Search Results (61)

By greatly increasing automation, accuracy, and flexibility at every step of the additive manufacturing process, from design and production to quality assurance, artificial intelligence (AI) is revolutionizing the 3D printing industry. The integration of AI algorithms into 3D printing systems enables real-time optimization of print parameters, accurate prediction of material behavior, and early defect detection using computer vision and sensor data. Machine learning (ML) techniques further streamline the design-to-production pipeline by generating complex geometries, automating slicing processes, and enabling adaptive, self-correcting control during printing—functions that align directly with the principles of Industry 4.0/5.0, where cyber-physical integration, autonomous decision-making, and human–machine collaboration drive intelligent manufacturing systems. Along with improving operational effectiveness and product uniformity, this potent combination of AI and 3D printing also propels the creation of intelligent manufacturing systems that are capable of self-learning. This confluence has the potential to completely transform sectors including consumer products, healthcare, construction, and aerospace as it develops. This comprehensive review explores how AI enhances the capabilities of 3D printing, with a focus on process optimization, defect detection, and intelligent control mechanisms. Moreover, unresolved challenges are highlighted—including data scarcity, limited generalizability across printers and materials, certification barriers in safety-critical domains, computational costs, and the need for explainable AI. Full article

The search for higher efficiency in agribusiness supports the adoption of digital tools and Lean Production principles in agricultural spraying, a crucial operation for crops. Spraying is essential to ensure yield, quality, cost efficiency, and environmental protection. This study analyzed operational data from self-propelled sprayers in soybean and corn fields, classifying hours, calculating efficiencies, and applying statistical process control. Efficiencies were investigated by combining Lean Production principles with CAN-based digital monitoring, which enabled the identification of non-value-adding activities and supported the real-time management of spraying operations. The results showed that productive time accounted for 41.2% of total recorded hours, corresponding to effective operation and auxiliary tasks directly associated with the execution of spraying activities. A high proportion of unrecorded hours (21.2%) was also observed, reflecting discrepancies between administrative work schedules and machine-logged data. Additionally, coefficients of variation for operational speed and fuel consumption were 12.1% and 24.0%, respectively. Correcting special causes increased work capacity (4.9%) and reduced fuel consumption (0.9%). Economic simulations, based on efficiencies, operating parameters of the sprayer, and cost indicators, indicated that increasing scale reduces costs when installed capacity is carefully managed. Integrating telemetry with Lean Production principles enables real-time resource optimization and waste reduction. Full article

The design objectives for the overall parameters of the hydrogen-powered self-propelled plant protection machine are multiple, and the constraints are complex, making it difficult for single-objective optimization methods to achieve the optimal design. This paper designed the objective function with the goal of optimizing the full-cycle cost and system volume of the energy system. By analyzing the structural characteristics of the power system of the self-propelled plant protection machine, the optimization parameters were determined. A constraint model was developed by studying the operational performance of the self-propelled plant protection machine. The multi-objective particle swarm optimization algorithm was used to derive the multi-objective optimization algorithm for the power system parameters of the hydrogen-powered self-propelled plant protection machine. Parameter optimization and dynamic simulation were carried out using the Matlab/Simulink (2023a) platform, and the results of the designed optimization scheme were compared with the single-objective optimization scheme: the full-cycle cost and system volume decreased by 15.8% and 17.6%, respectively. Both optimization schemes are capable of meeting the plant protection operation load requirements. The fuel cell output efficiency and battery efficiency increased by 15.3% and 10.1%, respectively. The hydrogen consumption of the fuel cell, the equivalent hydrogen consumption of the battery, and the equivalent hydrogen consumption of the system decreased by 10.5%, 13.8%, and 10.8%, respectively. The design conducted performance tests on the prototype of the hydrogen-powered plant protection machine, and the results showed that the operational performance indicators, system equivalent hydrogen consumption, and simulation values had an absolute mean error of 2.418, verifying the optimization method. Full article

