To obtain the physical parameters and contact parameters of ramie stalk decorticating simulation, the structural dimensions, density, moisture content, elastic modulus, and contact parameters of the ramie stalk were measured in this study based on the phloem and xylem of the ramie stalk. The physical stacking angles of the phloem and xylem were measured by the cylinder lift method and the extraction of the partition method, respectively. The contact parameters between the xylem and phloem of the ramie stalk were directly calibrated. Additionally, the contact parameters of the phloem–phloem, phloem–Q235A steel, xylem–xylem, and xylem–Q235A steel were used as calibration objects, and the simulated stacking angle was used as the evaluation index. Then, the Plackett–Burman test was designed to screen for the parameters which were significantly affecting the simulated stacking angle. Furthermore, the steepest ascent test determined the optimal range of values for two significant parameters of the phloem and three significant parameters of the xylem. Based on the central composite design, the second-order regression equations between the significant parameters of the phloem and xylem and the stacking angle were established, respectively. The physical stacking angles of 37.93° for phloem and 27.17° for xylem were the target values to obtain the optimal parameter group. The results showed that the restitution, static, and rolling friction coefficients between the xylem and phloem were 0.60, 0.53, and 0.021, respectively. The static and rolling friction coefficients between the phloem and phloem were 0.41 and 0.056, respectively. The rolling friction coefficient between the xylem and Q235A steel was 0.033, and the static and rolling friction coefficients between the xylem and xylem were 0.44 and 0.016, respectively. The verification test showed that the relative error values were less than 2.11%, which further indicated that the modeling method and parameter calibration of the ramie stalk phloem and xylem models were accurate and reliable. They can be used for the subsequent calibration simulation tests of ramie stalk bonding parameters and ramie stalk decorticating simulations.

Rice is a widely cultivated food crop worldwide, and threshing is one of the most important operations of combine harvesters in grain production. It is a complex, nonlinear, multi-parameter physical process. The flexible threshing device has unique advantages in reducing the grain damage rate and has already been one of the major concerns in engineering design. Using the measured test database of the flexible threshing test bench, the rotation speed of the threshing cylinder (RS), threshing clearance of the concave sieve (TC), separation clearance of the concave sieve (SC), and feeding quantity (FQ) are used as the input layer. In contrast, the crushing rate (Y_P), impurity rate of the threshed material (Y_Z), and loss rate (Y_S) are used in the output layer. A 4-5-3-3 artificial neural network (ANN) model, with a backpropagation learning algorithm, was developed to predict the threshing performance of the flexible threshing device. Next, we explored the degree to which the inputs affect the outputs. The results showed that the R of the threshing performance model validation set in the hidden layer reached 0.980, and the root mean square error ($RMSE$) and the average absolute error ($MAE$) were less than 0.139 and 0.153, respectively. The built neural network model predicted the performance of the flexible threshing device, and the regression determination coefficient R² between the prediction data and the experimental data was 0.953. The results showed revealed that the data combined with the ANN method is an effective approach for predicting the threshing performance of the flexible threshing device in rice. Moreover, the sensitivity analysis showed that RS, TC, and SC were crucial factors influencing the performance of the flexible threshing device, with an average relative importance of 15.00%, 14.89%, and 14.32%, respectively. FQ had the least effect on threshing performance, with an average threshing relative importance of 11.65%. Our findings can be leveraged to optimize the threshing performance of future flexible threshing devices.

Ramie is a valuable natural fiber resource. The fabric made of ramie fiber has distinctive natural characteristics, and its products are widely favored in the international market. Because the cellulose fiber in ramie is closely adhered by a viscous material composed of pectin, hemicellulose, and lignin, mechanical stripping and processing is needed to obtain primary ramie fiber for downstream use. To address the production challenges posed by high labor intensity and the scarcity of small, direct-feeding ramie decorticators in hilly and mountainous regions, this study designed and optimized a spiral ramie decortication component that integrated functions of ramie stalk crushing, xylem removal, outer shell scraping, and phloem separating and throwing. The three-dimensional model of the ramie stripping component was crafted with SolidWorks software, and subsequent modal analysis and dynamic simulation studies were conducted using Abaqus software. The Box–Behnken experimental design method was used to construct a mathematical model describing the effects of the decorticating drum rotation speed and the decorticating gap on the fiber percentage of fresh stalk, and the optimal operating parameters were determined accordingly. The research findings indicated that the component’s initial ten natural frequencies span from 234.41 to 431.70 Hz, which do not overlap with the external excitation frequencies, thus ensuring that no resonance phenomenon occurs during the operation process, meeting the design requirements for the ramie decortication operation. Under dynamic load conditions, the ramie decorticator can efficiently perform the task of ramie fiber decortication, and the stress and strain experienced by the device meet the established design specifications; by optimizing operating parameters, the optimal operating conditions were determined to be the speed of feeding and crushing parts (SFCP) of 100 r/min, the speed of separating and throwing parts (SSTP) of 400 r/min, the gap of feeding and crushing parts (GFCP) of 8 mm, and the gap of separating and throwing parts (GSTP) of 0 mm. Experimental results indicated that under this optimal parameter combination, the fiber percentage of fresh stalk of the spiral ramie decorticator can reach 5.03%, with a relative error of less than 3% compared to the theoretical model prediction value, thus confirming the accuracy of the model prediction. This study establishes a robust technical basis for the development of a convenient decortication technology for ramie fibers. However, this technique is more suitable for small growers, especially in hilly areas, to achieve large-scale applications, schemes must be reevaluated based on production efficiency.

In view of the elevated labor intensity and low efficiency of ramie fiber decortication, we designed a simple automatic ramie decortication machine in line with the characteristics of the ramie fiber decortication process, design requirements and market demand through an innovative design and theoretical analysis of key components such as the clamping and conveying device and the fiber detecting device, and identified the key factors and parameters affecting the quality of ramie decortication. We develop a mathematical model of the fiber percentage of fresh stalks and the ramie fiber impurity rate by considering decortication clearance, the drum speed, and the conveyance speed as factors, and determine the effect of operating parameters on ramie decortication and the optimal combination of parameters. Finally, a multi-objective optimization test was performed using the Box–Behnken test. In this paper, based on the results of the multi-objective parameter optimization analysis, the optimal parameters for ramie peeling were determined, namely, a decortication clearance of 3.7 mm, and a conveyance speed of 340 rpm. According to the optimized parameters, the ramie peeling process was experimentally validated. Using the optimized parameters, a validation test of the ramie direction in this study was performed. As indicated by the results, the percentage of fiber in the fresh stalk reached 5.05%, and the impurity rate in the ramie fiber was 1.24%. The relative errors of all metrics and model predictions were less than 5%, thus validating the accuracy of the prediction model. The machine achieved a production efficiency of 78.5 kg·h⁻¹, which is in line with the design specifications. The raw fiber had a gum content of 23.45 percent, and the stripped fiber met the national standard for secondary ramekin fiber. This study lays a theoretical basis while providing technical support for fully automatic ramie decorticators.