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Abstract A methodology combining physical experiments with simulation was employed to acquire contact parameters of sandy soil precisely for planting tiger nuts in the desert area of Xinjiang. The stacking angle under different parameter combinations was applied as a response value. Through the Plackett–Burman test, several factors that have a significant influence were determined. The steepest ascent test was conducted to establish the finest scope of values for these parameters. The stacking angle was considered the response variable, and non-linear tools were used to optimize these parameters for simulation. The findings showed that applying response surface methodology (RSM) resulted in a relative error of 1.24%. In the case of BP-GA, the relative error compared to the physical test value was 0.34%, while for BP, it was 2.18%. After optimization using Wavelet Neural Network (WNN), the relative error was reduced to only 0.15%. Results suggest that WNN outperforms the RSM model, and the sandy soil model and parameters generated using WNN can be effectively utilized for discrete element simulation research.

Tea bud detection is the first step in the precise picking of famous teas. Accurate and fast tea bud detection is crucial for achieving intelligent tea bud picking. However, existing detection methods still exhibit limitations in both detection accuracy and speed due to the intricate background of tea buds and their small size. This study uses YOLOv5 as the initial network and utilizes attention mechanism to obtain more detailed information about tea buds, reducing false detections and missed detections caused by different sizes of tea buds; The addition of Spatial Pyramid Pooling Fast (SPPF) in front of the head to better utilize the attention module’s ability to fuse information; Introducing the lightweight convolutional method Group Shuffle Convolution (GSConv) to ensure model efficiency without compromising accuracy; The Mean-Positional-Distance Intersection over Union (MPDIoU) can effectively accelerate model convergence and reduce the training time of the model. The experimental results demonstrate that our proposed method achieves precision (P), recall rate (R) and mean average precision (mAP) of 93.38%, 89.68%, and 95.73%, respectively. Compared with the baseline network, our proposed model’s P, R, and mAP have been improved by 3.26%, 11.43%, and 7.68%, respectively. Meanwhile, comparative analyses with other deep learning methods using the same dataset underscore the efficacy of our approach in terms of P, R, mAP, and model size. This method can accurately detect the tea bud area and provide theoretical research and technical support for subsequent tea picking.

Aiming at solving the problems of the high cost of manual pulling, the low reliability of existing pulling devices, and the high breaking rates and high leakage rates in the process of cotton stalk reuse after removal from the field in the Xinjiang cotton area, a soil-loosening and root-cutting cotton stalk pulling and gathering machine was researched and designed; a root-cutting force model was established; the key parameters of the V-shaped root-cutting knife were calculated and optimized; and the ranges of the slide cutting angle, the cutting-edge angle, and the soil entry angle were determined. A shoveling process simulation of the V-shaped root-cutting knife and the root–soil complex was constructed, and the working mechanism of the V-shaped root-cutting knife was clarified. In order to verify the reliability and operation performance of the V-shaped root-cutting knife, the slide cutting angle, the cutting-edge angle, and the soil entry angle were used as the test factors, and a response surface test with three factors and three levels was carried out with the root-breaking force and the mean value of the cutting resistance as the test indices. The test results were analyzed by variance analysis, and the significant factors influencing the root-breaking force in descending order were the slide cutting angle, cutting-edge angle, and soil entry angle. The degrees of influence on the mean value of the cutting resistance were ordered as follows: slide cutting angle, soil entry angle, and cutting-edge angle. In order to make the V-shaped root-cutting knife achieve the optimal working state, the parameters of the test indices were optimized, and the optimal design parameters of the V-shaped root-cutting knife were set as follows: the slide cutting angle was 48.3°, the cutting-edge angle was 43.4°, and the soil entry angle was 26.2°. The field uprooting test showed that the average pass rate of root breakage was 94.8% and the average pull-out rate of cotton stalks was 93.2%. This study provides theoretical guidance for the development of a root-breaking mechanism for cotton straw harvesters.