To address the issues of low efficiency, high cost of manual harvesting, and the lack of mechanized harvesting technology and equipment for high-stem Chrysanthemum coronarium, a self-propelled orderly harvester was designed to perform key harvesting operations such as row alignment, clamping and cutting, orderly conveying, and collection. Based on the analysis of agronomic requirements for cultivation and mechanized harvesting needs, the overall structure and working principle of the machine were described. Meanwhile, the key components such as the reciprocating cutting mechanism and orderly conveying mechanism were structurally designed and theoretically analyzed. The main structural and operating parameters of the harvester were determined based on the geometric and kinematic conditions of high-stem Chrysanthemum coronarium during its movement along the conveying path, as well as the mechanical model of the conveying process. In addition, a three-factor, three-level Box-Behnken field experiment was also conducted with the experimental factors including the machine’s forward, cutting, and conveying speed, and evaluation indicators like harvesting loss rate and orderliness. A second-order polynomial regression model was established to analyze the relationship between the evaluation indicators and the factors using the Design-Expert 13 software, which revealed the influence patterns of the machine’s forward speed, reciprocating cutter cutting speed, conveying device speed, and their interaction influence on the evaluation indicators. Moreover, the optimal parameter combination, obtained by solving the optimization model for harvesting loss rate and orderliness, was forward speed of 260 mm/s, cutting speed of 250 mm/s, and conveying speed of 300 mm/s. Field test results showed that the average harvesting loss rate of the prototype was 4.45% and the orderliness was 92.57%, with a relative error of less than 5% compared to the predicted values. The key components of the harvester operated stably, and the machine was capable of performing cutting, orderly conveying, and collection in a single pass. All performance indicators met the mechanized orderly harvesting requirements of high-stem Chrysanthemum coronarium. Full article

Aiming at key issues in harvesting film-covered potatoes in hilly and mountainous areas—incomplete residual film collection, poor potato–soil separation, and high damage from potato-collecting devices—this study developed a crawler self-propelled potato harvester suitable for these regions. This study first expounds the overall structure and working principle of the potato harvester and then conducts principal analysis and structural design for key components (film-collecting device, digging device, primary conveying and separating device, secondary conveying and separating device, and intelligent potato-collecting device) from the perspectives of material force and movement. Finally, field performance tests were carried out in Huangzhong County, Xining City, Qinghai Province. The test results show that the machine can achieve an operation effect with a potato harvest loss rate of 2.4%, a potato damage rate of 1.4%, an impurity content rate of 2.8%, a skin-breaking rate of 2.7%, and a residual film cleaning rate of 89.6%, meeting the potato harvesting needs of this region. The lightweight self-propelled crawler potato harvester designed in this paper can realize functions such as residual film collection, potato–soil vibration separation, manual auxiliary sorting, and intelligent potato boxing, providing technical and equipment references for the harvesting of film-covered potatoes in complex terrain areas. Full article

During headland manoeuvres of agricultural tractors, self-propelled machines, and autonomous agricultural vehicles, it is crucial not only to achieve the required working width but also to minimise the number of turns, path length, and time to reach the next field pass. The shortest trajectories can be obtained using Dubins curves or Reeds–Shepp paths. However, traversing such paths at constant velocity is only theoretically feasible. At the junctions between path segments, either the vehicle must stop or the steering angle must change at an infinite rate. These points exhibit abrupt changes in acceleration components, resulting in infinite jerk. This study presents the use of transition curves for executing U-turns and Ω-turns during headland manoeuvres. Implementing curves with gradually varying curvature ensures smooth transitions between trajectory segments, reducing sudden direction changes and improving motion dynamics. The curvature and tangent angle are defined using trigonometric functions. For the designed trajectory, kinematic parameters, including wheel steering angles, were determined for two models of agricultural tractors. The results provide a solid foundation for future research on refining transition curve models and integrating the proposed solutions with agricultural vehicle control systems. Full article

To address the frequent failure of anti-falling devices in inclined shaft tunnel boring machines caused by cyclic loading and fatigue during construction, this study proposes an optimized self-responsive anti-falling device design. Based on the operational conditions of the “Tianyue” tunnel boring machine, a three-dimensional model was constructed using SolidWorks. Finite element static analysis was employed to validate structural integrity, revealing a maximum stress of 461.19 MPa with a safety factor of 1.71. Explicit dynamic simulations further demonstrated the dynamic penetration process of propellant-driven telescopic columns through concrete lining walls, achieving a penetration depth exceeding 500 mm. The results demonstrate that the device can respond to falling signals within 12 ms and activate mechanical locking. The Q690D steel structure exhibits a deformation of 5.543 mm with favorable stress distribution, meeting engineering safety requirements. The energy release characteristics of trinitrotoluene propellant and material compatibility were systematically verified. Compared to conventional hydraulic support systems, this design offers significant improvements in response speed, maintenance cost reduction, and environmental adaptability, providing an innovative solution for fall protection in complex geological environments. Full article

Occupational Health and Safety (OHS) in agriculture is a critical concern worldwide, with self-propelled machinery accidents, particularly tip/roll-overs, being a leading cause of injuries and fatalities. In such a context, while great attention has been paid to machinery safety improvement, a major challenge is the lack of studies addressing the analysis of the work environment to provide farmers with precise information on field slope steepness. This information, merged with an awareness of machinery performance, such as tilt angles, can facilitate farmers in making decisions about machinery operations in hilly and mountainous areas. To address this gap, the Italian Compensation Authority (INAIL) launched a research programme to integrate georeferenced slope data with the tilt angle specifications of common self-propelled machinery, following EN ISO 16231-2:2015 standards. This study presents the first results of this research project, which was focused on vineyards in the alpine region of the Autonomous Province of Trento, where terrestrial LiDAR technology was used to analyze slope steepness. The findings aim to provide practical guidelines for safer machinery operation, benefiting farmers, risk assessors, and manufacturers. By enhancing awareness of tip/roll-over risks and promoting informed decision-making, this research aims to contribute to improving OHS in agriculture, particularly in challenging terrains. Full article

