Search Results (12)

To address the problems of low crushing efficiency and uneven distribution in traditional straw crushing and returning machines for cotton stalk return operations in Xinjiang, a vertical straw crushing and returning machine with large and small dual-blade discs was designed, adapted to Xinjiang’s cotton planting model. The machine employs a differentiated configuration of large and small blade discs corresponding to four and two rows of cotton stalks, respectively, effectively reducing tool workload while significantly improving operational efficiency. A simulation model of the crushing and returning machine was developed using the discrete element method (DEM), and a flexible cotton stalk model was established to systematically investigate the effects of machine forward speed, crushing blade rotational speed, and knife tip-to-ground clearance on operational performance. Single-factor simulation experiments were conducted using crushing qualification rate and broken stalk drop rate as evaluation indicators. Subsequently, a multi-factor orthogonal field experiment was designed with Design-Expert software (13.0.1.0, Stat-Ease Inc, Minneapolis, MN, USA). The optimal working parameters were determined to be machine forward speed of 3.5 m/s, crushing blade shaft speed of 1500 r/min, and blade tip ground clearance of 60 mm. Verification tests demonstrated that under these optimal parameters, the straw crushing qualification rate reached 95.9% with a broken stalk drop rate of 15.5%. The relative errors were less than 5% compared to theoretical optimization values, confirming the reliability of parameter optimization. This study provides valuable references for the design optimization and engineering application of straw return machinery. Full article

The scenario adaptability of agricultural machinery chassis in hilly and mountainous regions has become a key area of innovation in modern agricultural equipment development in China. Due to the fragmented nature of farmland, steep terrain (often exceeding 15°), complex topography, and limited suitability for mechanization, traditional agricultural machinery experiences significantly reduced operational efficiency—typically by 30% to 50%—along with poor mobility. These limitations impose serious constraints on grain yield stability and the advancement of agricultural modernization. Therefore, enhancing the scenario-adaptive performance of chassis systems (e.g., slope adaptability ≥ 25°, lateral tilt stability > 30°) is a major research priority for China’s agricultural equipment industry. This paper presents a systematic review of the global development status of agricultural machinery chassis tailored for hilly and mountainous environments. It focuses on three core subsystems—power systems, traveling systems, and leveling systems—and analyzes their technical characteristics, working principles, and scenario-specific adaptability. In alignment with China’s “Dual Carbon” strategy and the unique operational requirements of hilly–mountainous areas (such as high gradients, uneven terrain, and small field sizes), this study proposes three key technological directions for the development of intelligent agricultural machinery chassis: (1) Multi-mode traveling mechanism design: Aimed at improving terrain traversability (ground clearance ≥400 mm, obstacle-crossing height ≥ 250 mm) and traction stability (slip ratio < 15%) across diverse landscapes. (2) Coordinated control algorithm optimization: Designed to ensure stable torque output (fluctuation rate < ±10%) and maintain gradient operation efficiency (e.g., less than 15% efficiency loss on 25° slopes) through power–drive synergy while also optimizing energy management strategies. (3) Intelligent perception system integration: Facilitating high-precision adaptive leveling (accuracy ± 0.5°, response time < 3 s) and enabling terrain-adaptive mechanism optimization to enhance platform stability and operational safety. By establishing these performance benchmarks and focusing on critical technical priorities—including terrain-adaptive mechanism upgrades, energy-drive coordination, and precision leveling—this study provides a clear roadmap for the development of modular and intelligent chassis systems specifically designed for China’s hilly and mountainous regions, thereby addressing current bottlenecks in agricultural mechanization. Full article

Achieving global sustainable agriculture requires farmers worldwide to adopt smart agricultural technologies, such as autonomous ground robots. However, most ground robots are either task- or crop-specific and expensive for small-scale farmers and smallholders. Therefore, there is a need for cost-effective robotic platforms that are modular by design and can be easily adapted to varying tasks and crops. This paper describes the hardware design of a unique, low-cost multiaxial modular agricultural robot (ModagRobot), and its field evaluation for soybean phenotyping. The ModagRobot’s chassis was designed without any welded components, making it easy to adjust trackwidth, height, ground clearance, and length. For this experiment, the ModagRobot was equipped with an RGB-Depth (RGB-D) sensor and adapted to safely navigate over soybean rows to collect RGB-D images for estimating soybean phenotypic traits. RGB images were processed using the Excess Green Index to estimate the percent canopy ground coverage area. 3D point clouds generated from RGB-D images were used to estimate canopy height (CH) and the 3D Profile Index of sample plots using linear regression. Aboveground biomass (AGB) was estimated using extracted phenotypic traits. Results showed an R², RMSE, and RRMSE of 0.786, 0.0181 m, and 2.47%, respectively, between estimated CH and measured CH. AGB estimated using all extracted traits showed an R², RMSE, and RRMSE of 0.59, 0.0742 kg/m², and 8.05%, respectively, compared to the measured AGB. The results demonstrate the effectiveness of the ModagRobot for in-row crop phenotyping. Full article

