Update of the technical equipment of the grain-harvesting complex

Many options have been developed for the implementation of the algorithm for updating the fleet of grain harvesters to date. In accordance with the yield and other indicators, recommendations for the formation and renewal of the harvester fleet are proposed discretely in the form of tables or charts. This form of information does not always meet the requirements of operational correction and does not allow assessing the technological capabilities of the harvesting units, depending on the harvesting conditions. The method to improve the formation of the initial information for operational decision-making on the effective upgrading of technical means of grain harvesting complex taking into account the zonal features of a particular agricultural enterprise is proposed. A graph-analytical method for determining the main parameters of the basic harvesting tools depending on the predicted yield level is developed and the influence of the factors determining the composition of the grain harvesting fleet is assessed. This method makes it possible to identify the most rational basic parameters of alternative basic harvesting tools for a specific agricultural enterprise. The first step is to determine the basic parameters of the basic equipment, then select the appropriate size series of self-propelled threshers for combine harvesters and reapers. Further, alternative versions of various models of grain harvesting units and complexes are formed. For the subsequent selection of rational types of cleaning agents and their criterion assessment, technical and technological, environmental and other indicators are used. The expert-logical analysis of information resources makes it possible to identify and assess the factors that determine the quantitative composition of the technical means of the grain harvesting complex. The final stage in the formation of the initial information for making a decision on updating the technical means of the grain harvesting complex should be their economic assessment, which makes it possible to predict the competitiveness of the threshed grain.

Comparative Indicators of Grain Transportation When Unloading Combine Harvesters at the the Field Edge

Base don theresults of comparative experience in production conditions, the indicators of grain transportation by trucks were determined when unloading combine harvesters at the field edge.

Design and Experiment of a Broken Corn Kernel Detection Device Based on the Yolov4-Tiny Algorithm

At present, the wide application of the CNN (convolutional neural network) algorithm has greatly improved the intelligence level of agricultural machinery. Accurate and real-time detection for outdoor conditions is necessary for realizing intelligence and automation of corn harvesting. In view of the problems with existing detection methods for judging the integrity of corn kernels, such as low accuracy, poor reliability, and difficulty in adapting to the complicated and changeable harvesting environment, this paper investigates a broken corn kernel detection device for combine harvesters by using the yolov4-tiny model. Hardware construction is first designed to acquire continuous images and processing of corn kernels without overlap. Based on the images collected, the yolov4-tiny model is then utilized for training recognition of the intact and broken corn kernels samples. Next, a broken corn kernel detection algorithm is developed. Finally, the experiments are carried out to verify the effectiveness of the broken corn kernel detection device. The laboratory results show that the accuracy of the yolov4-tiny model is 93.5% for intact kernels and 93.0% for broken kernels, and the value of precision, recall, and F1 score are 92.8%, 93.5%, and 93.11%, respectively. The field experiment results show that the broken kernel rate obtained by the designed detection device are in good agreement with that obtained by the manually calculated statistic, with differentials at only 0.8%. This study provides a technical reference of a real-time method for detecting a broken corn kernel rate.

Technology and organization of storage of combine harvesters

During long-term storage, climatic and atmospheric factors affect the agricultural machine, which cause changes in the physical and chemical properties of structural materials, technical fluids, lubricants. Therefore, the development of technical and organizational measures related to improving the storage efficiency of combine harvesters is an urgent scientific task that the leading scientific institutes of the country are engaged in.

Study on Performance of Concentric Threshing Device with Multi-Threshing Gaps for Rice Combines

S concentric threshing device can improve rice crop separation and transportation capabilities. As one of the main factors affecting the threshing performance of rice combine harvesters, the threshing gap can influence the grain unthreshed rate and the grain damage rate directly. However, the clearance between any threshing cylinder tooth and the concave grid is constant for the traditional threshing device, named the single threshing gap in this paper, resulting in a consistently high total loss rate (the sum of unthreshed and damaged grains). Therefore, multi-threshing gaps are proposed in this paper for the concentric threshing device to solve the above problem. To compare the threshing performance between the single threshing gap and the multi-threshing gaps, the movement process of rice mixture (grain, short straw, and long straw) was simulated using the discrete element method (DEM). The simulation results showed that the separation and transportation abilities of the multi-threshing gaps were not decreased, but the distribution of threshed output mixture was more even for the multi-threshing gaps. Furthermore, a field experiment was also carried out on a combine harvester to compare the total loss rate. The experiment results showed that the total loss rate of the concentric threshing device with multi-threshing gaps was reduced by 0.0593%, which was 5.77% less than the total loss rate of the concentric threshing device with a single threshing gap.