To address the problem of large tractive resistance in traditional subsoiling methods, this paper designed a pulse-type gas explosion subsoiler, as well as an air-blown double-ended chisel type subsoiling shovel and a conduit. The mathematical equation of the influence of the structural parameters of the subsoiler on the groove profile is established. The EDEM 2022 software was used to simulate the subsoiling operation process. The soil disturbance law of the chisel subsoiler was analyzed by the change of soil particle velocity. The optimum value interval of quadratic regression orthogonal rotation combination test factors was determined by using the steepest climb test, with specific tillage resistance and filling power as evaluation indicators. Based on the Box–Behnken design test, a second-order regression model of response value and significance parameter was obtained, and an optimal combination was found by optimizing the significance parameter. The effects of subsoiling air pressure, pulse width and pulse interval on evaluation indicators were analyzed by the response surface method; the test results show that when the air pressure was 0.8 MPa, the pulse width was 0.17 s and the pulse interval was 0.12 s, and the specific tillage resistance was 0.4421 N/mm2 and the filling power was 18.5%; a comparative test between the pulse-type gas explosion subsoiler and a continuous gas explosion subsoiler was carried out, and the specific tillage resistance was reduced by 12.2% and the filling power was reduced by 10.5%; the comparative test shows that the pulse-type gas explosion subsoiler has smaller tractive resistance per unit area and smaller disturbance to soil. The research results provide a theoretical basis and reference for the optimization and improvement of gas explosion subsoilers.

Addressing the issues of the sand cat swarm optimization algorithm (SCSO), such as its weak global search ability and tendency to fall into local optima, this paper proposes an improved strategy called the multi-strategy integrated sand cat swarm optimization algorithm (MSCSO). The MSCSO algorithm improves upon the SCSO in several ways. Firstly, it employs the good point set strategy instead of a random strategy for population initialization, effectively enhancing the uniformity and diversity of the population distribution. Secondly, a nonlinear adjustment strategy is introduced to dynamically adjust the search range of the sand cats during the exploration and exploitation phases, significantly increasing the likelihood of finding more high-quality solutions. Lastly, the algorithm integrates the early warning mechanism of the sparrow search algorithm, enabling the sand cats to escape from their original positions and rapidly move towards the optimal solution, thus avoiding local optima. Using 29 benchmark functions of 30, 50, and 100 dimensions from CEC 2017 as experimental subjects, this paper further evaluates the MSCSO algorithm through Wilcoxon rank-sum tests and Friedman’s test, verifying its global solid search ability and convergence performance. In practical engineering problems such as reducer and welded beam design, MSCSO also demonstrates superior performance compared to five other intelligent algorithms, showing a remarkable ability to approach the optimal solutions for these engineering problems.

This study aimed to enhance the efficiency of tiger nut combine harvesters by reducing impurity and loss rates during processing. Scholars focused on analyzing the composition and suspension speed of the bean mixture, leading to the development of a wind-screen impurity-removal method. The wind-screen-type bean-separation device was designed with a cross-flow fan, louver screen, frame, and driving mechanism. Theoretical analysis was employed to discuss the motion characteristics and behavior of the sieve body and material, thereby revealing the screening dynamics of tiger nuts and impurities. Factors such as crank radius, crank speed, and fan speed were identified as crucial for optimizing separation performance. Initial single-factor tests helped narrow down the range of influencing factors. Subsequently, a three-factor, three-level Box–Behnken test was conducted with crank radius, crank speed, and fan speed as variables and impurity rate and loss rate as evaluation indexes. This led to the establishment of a multiple regression equation linking these factors to the evaluation indexes. Through response surface analysis and multi-objective optimization using the regression model, the optimal operational parameters for the device were determined: crank radius of 45 mm, crank speed of 497 r/min, and the fan speed of 1100 r/min. Theoretical calculations predicted an impurity rate of 2.42% and a loss rate of 0.51%. Verification tests confirmed these findings, showing an average impurity rate of 2.53% and a loss rate of 0.56%, which met the mechanized harvesting standards for tiger nuts. Overall, this study introduces a novel method and technical framework for effectively separating tiger nuts from impurities, thereby advancing the mechanization of tiger nut harvesting processes.