To address the issues of large turning radius, low mechanical compression bale density, and high requirements for knotters in existing towed straw balers, a self-propelled straw-harvesting and -baling machine has been developed. The machine can perform multiple tasks in one pass, including the harvesting, chopping, dust removal, compression bale, and net-wrapping of corn straws. By utilizing a hydraulic closed-compression system, the straw naturally binds together and is wrapped in netting, eliminating the need for knotters, thereby reducing operational costs and increasing bale density. This study focused on designing a baling compression and net-wrapping device, calculating the parameters of the compression hydraulic cylinder and hydraulic system, designing the control system, and conducting field tests. The results show that the finisher baling rate reached 99%, the regular bale rate reached 100%, the bale density was 264.77 kg/m³, the bale drop resistance rate was 94%, and the pure working hour productivity was 4.03 t/h. This research provides a reference for the design of straw-harvesting balers. Full article

In response to the issues of high energy consumption, limited functionality, and uneven soil–fertilizer mixing in mechanical operations for trenching and fertilizing in hilly orchards, this study proposes the design of a crawler-type self-propelled machine, integrating three main functions: trenching, fertilizing, and soil covering. The key components of the trenching device, fertilizing device, and soil-covering device were designed. Three fertilizing simulation models (pre-plant, mid-plant, and post-plant) were established using EDEM discrete element software. The soil–fertilizer mixing effects under each mode were analyzed, with results indicating that the post-plant fertilizing mode better meets the soil–fertilizer mixing requirements for deep organic fertilizer application. Using trenching speed, forward speed, and bending angle of the trenching knife as experimental factors, with operating power consumption and soil–fertilizer mixing uniformity as evaluation indicators, a Box–Behnken experiment was conducted to optimize the parameters of the trenching and fertilizing components. A regression model was established to analyze the interaction between experimental factors and indicators. The optimal operational parameter combination was determined as follows: trenching speed of 265.03 r/min, forward speed of 0.40 m/s, and bending angle of trenching knife of 130°. Under these parameters, the trenching power consumption and soil–fertilizer mixing uniformity were 1.74 kW and 77.15%, respectively. Orchard verification tests on the machine showed that under the optimal parameters, the relative errors in trenching power consumption and soil–fertilizer mixing uniformity between the field tests and simulations were 7.40% and 4.50%, respectively. These results meet the agronomic requirements for trenching and fertilizing, and the study provides valuable references for the application of related technologies in orchard trenching and fertilizing operations. Full article

Chemically powered micro/nanorobots (CPMNRs) are self-propelling artificially engineered materials or machines designed with micro-to-nano precision, inspired by the self-migration of biomolecules and microorganisms. CPMNRs convert chemical or external energy into mechanical motion, overcoming forces like Brownian diffusion and viscosity. They are created using top-down or bottom-up approaches for applications in chemo-/biosensing, environmental remediation, molecular imaging, and drug delivery. As self-mixing of contaminated water accelerates the remediation process, CPMNRs are preferred as an ideal choice for environmental applications. Recent advancements in multimodal propulsion technologies, material engineering, and surface modifications have significantly enhanced the capabilities of CPMNRs, enabling them to navigate complex environments and interact with contaminants at the molecular level. This review highlights the latest developments in chemical-driven CPMNRs, focusing on their use in environmental monitoring, pollutant detection, and remediation of heavy metals, microplastics, and organic contaminants in water and soil. It also discusses prospects, sustainability of chemical fuels, environmental biocompatibility, and scalability for large-scale deployment. Full article

The characteristics of soil ditching and backfilling are crucial for orchard ditching operations. However, experimentally investigating the dynamic ditching and backfilling process is currently not feasible. To address this issue, the 3DGZ-50A self-propelled orchard ditching machine (SPODM) was designed using a modular concept, incorporating three types of ditching cutter discs (01#, 02#, and 03#). These discs were designed, trial-manufactured, and tested in orchard ditching experiments. A corresponding simulation model was also constructed using EDEM 2022 software. This study evaluated the ditching and backfilling process, analyzing the performance of the three cutter discs through experimental and simulation methods. Results indicated that the 01# and 02# cutter discs created V-shaped furrows, whereas the 03# cutter disc formed an arc-shaped furrow. The relative errors in the final furrow depth (D_f) and width (W_f) between experimental and simulated results were 30.70% and 8.61%, respectively, while those in the maximum furrow depth (D_m) and width (W_m) were 9.44% and 3.00%. These minor relative errors confirmed the accuracy of the simulation model. Regarding maximum power consumption, the 01# cutter disc used 86.3% of the power consumed by the 02# cutter disc and 85.1% of that used by the 03# cutter disc. During the ditching process, the blades penetrated the soil to create the maximum furrow cross-section, which then gradually decreased due to backfilling. Both simulation and test results demonstrated that the 01# cutter disc performed best, achieving a maximum furrow cross-sectional area (46.70%), minimum final surface furrow cross-sectional area (6.04%), and lower power consumption (31.03 kW). This study provides equipment for ditching operations in low-height close-planting orchards in northern China. Full article