In China’s Yangtze River and Yellow River basin cotton-growing regions, the complex terrain, scattered planting areas, and poor adaptability of the existing machinery have led to a mechanized cotton harvesting rate of less than 10%. To address this issue, we designed a crawler chassis for a brush-roller cotton harvester. It is specifically tailored to meet the 76 cm row spacing agronomic requirement. We also conducted a theoretical analysis of the power transmission system for the crawler chassis. Initially, we considered the terrain characteristics of China’s inland cotton-growing regions and the current cotton agronomy practices. Based on these, we selected and designed the power system and chassis; then, a finite element static analysis was carried out on the chassis frame to ensure safety during operation; finally, field tests on the harvester’s operability, stability, and speed were carried out. The results show that the inverted trapezoidal crawler walking device, combined with a hydraulic continuously variable transmission and rear-drive design, enhances the crawler’s passability. The crawler parameters included a ground contact length of 1650 mm, a maximum ground clearance of 270 mm, a maximum operating speed of 6.1 km/h, and an actual turning radius of 2300 mm. The maximum deformation of the frame was 2.198 mm, the deformation of the walking chassis was 1.0716 mm, the maximum equivalent stress was 216.96 MPa, and the average equivalent stress of the entire frame was 5.6356 MPa, which complies with the physical properties of the selected material, Q235. The designed cotton harvester crawler chassis features stable straight-line and steering performance. The vehicle’s speed can be adjusted based on the complexity of the terrain, with timely steering responses, minimal compaction on cotton, and reduced soil damage, meeting the requirements for mechanized harvesting in China’s inland small plots. Full article

A few promising solutions for thermal imaging Unexploded Ordnance (UXO) detection were proposed after the start of the military conflict in Ukraine in 2014. At the same time, most of the landmine clearance protocols and practices are based on old, 20th-century technologies. More than 60 countries worldwide are still affected by explosive remnants of war, and new areas are contaminated almost every day. To date, no automated solutions exist for surface UXO detection by using thermal imaging. One of the reasons is also that there are no publicly available data. This research bridges both gaps by introducing an automated UXO detection method, and by publishing thermal imaging data. During a project in Bosnia and Herzegovina in 2019, an organisation, Norwegian People’s Aid, collected data about unexploded ordnances and made them available for this research. Thermal images with a size of 720 × 480 pixels were collected by using an Unmanned Aerial Vehicle at a height of 3 m, thus achieving a very small Ground Sampling Distance (GSD). One of the goals of our research was also to verify if the explosive war remnants’ detection accuracy could be improved further by using Convolutional Neural Networks (CNN). We have experimented with various existing modern CNN architectures for object identification, whereat the YOLOv5 model was selected as the most promising for retraining. An eleven-class object detection problem was solved primarily in this study. Our data were annotated semi-manually. Five versions of the YOLOv5 model, fine-tuned with a grid-search, were trained end-to-end on randomly selected 640 training and 80 validation images from our dataset. The trained models were verified on the remaining 88 images from our dataset. Objects from each of the eleven classes were identified with more than 90% probability, whereat the Mean Average Precision (mAP) at a 0.5 threshold was 99.5%, and the mAP at thresholds from 0.5 to 0.95 was 87.0% up to 90.5%, depending on the model’s complexity. Our results are comparable to the state-of-the-art, whereat these object detection methods have been tested on other similar small datasets with thermal images. Our study is one of the few in the field of Automated UXO detection by using thermal images, and the first that solves the problem of identifying more than one class of objects. On the other hand, publicly available thermal images with a relatively small GSD will enable and stimulate the development of new detection algorithms, where our method and results can serve as a baseline. Only really accurate automatic UXO detection solutions will help to solve one of the least explored worldwide life-threatening problems. Full article

