Search Results (53)

The optimisation design of agricultural machinery is shifting from offline, experience-driven engineering towards adaptive, data-driven, and closed-loop intelligent optimisation. Conventional approaches based on computer-aided engineering (CAE), empirical testing, mathematical modelling, and static multi-objective optimisation have provided an important engineering foundation, but they remain limited under unstructured field conditions involving soil heterogeneity, crop variability, climatic disturbance, and nonlinear machinery–environment interactions. This review systematically examines the evolution of intelligent optimisation design for agricultural machinery from conventional simulation-based methods to artificial intelligence (AI)- and digital twin (DT)-enabled paradigms. First, mathematical modelling, response surface methodology, discrete element method (DEM), computational fluid dynamics (CFD), multi-body dynamics (MBD), heuristic algorithms, and early AI-assisted surrogate optimisation are reviewed to clarify their contributions and limitations. Second, frontier enabling technologies are analysed, including agriculture-specific large models, generative AI, lightweight edge intelligence, deep reinforcement learning (DRL), embodied AI, federated learning (FL), and privacy-preserving computing. Third, system-level applications integrating DT and AI are discussed, with emphasis on full-lifecycle machinery optimisation, device–edge–cloud collaborative control, multi-agent fleet coordination, predictive maintenance, and Agriculture 5.0-oriented intelligent equipment systems. Key deployment bottlenecks are further identified, including sim-to-real inconsistency, virtual–physical mismatch in DTs, edge-side trade-offs among accuracy, latency, energy consumption, and cost, insufficient validation standards, and economic adoption barriers. Finally, a 2025–2030 roadmap is proposed, highlighting large-model–DT closed loops, control biomimetics, green low-carbon optimisation, and trustworthy human–machine symbiosis for sustainable Agriculture 5.0. Full article

Under dry sowing and wet emergence conditions in Xinjiang, cotton planting with extra-wide film mulching and sowing faced challenges including low soil moisture content and poor soil plasticity. These conditions resulted in inadequate film edge laying, seed exposure, and unstable sowing depth. This study focused on an extra-wide film mulch planter, conducting operational process analysis and parameter optimization experiments. The research first analyzed the soil layer structure required for a high-quality cotton seedbed, described the structural composition and working principle of the extra-wide film mulch planter, and examined the interaction between key components and soil during operation. The primary factors affecting machine performance were identified, and a soil-deflecting device was added to mitigate rapid soil backflow. A coupled MBD-DEM model was developed to simulate the operation of key components, and simulation experiments were conducted. The optimal parameter combination obtained through optimization was as follows: furrowing disc deflection angle of 11°, primary soil-covering disc deflection angle of 20°, operational speed of 3.5 km/h, longitudinal blade height of 16 mm, and spring stiffness of 14 N/mm. Simulation validation under these parameters yielded the following results: covering soil amount ranged from 3.22 kg/m to 3.67 kg/m, with a mean of 3.43 kg/m; seeding qualification rate ranged from 94.97% to 97.52%, with a mean of 96.3%; film hole length ranged from 43.14 mm to 46.86 mm, with a mean of 45.18 mm; and cotton seed sowing depth ranged from 29.51 mm to 31.82 mm, with a mean of 31.23 mm. These simulation results met the operational requirements for extra-wide film mulching and sowing. Field validation experiments were conducted using the optimal parameter combination. The results showed a mean soil-covering thickness of 35.1 mm, mean soil-covering width of 65.3 mm, mean film hole length of 45.7 mm, and mean cotton seed sowing depth of 29.1 mm, with coefficients of variation of 5.1%, 2.6%, 4.7%, and 5.8%, respectively. The field results were generally consistent with the simulation results, confirming the reliability of the simulation model and demonstrating improved operational performance of the extra-wide film mulch planter, making it more suitable for the dry sowing with wet emergence technique. Twenty days after sowing, the mean emergence rate reached 93.3% with a coefficient of variation of 1.0%, indicating stable emergence, which preliminarily validated the effectiveness of the constructed seedbed in promoting cotton growth. Full article