To address the inadequacies of mechanized potato-harvesting equipment on challenging terrains like hills, mountains, and small fields, a lightweight and simple self-propelled crawler potato combine harvester was developed based on the agronomic and harvesting requirements of potato cultivation. The machine consists of key components including a depth-limited soil-crushing device, an auxiliary feeding device, an excavation device, a rubber rod separation device, and a ton bag sorting device. It offers technical advantages such as a lightweight structure, auxiliary feeding and conveying, and manual assistance in sorting ton bags. The key components, such as the auxiliary feeding device, depth-limiting soil-crushing device, and rubber rod separation device, were analyzed theoretically to determine the relevant structures and parameters. Through initial harvesting performance tests, the separation screen line speed, vibration frequency, and device inclination angle were identified as the experimental factors. Evaluation indicators such as potato bruise rate, skin breakage rate, loss rate, and impurity content were chosen, and a three-factor, three-level Box–Behnken optimization test was conducted. The results indicated that with a separation screen line speed of 1 m/s, vibration frequency of 8 Hz, and device inclination angle of 30°, the potato damage rate during harvesting was 1.318%, the skin breakage rate was 1.825%, the loss rate was 2.815%, and the impurity rate was 2.736%. Field tests with the same parameters showed that the potato damage rate, skin breakage rate, loss rate, and impurity rate of the harvester were 1.357%, 1.853%, 2.86%, and 2.748%, respectively, meeting relevant industry technical standards. This research can serve as a reference for enhancing the harvesting performance of potato combine harvesters and ton bag sorting technology. Full article

The squirrel cage induction generator or SCIG (Squirrel Cage Induction Generator) belongs to the family of induction machines, which are currently used as the most common electrical machines. The use of power electronic converter systems along with advanced control vector algorithms allows for the implementation of the effective operation of squirrel cage generators in various conditions. Up to now, there are a few practical realizations of squirrel cage generators, which are installed on board the vessels; mostly, these generators act as shaft generators, and it originates from the rules that require self-excitement of main electrical generators, acting as an immediate ready-to-use voltage source. In this article, we present a solution that utilizes an SCIG that operates with varying rotational speed as a shaft generator but can also act as an emergency propeller drive in case of main combustion engine failure. The main achievement of the presented work was the creation of a control table prepared for real-time software of the machine-side inverter. The data for the table were collected during the experimental research, and such a setup allowed us to use a DTC-controlled SCIG as a generator that rotated with variable speed and under changing load. Full article

The self-propelled straw pickup baler in agricultural work is responsible for collecting and compressing straw to facilitate transportation and storage, while reducing waste and environmental pollution. Like other agricultural equipment, the straw pickup baler is a complex mechanical system. During operation, its excitation characteristics under multi-source stimuli and the coupling characteristics of various components are not yet clear. This paper analyzed the excitation mechanics property of each component of the self-propelled straw pickup baler and established balance equations. Based on the balance equations, the coupling characteristics of the structures were studied. Through experiments collecting excitation signals from multiple devices under different operating conditions, the vibration excitation signals of each component were obtained. The experiments revealed that the excitation and coupling signals in the Z direction are particularly evident. Based on experiments, the effective Z-direction vibration signal value on the left front of the chassis exceeds 7 m·s², while on the right front it increases from 1.995 m·s² to 7.287 m·s², indicating the most intense vibration direction. It was also found that, at the driver’s cab, the effective Z-direction vibration signal values at two response points, 11 and 12, both exceed 7 m·s². The data indicate significant vibrations occur in both the longitudinal and vertical directions. Using the Signal Analyzer module in MATLAB for signal processing, it was found that the prominent filtered signals consist of combustion excitation harmonics and continuous low-frequency vibrations from the compression mechanism. The periodic reciprocating compression motion of the crank-slider mechanism causes sustained impacts on the frame, leading to periodic changes in the vibration amplitude of the chassis. Thus, the vibration reduction of the compression mechanism’s periodic motion is key to reducing the overall vibration of the machine. Full article