To tackle problems such as the difficult separation from sand and the high power consumption of tiger nut harvesting in the sandy areas of Xinjiang, a conveying and separating device for tiger nut harvesters was designed. The axial and radial migrations of materials under screw action and the separation process of materials under vibratory action were analyzed dynamically. A simulation analysis was carried out on the conveying and separating process based on EDEM software. The migration trajectories of tiger nuts and sand particles were extracted, the displacement variations of sand particles on the X-axis, Y-axis, and Z-axis were analyzed in the action area of the screen-cleaning spike teeth and the screw action area, respectively, and the conveying and separation law of the tiger nut harvest mixture was clarified. With key parameters such as the screw velocity ratio, amplitude, vibration frequency, and machine operation velocity as test factors, and with the sand removal rate, crushing rate, and power consumption as test evaluation indicators, a four-factor, five-level orthogonal central composite test design was implemented. The test results were analyzed via the regression variance analysis method, and relation models between variable factors and evaluation indicators were constructed. The test results show that under the combined conditions of a screw velocity ratio of 0.88, an amplitude of 4.7 mm, a vibration frequency of 7.5 Hz, and a machine operation velocity of 0.92 km/h, the sand removal rate is 90.40%, the crushing rate is 1.66%, and the power consumption is 2.24 kW in theory. The optimized results were verified by tests. The sand removal rate was 88.92%, the crushing rate was 1.71%, the total power consumption was 2.29 kW, and the errors from the predicted values were 1.6%, 3.0%, and 2.2%, respectively, meeting the requirements for tiger nut harvesting conveyance and separation. This research can provide support for the development of technology and equipment for mechanized harvesting of tiger nuts in the sandy areas of Xinjiang.

To improve the accuracy of the discrete element research, physical and simulation experiments were used to calibrate the cotton stalk contact parameters. Based on the stalk-stalk and stalk-steel contact mechanics, the parameters were measured in physical experiments, and the discrete element simulation software was used to build the stalk model. In the simulation process, the Plackett-Burman experiment was used to screen three significant factors from six initial factors. The steepest Plackett-Burman experiment was used to determine the optimal interval of the significant factors. A second-order regression model of the significant factors and the angle of repose was established according to the Central Composite design experiment. The best parameter combination of the significant factors was then obtained: the coefficient of static friction on stalk-steel contact was 0.31, the coefficient of static friction on stalk-stalk contact was 0.62, and the coefficient of rolling friction on stalk-stalk contact was 0.02. The relative error between the physical angle of repose and the simulated angle was 3.27%, indicating that it is feasible to apply the simulation experiment instead of the physical one. It offers insights into cotton stalk contact parameter settings and film-stalk separation in the simulation.

Efficient furrow fertilization is extremely critical for fertilizer utilization, fruit yield, and fruit quality. The precise determination of trench quality necessitates the accurate measurement of its characteristic parameters, including its shape and three-dimensional structure. Some existing algorithms are limited to detecting only the furrow depth while precluding the tridimensional reconstruction of the trench shape. In this study, a novel method was proposed for three-dimensional trench shape reconstruction and its parameter detection. Initially, a low-cost multi-source data acquisition system with the 3D data construction method of the trench was developed to address the shortcomings of single-sensor and manual measurement methods in trench reconstruction. Subsequently, the analysis of the original point cloud clarified the “coarse-fine” two-stage point cloud filtering process, and then a point cloud preprocessing method was proposed based on ROI region extraction and discrete point filtering. Furthermore, by analyzing the characteristics of the point cloud, a random point preselection condition based on the variance threshold was designed to optimize the extraction method of furrow side ground based on RANSAC. Finally, a method was established for extracting key characteristic parameters of the trench and trench reconstruction based on the fitted ground model of the trench side. Experimental results demonstrated that the point cloud pretreatment method could eliminate 83.8% of invalid point clouds and reduce the influence of noise points on the reconstruction accuracy. Compared with the adverse phenomena of fitting ground incline and height deviation of the original algorithm results, the ground height fitted by the improved ditch surface extraction algorithm was closer to the real ground, and the identification accuracy of inner points of the ground point cloud was higher than that of the former. The error range, mean value error, standard deviation error, and stability coefficient error of the calculated ditch width were 0 ~ 5.965%, 0.002 m, 0.011 m, and 0.37%, respectively. The above parameters of the calculated depth were 0 ~ 4.54%, 0.003 m, 0.017 m, and 0.47%, respectively. The results of this research can provide support for the comprehensive evaluation of the quality of the ditching operation, the optimization of the structure of the soil touching part, and the real-time control of operation parameters.

