As a promising and convenient numerical calculation approach, the discrete element method (DEM) has been increasingly adopted in the research of agricultural machinery. DEM is capable of monitoring and recording the dynamic and mechanical behavior of agricultural materials in the operational process of agricultural machinery, from both a macro-perspective and micro-perspective; which has been a tremendous help for the design and optimization of agricultural machines and their components. This paper reviewed the application research status of DEM in two aspects: First is the DEM model establishment of common agricultural materials such as soil, crop seed, and straw, etc. The other is the simulation of typical operational processes of agricultural machines or their components, such as rotary tillage, subsoiling, soil compaction, furrow opening, seed and fertilizer metering, crop harvesting, and so on. Finally, we evaluate the development prospects of the application of research on the DEM in agricultural machinery, and look forward to promoting its application in the field of the optimization and design of agricultural machinery.

Automatic machine vision-based defect detection has been successfully applied to many industrial visual inspection applications. However, automatic steel surface defect detection is still a challenging task due to diverse defect categories, low-contrast between defect and complex texture background. To address these challenges, a chained atrous spatial pyramid pooling network (CASPPNet) is proposed for steel surface defect detection. In CASPPNet, chained atrous spatial pyramid pooling is designed to enlarge receptive field and obtain enrich semantic information. An improved global attention feature fusion module is introduced to achieve feature interaction and salience. Moreover, residual boundary refinement block is introduced to get more complete defect boundary. Comparative experimental results verify that our method is superior to the state-of-the-art segmentation methods on public accessible SD-saliency-900 datasets and can meet the requirement of real-time online detection (the detection efficiency is at over 47 FPS on a single GPU).

NiCr/hBN self-lubricating composites with hBN solid-lubricant contents of 8%, 9%, 10%, 11%, and 12% (mass fractions) were prepared by powder-metallurgy method. Their tribological properties at room temperature and 600, 700, and 800 °C were studied. SEM and XRD were performed to analyze their wear-surface morphology and abrasive-dust composition. Results indicate that the NiCr/hBN self-lubricating composites have favorable tribological properties at room temperature and 600 °C. The optimum comprehensive friction and wear performance are achieved at 10% hBN, and the main wear mechanism is abrasive wear. At 700 and 800 °C, the friction and wear properties of NiCr/hBN self-lubricating composites obviously decline. The wear surface experiences oxidation and the spinel oxides Cr2O3, NiCr2O4, and CrBO3 are formed. The main wear mechanism becomes combined scratching and glue form of adhesive wear, leading to greatly increased wear rate for the NiCr/hBN sel-lubricating composites.

This study aimed to improve the measurement accuracy of the discrete element method (DEM) simulation parameters of sorghum seeds for enhanced model accuracy. We measured the intrinsic and contact parameters of sorghum seeds, extracted the outline of the seeds by 3D scanning, and used the multi-spherical particle model filling method in the EDEM (Version 2020) software to obtain the simulation model of the seeds. By simulating the free-fall, slope slip, slope rolling, and rolling experiments of sorghum seeds–photosensitive resin material, we calibrated the collision restitution coefficient of the sorghum seeds–photosensitive resin material to 0.690, static friction coefficient to 0.345, and rolling friction coefficient to 0.040. Through the steepest ascent search and central composite design experiments, we calibrated the collision restitution coefficient of sorghum seeds–sorghum seeds to 0.400, the static friction coefficient to 0.450, and the rolling friction coefficient to 0.043. The angle of repose of the parameter combination and the angle of repose of the physical experiment (33.82°) were verified, and the relative errors of the coefficients were 0.7%, 0.25%, and 0.3%, respectively, indicating that the established model had a high simulation accuracy and reliability. These results show that the established sorghum seeds model and the optimally calibrated parameter combination are effective for DEM studies on sorghum seeds.

Achieving rapid and accurate localization of winter jujubes in trees is an indispensable step for the development of automated harvesting equipment. Unlike larger fruits such as apples, winter jujube is smaller with a higher density and serious occlusion, which obliges higher requirements for the identification and positioning. To address the issues, an accurate winter jujube localization method using improved YOLOX-Nano network was proposed. First, a winter jujube dataset containing a variety of complex scenes, such as backlit, occluded, and different fields of view, was established to train our model. Then, to improve its feature learning ability, an attention feature enhancement module was designed to strengthen useful features and weaken irrelevant features. Moreover, DIoU loss was used to optimize training and obtain a more robust model. A 3D positioning error experiment and a comparative experiment were conducted to validate the effectiveness of our method. The comparative experiment results showed that our method outperforms the state-of-the-art object detection networks and the lightweight networks. Specifically, the precision, recall, and AP of our method reached 93.08%, 87.83%, and 95.56%, respectively. The positioning error experiment results showed that the average positioning errors of the X, Y, Z coordinate axis were 5.8 mm, 5.4 mm, and 3.8 mm, respectively. The model size is only 4.47 MB and can meet the requirements of winter jujube picking for detection accuracy, positioning errors, and the deployment of embedded systems.

Aiming to solve the problems of the poor uniformity of seed flow discharge and serious damage of traditional straight grooved wheels to improve the performance of air-assisted maize high-speed precision seed metering devices, a staggering symmetrical spiral grooved feeding wheel with maize seeds was designed. To explore the influence of the spiral groove inclination angle and the length of the staggered symmetrical spiral groove feed wheel on the uniformity of seed flow discharge, the spiral groove length l and the spiral groove inclination angle ρ were used as the experimental factors, and the variation coefficient of the increase in seed, a full-factor simulation test was carried out for the test indicators, and it was found that both the inclination angle and the length of the spiral groove have an influence on the uniformity of seed flow discharge, and the influence of the inclination angle of the groove is more significant. Comparing the force of a single seed in the traditional straight grooved wheel and that of the spiral feeding wheel, it is found that the staggered symmetrical spiral grooved feeding wheel can reduce the damage of seed fertilizer. Through a bench test, the spiral groove length was found to be 50 mm, and the groove inclination angles are 30°, 45° and 90°. The test results show the variation trend and simulation results of the fluctuating coefficient of variation of the seed flow discharge in the bench test. The trend of change is basically the same. The inclination angle of the spiral groove is 45° and the uniformity of seed flow discharge is the best when the groove length is 50 mm, indicating that this structure can effectively improve the uniformity of material discharge, and the variation coefficient of seed flow discharge fluctuation is 3.12% and the seed breakage rate is 0.69%. Through the seeding performance test, it is verified that the staggered symmetrical spiral grooved feeding wheel can improve the seeding performance of the pneumatic high-speed precision metering device. When the metering device runs smoothly, the qualified rate reaches more than 90%, and the leakage rate is reduced to 0%. Therefore, the results of this study can provide a reference for research on uniform seeding, drill seeding and the uniform application of granular fertilizer.