The middle and lower reaches of the Yangtze River are the main production area of rapeseed. Small windrowers with two tracks are adopted in this area, which have lower efficiency. With the advancement of large-scale rape planting, medium and large windrowers are urgently needed; however, most medium and large windrowers are wheeled machines which have poor adaptability to sticky soil in rice–rape rotation areas. Therefore, a wheel-track high clearance chassis for rape windrower was developed. Theoretical analysis and simulation of the main performance of this chassis were investigated. Mathematical models of the relationship between the chassis eccentricity and running resistance, uphill and downhill angle and the height of obstacle were established. Then, three-dimensional modeling and dynamic simulations of a wheel-track high clearance chassis of a rape windrower in wet clay soil were carried out based on Pro/E and RecurDyn software. The simulation results indicated that when the chassis ran on flat hard road at the same speed, eccentricity had little effect on average walking speed; the coefficient variation of speed decreased with the increase of eccentricity, while the driving torque and its coefficient variation decreased first and then increased. The minimum driving torque and the coefficient variations were obtained when the eccentricities were 1484 mm and 1584 mm. Field experiments were carried out on two kinds of ground. The results showed that on flat hard road, the speed of the wheel-track high clearance rape windrower was 0~20.22 km/h, the minimum turning radius was 5.965 m; on rice stubble field with 38.7% water content, the working speed was 0~9.12 km/h, the minimum turning radius was 6.498 m, and the climbing angle was over 20°. All parameters of the wheel-track high clearance chassis met the design specifications, and the working efficiency increased over 100% compared with the existing two-tracked rape windrower. A new kind of rape windrower for the middle and lower reaches of the Yangtze River was provided. Full article

The combined ceiling and ground effect on the aerodynamics of a hovering flapping wing is investigated using numerical simulations. In the simulations, the wing was located between the ceiling and the ground. Simulations were carried out for different wall clearances at two Reynolds numbers ($Re$ = 10 and 100). Special efforts were paid to whether there exists aerodynamic coupling between the ceiling effect and the ground effect. At $Re$ = 10, the combined ceiling and ground effect increases the aerodynamic forces monotonically through two effects, namely the narrow-channel effect and the downwash-reducing effect. Additionally, there exists a coupling effect of the ceiling and the ground for the combined case at $Re$ = 10, where the force enhancement of the combined effect is much more significant than the sum of the ceiling-only effect and the ground-only effect. At $Re$ = 100, the combined effect of ceiling and ground causes three non-monotonic force regimes (force enhancement, reduction and recovery) with increasing wall clearance. The narrow-channel effect at $Re$ = 100 leads to a monotonic force trend, while the downwash-reducing effect results in a non-monotonic force trend. The two effects eventually lead to the three force regimes at $Re$ = 100. Unlike the $Re$ = 10 case, the coupling effect at $Re$ = 100 is small. Full article

The icing facilities of the Anti-Icing Materials International Laboratory AMIL have been adapted to reproduce icing conditions on a Bell APT70 drone rotor, typical of small-to-medium UAV models. As part of an extensive icing test campaign, this paper presents the design and preliminary testing of the experimental setup and representative icing conditions calibration in the laboratory’s cold chamber. The drone rotor used has four blades with a diameter of 0.66 m and a maximum tip speed of 208 m/s. For the icing conditions, freezing rain and freezing drizzle were selected. A Liquid Water Content (LWC) calculation methodology for a rotor in hover was developed, and procedures to determine experimental LWC in the facility are presented in this paper. For the test setup, the cold chamber test section was adapted to fit the rotor and to control its ground clearance. Testing was aimed at studying the effect of rotor height h on aerodynamic performance, both with and without icing conditions. Results show no significant effect on the ground effect between h = 2 m and h = 4 m in dry runs, while the icing behavior can be largely influenced for certain conditions by the proximity of the precipitation source, which depend on the height of the rotor in these experiments. Full article