Accurate road extraction and recognition of roadside fruit in complex orchard environments are essential prerequisites for robotic fruit picking and walking behavioral decisions. In this study, a novel algorithm was proposed for unstructured road extraction and roadside fruit synchronous recognition, with wine grapes and nonstructural orchards as research objects. Initially, a preprocessing method tailored to field orchards was proposed to reduce the interference of adverse factors in the operating environment. The preprocessing method contained 4 parts: interception of regions of interest, bilateral filter, logarithmic space transformation and image enhancement based on the MSRCR algorithm. Subsequently, the analysis of the enhanced image enabled the optimization of the gray factor, and a road region extraction method based on dual-space fusion was proposed by color channel enhancement and gray factor optimization. Furthermore, the YOLO model suitable for grape cluster recognition in the wild environment was selected, and its parameters were optimized to enhance the recognition performance of the model for randomly distributed grapes. Finally, a fusion recognition framework was innovatively established, wherein the road extraction result was taken as input, and the optimized parameter YOLO model was utilized to identify roadside fruits, thus realizing synchronous road extraction and roadside fruit detection. Experimental results demonstrated that the proposed method based on the pretreatment could reduce the impact of interfering factors in complex orchard environments and enhance the quality of road extraction. Using the optimized YOLOv7 model, the precision, recall, mAP, and F1-score for roadside fruit cluster detection were 88.9%, 89.7%, 93.4%, and 89.3%, respectively, all of which were higher than those of the YOLOv5 model and were more suitable for roadside grape recognition. Compared to the identification results obtained by the grape detection algorithm alone, the proposed synchronous algorithm increased the number of fruit identifications by 23.84% and the detection speed by 14.33%. This research enhanced the perception ability of robots and provided a solid support for behavioral decision systems.

Aiming at the problems of low uniformity and utilization rate in the traditional deep application method of orchard manure, a soil–fertilizer collision mixing and mulching device was designed. The ditching mechanism, the structure of the soil divider, and the fertilizer delivery auger were analyzed and designed. Furthermore, with the rotational speed of the cutter and auger and the deflection angle of the soil divider as factors, as well as the uniformity of soil–fertilizer mixing and mulching as evaluation indexes, the discrete element simulation tests were conducted. The simulation results showed that when the turret speed, the stirrer speed and the soil separator deflection angle were 140 r/min, 146 r/min and 22°, the mixing uniformity and mulching uniformity were the highest, which was 88.35% and 96.86%, respectively. Based on the optimal parameters, the field test was conducted, and the soil–fertilizer mixing uniformity was 87.02%, with a relative error of 1.33% compared with the simulation test results. The relative error of 94.37% of mulch uniformity is 2.49%, which indicates that the simulation optimization results are reliable and the mixing performance of the device is good and can meet the requirements of soil–fertilizer mixing operation. The results of this study can provide an important reference for the design of the soil and fertilizer mixing machine.