High-pressure grinding rolls (HPGRs) are critical in mineral processing, making comprehensive research and analysis of their performance of great significance. This study focuses on the HPGR-3516 test prototype and develops an analytical model that combines the discrete element method (DEM) with multi-body dynamics (MBD). The influences of feed top size, roll speed, and specific press force on equipment performance were examined using analysis of variance (ANOVA) in conjunction with response surface methodology (RSM). A performance prediction model was established through regression analysis, followed by multi-objective optimization and experimental validation. The results indicate that increasing roll speed under high specific press force significantly reduces the roll gap, while the effect is negligible under low specific press force. Increasing roll speed improves throughput more substantially for fine feed than for coarse feed. The optimal process parameters were determined to be a feed top size of 8 mm, a roll speed of 0.37 m/s, and a specific press force of $4.84 \mathrm{N}/{\mathrm{m}\mathrm{m}}^2$. In comparison to the original parameters, throughput increased by 15.81%, qualified particle size passing rate (QPR) improved by 7.85%, and roll gap decreased by 10.24%. This study offers valuable insights into predicting the dynamic performance of HPGRs and has significant engineering implications. Full article

Weed control is crucial for safeguarding the yield and quality of fresh maize. To achieve comprehensive, low-damage removal of weeds in fresh maize fields, an intelligent mechanical weeding system was developed. Based on the spatial distribution of maize seedling roots and agronomic requirements, a three-dimensional protection zone was established and a dedicated intra-row weeding knife was designed. An EDEM–RecurDyn co-simulation was then performed; single-factor and orthogonal experiments were used to evaluate the effects of operating speed, hydraulic cylinder extension–retraction speed, and knife bending angle on the coverage rate and intrusion rate, and to determine the optimal parameter combination. Seedling detection and field weeding trials were subsequently conducted. The detection accuracies under good and low illumination were 95.82% and 93.32%, respectively. Under the optimal settings (operating speed 1.5 km/h, hydraulic cylinder extension–retraction speed 0.22 m/s, and knife bending angle 20°), the system achieved a mean weeding rate of 90.79% and a mean seedling damage rate of 2.27%. The results demonstrate stable performance and confirm that the proposed system meets the requirements for comprehensive, low-damage weeding in fresh maize fields, providing a reference for the design of intelligent mechanical weeding equipment. Full article

Aiming at the problems of inter-row straw congestion, soil accumulation, and consequent uneven seeding depth during high-speed sowing with narrow row spacing under the summer maize no-tillage sowing mode in the Huang-Huai-Hai region, this study proposed a maize seedling belt pre-sowing treatment device suitable for narrow row spacing operation by analyzing the physical properties of straw and soil in the region. Dynamic analysis of the mechanical device was carried out, and the key factors affecting the straw removal effect of the seedling belt and the degree of soil disturbance were identified as machine offset distance, traction speed, and straw-cleaning wheel angle. Discrete element method simulation experiments were conducted via EDEM-ADAMS coupling; the key factors were simulated and optimized, and the optimal parameter combination of the device was determined as follows: machine offset distance of 165 cm (the relative distance between the front and rear positions of the right wheel of adjacent unit cleaning components), traction speed of 11 km/h, and straw-cleaning wheel angle of 44°. Field validation tests of the prototype were performed. The test results showed that the overall straw removal rate of the seedling belt reached 95%, and no large-scale straw and soil accumulation caused by pushing was observed between rows. Compared with the simulation results, the error of straw removal rate was only 0.5%. Sowing comparison tests were conducted, and the results indicated that the device could significantly improve the uniformity of seeding depth and meet the seedling belt quality requirements for high-speed sowing with narrow row spacing of summer maize. This study provides new ideas and methods for the design of straw-cleaning mechanisms in no-till seeding systems. Full article

Accurate prediction of excavation forces is critical for the design reliability and operational safety of Mars surface sampling systems. This study establishes an analytical modeling framework to describe the excavation mechanics of Martian soil, focusing on the formation mechanism and evolution of resistance. Soil deformation and failure processes are qualitatively identified using particle image velocimetry (PIV) and discrete element method (DEM) simulations. Based on limit equilibrium theory, the passive earth pressure is derived, and the scoop is divided into seven force-bearing regions for three-dimensional force decomposition. The analytical model is validated against multibody dynamics–discrete element method (MBD–DEM) co-simulation. The results indicate that excavation resistance exhibits a distinct single-peak evolution, maximizing near the maximum excavation depth. Notably, the inner bottom surface and cutting edge dominate resistance during penetration, contributing approximately 56% and 30% of the total force, respectively. The resistance mechanism transitions after soil emergence due to the gravitational effect of retained soil. Consequently, this framework provides a physically interpretable and quantitatively validated approach for force prediction, offering theoretical support for sampling scoop design and optimization in future Mars missions. Full article

