya (0.58±0.1 g) had small fruits. The most winter-hardy cultivars were identified as Moskovskaya Ananasnaya, Botanicheskaya Aromatnaya, Botanicheskaya Perchik, Botanicheskaya Lyubitelskaya and Lomonosovskaya.

show abstract

Mathematical Modelling of the Process of Renewal of the Fleet of Combine Harvesters

Cited by 10 publications

References 5 publications

Performance analysis of the process of combine harvesting of grain crops

Performance analysis of the process of combine harvesting of grain crops

Improving the adjustment process of the technological parameters of agricultural machines

Monitoring the Gene Pool of Sea-Buckthorn Cultivars (Hippophae Rhamnoides L.) for Breeding in the Conditions of the Nonchernozem Zone of Russia

Contact Info

Product

Resources

About