Green, healthy and sustainable development is the development direction of China’s agriculture, and stable fertilizer has become the first choice for orchard fertilizer. In this paper, in order to improve the working performance of the combined fertilizer application device of 2KF-30 type orchard stable fertilizer deep applicator, the matching degree of the combined operation of scraper and auger was taken as the research objective, and theoretical analysis, numerical simulation, and experimental verification were combined to carry out the research. Applying fuzzy theory, the comprehensive qualified rate weighted by the uniformity of fertilization and the qualified rate of fertilization was proposed as the evaluation index. The scraper shaft speed, scraper space, spiral conveyor speed, and spiral conveyor pitch were selected as the test factors, and the comprehensive qualified rate of fertilization for the combined fertilization device was taken as the evaluation index. The test design was carried out by single-factor and response surface method tests, and numerical simulations were conducted by discrete element software to analyze the optimal combination of fertilizer application parameters. The test results were analyzed based on the numerical simulation of discrete element software. The testbed was set up to verify the above optimal results. The results showed that the maximum error between the physical test and the numerical simulation was 8.67%, the minimum error was 1.75% and the overall mean error between the physical test value of the combined fertilizer application pass rate and the predicted value of the quadratic regression equation was 5.99%, which can meet the operational performance requirements of the fertilization device. The research results can provide a theoretical basis for the design and improvement of the deep fertilizing machine for orchard manure.

The accuracy of the material parameter settings directly affects the reliability of the results of the discrete element method simulation. It is necessary to calibrate the relevant parameters to obtain accurate discrete element simulation results when separating the cotton stalk particles from the residual film after crushing. The repose angle of the chopped cotton stalk particles was used as the response value to calibrate the contact parameters between particles. Physical tests measured the intrinsic particle and contact parameters between the cotton stalk particles and the contact material, which provided data for the simulation tests. According to the biological structure characteristics of cotton stalk, the discrete element method model of cotton stalk particles was constructed by bonding the elements of nonequal-diameter basic particles. Based on the response surface methodology, the stacking test of particles was simulated. The response model between the contact parameters and repose angle was established, and the effect law of the single-factor terms and interaction terms on the repose angle was analyzed. The optimal combination of contact parameters was obtained through the single-objective and multi-variable optimization methods. Finally, the contact parameter combination was verified by a simulation test of the repose angle. The results showed that the average relative error of the repose angle between the simulation test and the physical test was 1.04%, which verified the accuracy of the calibrated contact parameters and the reliability of the simulation test. These parameters provide a basis for the discrete element simulation study of cotton stalk motion in the separation process of cotton stalks and residual film and the subsequent gas–solid coupling simulation research.

The friction characteristic parameters of cotton stalks are important basic physical parameters required to establish the crushing mechanics model and study the separation machinery of film residue mixtures. In this paper, the friction characteristics of cotton stalks were studied using response surface methodology, and the influence of the variation in contact materials, sampling location, and moisture content on the static sliding friction coefficient (μs) and stable static rolling angle (φs) were analyzed. The results show that the contact materials, sampling location, and moisture content significantly influence the μs and φs. When the contact material is cotton stalk bark, the μs and φs values of cotton stalks are maximum. When the sampling location of the cotton stalk changes from top to bottom, the μs increases and φs decreases, respectively, while the moisture content has an opposite influence on the μs and the φs. The model coefficient of the μs and the φs indicates that the influencing factors have a high degree of explanation for the influence on the μs and φs. This study on the friction characteristics of cotton stalks can provide theoretical references and basic parameters for the separation technology research and equipment development of film residue mixtures.

The multi-scale model is key to the evaluation of shear or compression mechanical properties of jujube branches at the microlevel. In this study, multi-scale models of the microstructure of jujube branches, namely, the natural model and the artificially simplified model, were built using computed tomography and Python. The equivalent compression and shear properties of the microstructure were predicted by the finite element method. The prediction results of the artificially simplified model were compared with those of the natural model, and the prediction deviation of the artificially simplified model was analyzed. The results showed that the transverse shear modulus obtained by the artificially simplified model was slightly higher than the predicted value of the natural model, with an average deviation of 1.84%. The transverse shear strain energy obtained by the artificially simplified model was lower than the predicted result of the natural model, with a maximum deviation of 5.59%. The cell distribution direction had an important effect on the accuracy of prediction for the transverse elastic modulus, and the deviation was 16.53%, indicating that the further optimization of the cell distribution direction could enhance the prediction accuracy and the effectiveness of the model. The results can be used to evaluate the unit compression or shear mechanical properties of plant stalks with hierarchical structuring and to analyze the quantitative relationship between the microstructure and equivalent mechanical properties.