The operational reliability of the elastic wheel, essential for specialized vehicle mobility on complex terrain, is critically constrained by fatigue failure under multi-axis ground loads. While high-fidelity physics-based simulation provides an accurate assessment, its “one-simulation-per-test” paradigm is inefficient for exploring multi-condition, multi-parameter designs. Conversely, purely data-driven methods are hindered by the scarcity of high-quality fatigue data. This paper proposes LightGBM-CH, an integrated framework that couples Discrete Element Method–Multi-Body Dynamics (DEM-MBD) simulation with an enhanced LightGBM model to overcome these limitations. The framework first converts high-fidelity simulations into a configurable data generator, producing batches of dynamic load–stress response data. A physics-informed feature engineering scheme then extracts 122 discriminative features characterizing six-dimensional loads, fatigue damage metrics, and load–stress coupling. To address the “small-sample, high-dimensional” challenge, a tailored training strategy incorporating robust scaling, correlation-based feature selection, and stability-constrained hyperparameter optimization is developed. Simulation experiments demonstrate that the LightGBM-CH model achieves a determination coefficient of 0.9251 and a root mean square error of 67.06, significantly outperforming benchmark models in accuracy and generalization. The study validates the framework’s engineering efficacy, identifies key influencing factors such as peak–stress ratio, and provides an intelligent, data-informed pathway for fatigue-resistant elastic wheel design. Full article

Potato combine harvesters often face the challenge of balancing efficient potato–soil separation with minimizing tuber mechanical damage, which significantly affects harvest quality and economic returns. To address this issue, a dual-vibration potato–soil separation conveyor was designed based on agronomic planting parameters and soil physical characteristics. A high-fidelity DEM-MBD coupling simulation model was developed to analyze soil clod breakage behavior and potato collision-induced jumping dynamics, and to identify key operational factors influencing separation performance. The porosity was verified using computer vision combined with CT technology to ensure the model’s fidelity. Single-factor simulations and a central composite design (CCD) response surface experiment were conducted using potato damage rate and soil removal efficiency as evaluation indices. The results showed that the inclination angle α, conveying line speed V_f, and vibration frequency f were the dominant factors affecting separation efficiency and tuber integrity. Multi-objective optimization determined optimal operating parameters of α = 18.51°, V_f = 1.995 km·h⁻¹, and f = 6.22 Hz, under which soil removal efficiency reached 98.43% and the minimum damage rate was 1.60%. Field experiments using a 4U-1000 combine harvester verified the simulation results, with an average soil removal efficiency of 97.8% and an average damage rate of 1.62%. These findings confirm the accuracy of the DEM-MBD simulation model and provide theoretical guidance for optimizing separation devices in large-scale potato harvesting equipment. Full article

This study investigates a duckbill-type hole seeder to elucidate the kinematic and force characteristics of hole formation under the dry sowing–wet emergence regime and to provide theoretical support for the optimization of key structural parameters. A bidirectional coupling simulation model based on the discrete element method (DEM) and multibody dynamics (MBD) was established to analyze the motion trajectories of the fixed and movable duckbills, the evolution of three-directional forces, and the associated soil–plastic film disturbance under different combinations of front and rear angles. The results indicate that soil disturbance during hole formation is dominated by vertical penetration and uplift, accompanied by forward cutting and lateral redistribution. The three-directional forces acting on the fixed duckbill exhibit a non-monotonic response with respect to the front angle, decreasing first and then increasing, while the force level during the expansion stage of the movable duckbill generally increases with the rear angle. Within the investigated parameter range, a front angle of 18° combined with a rear angle of 38° resulted in a relatively lower overall force level during penetration and expansion, which is favorable for stable hole formation. Field experiments conducted with this configuration showed an average seed placement deviation of 0.50 cm, satisfying the requirements for precision cotton planting under plastic mulch. The findings provide theoretical insight and methodological support for the structural optimization and engineering design of cotton hole seeders operating under the dry sowing–wet emergence regime. Full article