The Society of Automotive Engineers (SAE) Recommended Practice (RP) J2954 (November 2017) was recently published to standardize the wireless power transfer (WPT) technology to recharge the battery of an electric vehicle (EV). The SAE J2954 RP establishes criteria for interoperability, electromagnetic compatibility (EMC), electromagnetic field (EMF) safety, etc. The aim of this study was to predict the magnetic field behavior inside and outside an EV during wireless charging using the design criteria of SAE RP J2954. Analyzing the worst case configurations of WPT coils and EV bodyshell by a sophisticated software tool based on the finite element method (FEM) that takes into account the field reflection and refraction of the metal EV bodyshell, it is possible to numerically assess the magnetic field levels in the environment. The investigation was performed considering the worst case configuration—a small city car with a Class 2 WPT system of 7.7 kVA with WPT coils with maximum admissible ground clearance and offset. The results showed that the reference level (RL) of the International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines in terms of magnetic flux density was exceeded under and beside the EV. To mitigate the magnetic field, the currents flowing through the WPT coils were varied using the inductor-capacitor-capacitor (LCC) compensation instead of the traditional series-series (SS) compensation. The corresponding calculated field was compliant with the 2010 ICNIRP RL and presented a limited exceedance of the 1998 ICNIRP RL. Finally, the influence of the body width on the magnetic field behavior adopting maximum offset was investigated, demonstrating that the magnetic field emission in the environment increased as the ground clearance increased and as the body width decreased. Full article

A compact antenna with a 6 mm ground clearance for 4G and 5G metal frame mobile phones is proposed in this paper. The proposed antenna consists of a coupled line, a ground branch, a monopole branch, and a tuning line. The ground branch and the coupled line are used to obtain the lower band (698–960 MHz), the monopole branch is used to improve the match at the lower band and obtain the higher band (1710–2690, 3400–3800 MHz), and the tuning line is used to improve the match at the higher band. The novelty of the proposed antenna is that more modes are excited and work together to obtain multiple working bands, by using the coupled line and the folded branches with the help of the tuning line, and then nine bands are obtained under the conditions of a 6 mm, only, ground clearance and a metal frame environment. A prototype has been fabricated and measured. The measured −6 dB impedance bandwidths are 345 MHz (0.685–1.03 GHz) and 2.16 GHz (1.67–3.83 GHz) at the lower and higher bands, respectively. The LTE700, GSM850, GSM900, DCS, PCS, UMTS, LTE2300, and LTE2500 bands for 2G, 3G, 4G, and the 3.5 GHz band that is possible for 5G are covered. The measured efficiencies and patterns are also presented. Full article

This paper proposes a 3D radiation pattern reconfigurable antenna (RPRA) and a reconfigurable phased array (RPA) for 5G mobile communication. The antenna and array are working at 28 GHz, which is selected as a 5G communication band in many countries. The proposed phased array will be applied as sensors to find out the optimal transmitting–receiving angle in a randomly changed cellular wireless scenarios. The RPRA and RPA are fed by Substrate Integrated Waveguide (SIW) and have three switchable radiation modes: Broadside 1, Broadside 2 and Endfire. The three modes correspond to three different radiation patterns and each of them covers a different area in the Azimuth plane. An eight-element phased array constructed by the proposed RPRA, which is able to switch beam in Azimuth plane and scan in the Elevation plane, is also presented in this paper. The proposed RPA is able to provide much higher spatial coverage than the conventional phased arrays and without additional feeding and phase shifting networks. The beam switching is realized by the PIN diodes. The proposed antenna and array have planer structures and require small clearance on the ground plane which makes them compatible with mobile phones. The simulations show good performance for both RPRA and RPA. Full article

Forests in snow-dominated areas have substantial effects on the snowpack and its evolution over time. Such interactions have significant consequences for the hydrological response of mountain rivers. Thus, the impact of forest management actions on the snow distribution, and hence the storage of water in the form of snow during winter and spring, is a major concern. The results of this study provide the first detailed comparison of the small-scale effect of forest characteristics on the snowpack distribution, assessed prior to and following major modification of the structure of the canopy by pruning of the lower branches of the trees to 3 m above the ground. This is a common management practice aimed at reducing the spread of forest fires. The snowpack distribution was determined using terrestrial laser scanning (LiDAR technology) at a high spatial resolution (0.25 m) over a 1000 m² study area during 23 survey dates over three snow seasons in a small study area in the central Pyrenees. The pruning was conducted during summer following the snow season in the second year of the study (i.e., the study duration encompassed two seasons prior to canopy pruning and one following). Principal component analysis (PCA) was used to identify recurring spatial patterns of snow distribution. The results showed that pruning reduced the average radius of the canopy of trees by 1.2 m, and increased the clearance around the trunks, as all the branches that formerly contacted the ground were removed. However, the impact on the snowpack was moderate. The PCA revealed that the spatial configuration of the snowpack did not change significantly, as the principal components included survey days from different periods of the snow season, and did not discriminate days surveyed prior to and following pruning. Nevertheless, removal of the lower branches reduced the area beneath the canopy by 36%, and led to an average increase in total snow depth of approximately 14%. Full article