In order to solve the problems of serious soil reflux and poor stability of ditch depth in the existing ditching organic fertilizer fertilization device in grey desert and loess orchards, rotary tillage theory and software simulation were used to conduct kinematic analysis of soil particles and ditching blade in the ditching process, and meanwhile, modeling and simulation are carried out for sand soil particles by using EDEM software, so as to determine the action mechanism of soil, blade and fairing in ditching process of grey desert and loess. The abstract on this basis, the quadratic orthogonal regression-rotation combination experiment was designed. The soil bin test was carried out by taking the cutter wheel speed, ditching depth and inclination of curved surface as the influencing factors, and the throwing distance and the stability of ditch depth as the test indexes. And it was concluded that the order of the influence of the operating parameters of the ditching device on the soil throwing distance is ditching depth > inclination of curved surface > cutter speed, and the order of the influence on the stability of the ditch depth is ditching depth > cutter speed > Inclination of curved surface. Finally, the optimized operating parameters of the ditching device are as follows: the cutter wheel speed is 119.61 r·min−1, the inclination of curved surface is 30.07°, the ditching depth is 35.52 mm, the soil throwing distance is 57.31, and the stability of ditch depth is 87.43. With these parameters as test objects, 10 groups of single factor tests were carried out to obtain that the soil throwing distance is 58.33, and the stability of ditch depth is 86.51, which were basically consistent with the expected results of the optimization test, and also in line with the relevant agronomic standards.

To improve the accuracy of the discrete element research, physical and simulation experiments were used to calibrate the cotton stalk contact parameters. Based on the stalk-stalk and stalk-steel contact mechanics, the parameters were measured in physical experiments, and the discrete element simulation software was used to build the stalk model. In the simulation process, the Plackett-Burman experiment was used to screen three significant factors from six initial factors. The steepest Plackett-Burman experiment was used to determine the optimal interval of the significant factors. A second-order regression model of the significant factors and the angle of repose was established according to the Central Composite design experiment. The best parameter combination of the significant factors was then obtained: the coefficient of static friction on stalk-steel contact was 0.31, the coefficient of static friction on stalk-stalk contact was 0.62, and the coefficient of rolling friction on stalk-stalk contact was 0.02. The relative error between the physical angle of repose and the simulated angle was 3.27%, indicating that it is feasible to apply the simulation experiment instead of the physical one. It offers insights into cotton stalk contact parameter settings and film-stalk separation in the simulation. [ABSTRACT FROM AUTHOR]

The influence of the variation in water content, sampling location and loading speed on the shearing and across-compression mechanical characteristics of dwarf-denseearly major cotton variety stalks was analysed. The second-order response models of the factors vs. the maximum shear force and critical across-compression failure force were built using the response surface methodology. Besides, the sampling location and water content have a significant influence over the maximum shear force and critical across-compression failure force, especially the sampling location. Both the maximum shear force and critical across-compression failure force reach a theoretical maximum when the water content is 10%, the sampling location is the lower part and the loading speed is 40 mm min-1. When the sampling location is the lower part, optimization is carried out assuming the theoretical minimum of the maximum shear force and critical across-compression failure force as the optimization target. In this case, the loading speed is 20 mm min-1, while the water content is between 30 and 50%. This indicates that the parameter range requires a low power consumption during the crushing of film residue mixtures. The test data can provide some theoretical references for the technical research and equipment development for the crushing of film. [ABSTRACT FROM AUTHOR]