To address the challenges of the lack of specialized machinery adapted to traditional agronomic requirements, high labor intensity, and low efficiency in the planting of Ligusticum chuanxiong stalk segments (commonly known as Chuanxiong seed stalk or Lingzhong), a planting mechanism for the cutting of Chuanxiong seed stalk was developed in accordance with traditional agronomic requirements. A kinematic model of the gripping point was established, from which a plant spacing formula was derived. Based on the zero-speed planting principle, a cuttage planting scheme for Chuanxiong seed stalks was proposed, in which the gripper trajectory as well as the forward-tilt x_t and correction x_c were defined, and the decisive role of installation height on planting depth and the influence of driven-sprocket motion parameters on planting uprightness were elucidated. A 3D model and a DEM-MBD coupled simulation model were constructed to analyze planter–soil–seed interaction. A three-factor, three-level Box–Behnken experiment was conducted, and a response surface model was built and optimized using ‘Design-Expert’ software. The optimal parameters were a driven sprocket angular velocity of 0.654 rad/s, a rotation radius of 100.787 mm, and a release angle of 90.647°, yielding an average planting uprightness of 85.264°, with the corresponding x_t and x_c of 5.18 mm and 2.69 mm, respectively; the factor influence ranked as angular velocity > rotation radius > release angle. Seed–soil interaction analysis verified the mechanism’s feasibility and the accuracy of the theoretical models. Field tests showed average qualification rates of 87.13% for plant spacing, 96.01% for planting depth, and 90.41% for uprightness, with corresponding coefficients of variation of 4.37%, 2.95%, and 3.73%, indicating stable and reliable field performance. Full article

With the continuous increase in high-speed train operating speeds, effective vibration suppression of the car body is critical for ensuring passenger comfort. This study proposes a composite damping device based on particle damping technology, featuring a variable cavity structure incorporating spring components designed for space-constrained areas. The primary aim of this work is to elucidate the energy dissipation mechanism of granular media under adaptive boundary conditions and to establish a novel method for overcoming the saturation limitations of traditional fixed-cavity dampers. The energy dissipation characteristics were investigated using coupled Discrete Element Method (DEM) and Multibody Dynamics (MBD) numerical simulations. Parametric analysis quantitatively demonstrated significant performance variations: 2 mm particles outperformed larger diameters by maximizing collision frequency, and cast iron particles (29.497 J) achieved approximately five times the energy dissipation of steel particles (5.909 J). Furthermore, the filling rate exhibited a non-linear relationship with damping performance, peaking at a 98% filling rate (57.251 J)—a nearly 9-fold increase compared to a 90% filling rate. Most notably, quantitative comparison confirms that the introduction of the spring-adaptive mechanism enhanced the total energy dissipation to approximately 2 times that of the traditional fixed-cavity design. Simulation results reveal that the flexible cavity significantly enhances performance by preventing particle packing and stagnation. The dynamic deformation continuously “recruits” particles into high-energy collision regimes, ensuring sustained broadband attenuation. These findings establish the spring-based variable volume design as a high-efficiency strategy for high-speed rail applications. Full article

To address the low efficiency of corn straw collection, this study aims to optimize the design of the straw shredding mechanism of corn straw harvesters. A multi-blade arrangement shredding mechanism was designed, with ANSYS 2022 employed for gas-phase flow field simulation of the pick-up and fan conveying chambers, and a multi-field coupled simulation was conducted to evaluate performance using pick-up rate and qualified cutting length rate as metrics. Field tests were carried out to validate the simulation results. The results show that the DC-type pick-up (symmetrically arranged Y-shaped and hammer claw blades) exhibited optimal performance. At a travel speed of 1.2 m/s and rotational speed of 2100 r/min, the pick-up rate and qualified cutting length rate reached 93.62% and 93.94%, respectively, in field tests (81.34% pick-up rate in simulation); its maximum collection efficiency reached 92.98% under the conditions of fan 1 speed of 2300 r/min, fan 2 speed of 4600 r/min, and single feed rate of 9.4 kg. All pick-up types had maximum forces below the stress limit (348 MPa), meeting operational requirements. This research provides reliable references for the design and optimization of corn straw returning machines and verifies the accuracy of the simulation method. Full article