The threshing mixture of Cyperus esculentus (Tiger nut) planted in sandy areas is complex during harvesting, and there are problems of high impurity rate and high cleaning loss rate of the seeds. In this paper, the threshing mixture of Cyperus esculentus is taken as the research object, and the suspension speed of each component is measured to design an “airflow + vibration” sieving device. Use the vector polygon method to explore the law of motion of the vibrating sieve, establish the force model of the seeds on the sieve surface, and analyze the conditions for the seeds to penetrate the sieve. According to the principle of seeds penetrating the sieve and long stalks not penetrating the sieve, the geometric model of sieve blades opening degree adjustment mechanism is constructed. Study of the conditions under which long stalks can be thrown out of the machine. The experiment bench of the cleaning device was built, and the evaluation indexes were the rate of seed impurity and the rate of cleaning loss of the device, and the crank speed, sieve blades opening degree and fan speed were used as the experiment factors to study the influence law of each influencing factor on the evaluation index through single-factor experiment. Using response surface methodology to find the optimal combination of working parameters of the cleaning device. To verify the device’s application on the combine harvester to improve the effectiveness of the cleaning operation of the Cyperus esculentus combine harvester. [ABSTRACT FROM AUTHOR]

As the existing residual film crushing device in Xinjiang cannot directly crush membrane-impurity mixed material, by analyzing the compressive and cutting force characteristics of residual film material layer and cotton stalk, the cutting conditions of mixed materials were obtained, and the method of cutting was determined. A multi-edge toothed cutters was created, and a cutting device was built. It was preliminarily determined that the number of teeth in the cutters was 8, the clearance between the teeth and between the tooth and fixed blade was 3 mm, the speed of the high-speed cutter was 800 r/min, and the speed difference between the high- and low-speed cutters was –300 r/min. Test results show that the ratio of residual film to total residual film sampling mass was (2.22±0.3)%, (19.19±2.02)%, (58.94±3.19)% and (20.65±2.05)%, respectively, when the maximum outer profile size in the range of [0,20) mm, [20,100) mm, [100,500) mm and [500,~) mm. The mass of cotton stalks with lengths of [0,50) mm, [50,100) mm and [100,~) mm accounted for (32.57±1.5)%, (27.77±1.3)% and (39.66±1.75)%, respectively, and the cutting power consumption was (85.41±15.63) kJ. The test results can provide a basis for the subsequent membrane-impurity mixed material cutting technology, as well as some guidance for the separation of it. [ABSTRACT FROM AUTHOR]

In view of the fact that the existing cotton stem simulation models are simplified and have a large discrepancy from the actual appearance and the contact parameters have not been calibrated. In this study, the simulation model and numerical simulation had been established using the discrete element software EDEM. Then a second-order response model between contact parameters and repose angle had been constructed. The test result showed that the static friction coefficient, rolling friction coefficient, and coefficient of restitution between cotton stems were crucial factors affecting the repose angle. The determination coefficient corrected determination coefficient and p-value of the second-order response model were R²=0.959, R²adj =0.921, and p<0.0001 respectively. The error values of the comparison between the simulation test results and the corresponding physical test values were all less than 10%, which showed that the model was reliable and had high interpretation and predictability, this study can provide a certain theoretical basis and data support for the setting of contact parameters in the data simulation of cotton stem harvesting and processing, mechanically-harvested film residue crushing and film stem separation, etc. [ABSTRACT FROM AUTHOR]

The restitution coefficient (RC) of cotton stalks is an important elementary physical parameter that is required to establish the crushing mechanical model and research the film residue separation machinery. In this study, the calculation method of restitution coefficient considering the rotation motion of stalk-shaped agricultural materials was derived based on the principle of kinematics and the energy restitution coefficient method, and a test bench for measuring the RC was designed and built. The effects of collision material, moisture content, length, diameter, release height, and collision angle respectively on the RC were investigated by single-factor experiments and orthogonal experiments, and the regression models between influence factors and the RC were established. The results showed that Q235 showed the highest value of the RC, and it was followed by cotton stalks and soil lumps, sequentially. The RC of cotton stalks decreased with the increase of moisture content and diameter, while it increased at first and then decreased with the increase of length. As the release height was less than 500 mm, the RC increased with the increased release height. As the collision angle was less than 40°, the RC showed a linear increasing trend. The significance of the effects of factors on RC decreased with the following sequence: collision angle, length, release height, diameter, and moisture content. Length, collision angle, and release height were extremely significant. The contrast test results showed that the values based on Newton's restitution coefficient method were smaller than that based on the energy restitution coefficient method. The verification test showed that the predicted rebound height of cotton stalks calculated based on the energy restitution coefficient method was closer to the actual rebound height, and the relative error was less than 5% [ABSTRACT FROM AUTHOR]

In order to obtain accurate contact parameters of jujubes in dwarfing and closer cultivation in Xinjiang during the harvest period, based on the Hertz-Mindlin (no-slip) contact model in EDEM, the contact parameters, including the coefficient of restitution, static friction, and rolling friction, between jujube and machine components have been calibrated through physical and simulation test. The coefficient of restitution, static friction, and rolling friction between the jujubes and steel (jujube-steel) were calculated as 0.33, 0.46, and 0.04, respectively. The coefficient of restitution, static friction, and rolling friction between the jujubes and polyvinyl chloride (PVC) (jujube-PVC) were calculated as 0.39, 0.61, and 0.06, respectively. The optimum contact parameters among jujubes (inter-jujubes) were 0.23, 0.33, and 0.04. The accumulation test was applied for comparing the simulation and testing values of jujube's repose angle. In the results, the relative error was 1.27% which means the discrete element model and the contact parameters of jujube can be used for the discrete element simulation test. In addition, the results can be adequately used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc.) of jujube in harvest as well as the design and working mechanism study of post-harvest processing machinery and devices. [ABSTRACT FROM AUTHOR]

According to the agronomic requirements of orchard planting pattern and fertilization in Xinjiang, the soil particle models and a soil-trenching device interaction model were established by using discrete element simulation software in order to find out the law of influence of structure parameters and working parameters on the operation power consumption of a segmented cutting trenching device; moreover, its cutting process was simulated according to the response surface test design. According to the results of research on the influence of forward speed, cutter disk speed and cutter disk combination on the operation power consumption of the segmented cutting trenching device, the law of their influence on the operation power consumption in descending order is forward speed, cutter disk combination, cutter disk speed. According to the response surface test result, the following influential factor parameter combination has been obtained: forward speed 815 m/h, cutter disk speed 112 r/min, cutter disk combination A (cut angle 150°, bent angle 60° and working width 133 mm), cutter disk combination B (cut angle 180°, bent angle 90° and working width 166 mm), and trenching operation power consumption-optimization results were verified through field tests. According to the verification, the results showed a high accuracy of the simulation, with a relative error mean of 3.18% between the theoretical value and the field test value. This study can provide a reference for the energy-saving design of orchard trenching devices. [ABSTRACT FROM AUTHOR]

In order to obtain accurate contact parameters of a particulate material in residual film mixture collected by cotton field machine in Xinjiang, the angle of repose test and inclined plane test were carried out. In the tests, the angles of repose of the particulate material with the water content of (6.26±1.5)% and (14.1±2.1)% were measured respectively, as well as the static sliding friction angle between the particulate material and the residual film. At the same time, the EDEM software was used to calibrate the coefficient of restitution, static friction coefficient and dynamic friction coefficient between the material and the film. Then, the second-order response model between contact parameters and the angle of repose and static sliding friction angle was constructed. In addition, the optimal contact parameters between the granular materials and the mulch were obtained by fitting the physical test data. The results indicated that the errors between the physical test results and the numerical simulation results are small. It was proved that the second-order response model could predict the repose angle of granular materials and the static sliding friction angle between granular materials and farmland film. This study could provide theoretical support for the subsequent model construction of the residual film mixture collected by the cotton field machine. [ABSTRACT FROM AUTHOR]