To solve the problems of high resistance and blockage in stubble-breaking operations, it is necessary to reveal the interaction mechanism between disc coulters and crop root–soil composites. This study developed a discrete element method–multi-body dynamics (DEM-MBD) coupling model of the stubble-breaking operation and verified the accuracy of the model through soil bin tests (error < 20%) and field experiments (error < 32%). The model was used to investigate the effects of different design parameters (coulter type and disc radius) and operating parameters (tillage speed and depth) on the stubble-breaking operation. The results showed that due to the significant strengthening effect of roots on soil, the resistance of disc coulter stubble-breaking operation was high; the number of roots in contact with the blade edge and the amount of root deformation significantly affected the resistance of the disc coulter; irreversible deformation of roots and soil could easily lead to the holes and root hairpin effects in the seeding furrow; compared to plain disc coulters, the difference in the time of deformation and fracture of the roots made the resistance of the notched coulter lower. The wavy disc coulter with a longer edge curve made its resistance higher; the disc coulter with a greater radius, higher tillage speed, and deeper tillage depth significantly increased the tillage resistance. However, the disc coulter with a greater radius or a higher tillage speed was beneficial for improving stubble-breaking performance. This study revealed the interaction mechanism between disc coulters and maize root-soil composites, providing a theoretical basis for the optimization design of no-till stubble-breaking devices. Full article

Under the condition of high-speed maize seeding, the collision between the seeds and the restraint seeding guide device, as well as the excessively high seeding speed, will lead to a sharp increase in the coefficient of variation in the seed spacing during seeding. To address these problems, this study designed a brush-belt-type seed-guiding device incorporating an auxiliary seed-receiving mechanism (ASRM). The aim of this device is to improve the stability of the brush tube in receiving seeds through the ASRM and to stabilize the seed spacing during seeding under the constraint of the brush belt and the seeding tube. Finally, the seeding speed is balanced by adjusting the rotational speed of the brush belt to achieve zero-speed seeding. A multi-body dynamics model of the seeding machine and a discrete element model of the soil were constructed. The seeding process of the device was simulated and analyzed using the discrete element method and multi-body dynamics (DEM-MBD) coupling simulation method. The seeding height and seeding angle were used as experimental factors, and a two-factor five-level orthogonal simulation experiment was conducted. The qualified rate of seed spacing, the re-seeding rate, and the missed seeding rate were used as experimental indicators. The results show that the optimal operating parameters of this device are as follows: seeding height of 46.8 mm, seeding angle of 25.5°, qualified coefficient of seed spacing of 96.03%, missed seeding rate of 1.76%, and re-seeding rate of 3.48%. Under the optimal working parameters of the device, speed performance verification tests were conducted. The research results show that when the operating speed is 12–16 km h⁻¹, the qualified rate of grain spacing is not less than 94.3%, the re-seeding rate does not exceed 3.92%, the missed seeding rate does not exceed 3.19%, and the damage rate does not exceed 0.19%. This study can provide a reference for the design and optimization of high-speed maize seeding devices. Full article

To address issues in traditional vegetable transplanter planting mechanisms such as poor hole-forming quality and low seedling uprightness, a seven-bar linkage planting mechanism with posture compensation of seedling entering soil was designed. By establishing a mathematical model of the planting mechanism and developing visual auxiliary optimization software, the optimal mechanism parameters for the best planting trajectory were determined. A DEM–MBD (Discrete Element Method and Multibody Dynamics) coupling simulation model of planting mechanism-soil-seedlings was established. The planting frequency, opening width, and opening time of the planter were used as factors, and the soil backflow and seedling uprightness were used as evaluation indicators. A quadratic regression orthogonal rotation combination simulation test was carried out. The regression model was established using Design-Expert 12.0 software to analyze the influence of various factors on the indicators. Response surface methodology was simultaneously applied for comprehensive optimization of the influencing factors. The optimal parameter combination obtained was as follows: planting frequency 57 plants/min, opening width 48.5 mm, opening time 0.76 s, corresponding to a soil backflow of 0.67 and seedling uprightness of 80.35°. Field tests were conducted to verify the following mechanism: the soil backflow was 0.64, and the seedling uprightness was 78.49°, which were 4.47% and 2.31% different from the regression model optimization results, respectively. The error variation was small, indicating that the simulation results were effective and the mechanism design was reasonable. This study provides a reference for the development of high-quality and efficient vegetable transplanters. Full article