Objectives. The optimization for the screw configurations and bone plate parameters was studied to improve the biomechanical performances such as reliable internal fixation and beneficial callus growth for the clinical treatment of femoral shaft fracture. Methods. The finite element analysis (FEA) of internal fixation system under different screw configurations based on the orthogonal design was performed and so was for the different structural parameters of the locking plate based on the combination of uniform and orthogonal design. Moreover, orthogonal experiment weight matrixes for four evaluation indexes with FEA were analyzed. Results. The analytical results showed the optimal scheme of screw configuration was that screws are omitted in the thread holes near the fracture site, and single cortical screws are used in the following holes to the distal end, while the double cortical screws are fixed in thread holes that are distal to the fracture; in the other words, the length of the screws showed an increasing trend from the fracture site to the distal end in the optimized configuration. The plate structure was optimized when thread holes gap reached 13 mm, with a width of 11 mm and 4.6 mm and 5 mm for thickness and diameter of the screw, respectively. The biomechanical performance of the internal fixation construct was further improved by about 10% based on the optimal strain range and lower stress in the internal fixation system. Conclusions. The proposed orthogonal design and uniform design can be used in a more efficient way for the optimization of internal fixation system, which can reduce the simulation runs to about 10% compared with comprehensive test, and the methodology can be also used for other types of fractures to achieve better internal fixation stability and optimal healing efficiency, which may provide a method for an orthopedist in choosing the screw configurations and parameters for internal fixation system in a more efficient way.

Aiming at the problem of large differences in the laying angle and posture of plants cut by the hemp harvester, which is unfavorable for the subsequent picking-up, this paper analyzed the laying process and laying angles, and built a conveyor-plant rigid-flexible coupling model for simulating the laying of hemp plant. Moreover, the operating parameters were tested and optimized based on the central composite design theory, and carried out multi-objective optimization with the minimum laying angle as the response index. Firstly, the formation mechanism of the laying angle of hemp harvester was studied. Secondly, a test was designed with the quadratic orthogonal rotational combination test method, with the data being processed by Design-Expert. A regression mathematical model of the laying angle was built, and the influence of the interactions between factors on the laying angle was analyzed with the response surface method. Furthermore, multi-objective optimization was conducted on the regression model according to the actual production design requirements. As a result, the best combination was obtained, that is, when the forward speed is 0.7 m/s, speed ratio 1.40, and stubble height 95 mm, the minimum laying angle can be obtained, namely 124.9°. The optimization parameters were verified by the simulation and field tests. The simulation test showed that the simulated laying angle is 125.2°, with a relative error of 0.24% from the theoretical value, under the best combination of parameters. The field test showed that the average laying angle of hemp plant is 121.8°, with a relative error of 2.5% from the theoretical value, under the best combination of parameters. The results may provide a reference for the structural improvement and operating parameter control of hemp harvesters. Keywords: agricultural machinery, hemp, laying angle, rigid-flexible coupling model, optimization, response surface analysis DOI: 10.25165/j.ijabe.20231604.7978 Citation: Huang J C, Tan L, Tian K P, Zhang B, Ji A M, Liu H L, Shen C. Formation mechanism for the laying angle of hemp harvester based on ANSYS-ADAMS. Int J Agric & Biol Eng, 2023; 16(4): 109–115.

Planetary gear is the key component of the transmission system of electromechanical equipment for energy industry, and it is easy to damage, which affects the reliability and operation efficiency of electromechanical equipment of energy industry. Therefore, it is of great significance to extract the useful fault features and diagnose faults based on raw vibration signals. In this paper, a novel deep feature learning method based on the fused-stacked autoencoders (AEs) for planetary gear fault diagnosis was proposed. First, to improve the data learning ability and the robustness of feature extraction process of AE model, the sparse autoencoder (SAE) and the contractive autoencoder (CAE) were studied, respectively. Then, the quantum ant colony algorithm (QACA) was used to optimize the specific location and key parameters of SAEs and CAEs in deep learning architecture, and multiple SAEs and multiple CAEs were stacked alternately to form a novel deep learning architecture, which gave the deep learning architecture better data learning ability and robustness of feature extraction. The experimental results show that the proposed method can address the raw vibration signals of planetary gear. Compared with other deep learning architectures and shallow learning architecture, the proposed method has better diagnosis performance, and it is an effective method of deep feature learning and fault diagnosis.

In response to the unclear issue of whether the dynamic cutting performance and structural parameters of an industrial hemp blade, which was developed earlier based on the bionic prototype of the batocera horsfieldi, can be optimized in actual working conditions, this paper analyzes the effective clamping conditions of a reciprocating double-acting cutting blade for stalks and the cutting motion. To investigate the effect of different structural and motion parameters, as well as their interactions, of the bionic blade on cutting energy consumption, bionic blades with different combinations of tooth pitch and tooth angle were designed. A Box–Behnken response surface method with three factors and three levels was used to design an experimental scheme. Utilizing rigid-flexible coupling numerical simulation technology, numerical simulation experiments were conducted to investigate the cutting performance of industrial hemp stalks using the blade. A regression model for cutting energy consumption was established, and variance analysis indicated that tooth angle, speed ratio, and the interaction between tooth angle and speed ratio had an extremely significant effect on the regression model. The primary and secondary orders of factors affecting cutting energy consumption were determined to be: speed ratio > tooth angle > tooth pitch. Through optimization, the optimal parameter combination was found to be a blade tooth pitch of 6.61 mm, a tooth angle of 30°, and a speed ratio of 1.62. Under these conditions, the cutting energy consumption was 3947.99 mJ. The optimized parameters were verified through numerical simulation cutting experiments, and the results showed that the error compared with the optimization results was only 8.16%. This indicates that the optimization results have high credibility and further verifies the reliability of the model. This study can provide a reference for the development of cutting devices for industrial hemp harvesters and the selection of motion parameters.

This paper presents a novel procedure to identify cross-section deformation modes of thin-walled structures with the application of pattern recognition. Initially, a higher order model is derived by considering an approximation of cross-section deformation by a set of basis functions, which are integrated in the governing equations and decoupled through the solution of the associated generalized eigenvalue problem. The eigenvectors obtained are deemed to inherit the attributes of structural behaviors, and thus can serve as the basis to identify deformation modes. Accordingly, these eigenvectors are further handled employing the singular value decomposition, in order to recognize the axial variation patterns of the basis functions. Next, each eigenvector is orthogonally decomposed into components corresponding to the variation patterns, with their proportional relationship, which is really pursued, being obtained and used as the weights to “assemble basis„ functions to generate deformation modes. Moreover, a numbering system is proposed to hierarchically organize these deformation modes. Finally, a reduced higher order model can be obtained by updating the initial governing equations with a selective set of cross-section deformation modes. The main features lie in the capability to be numerically implemented in a simple and intuitive way and the nature to give identified deformation modes mechanical interpretation inherited from actual dynamic behaviors of thin-walled structures. The versatility of the procedure as well as the resulting beam model has been validated through both numerical examples and comparisons with other theories.

Finite element numerical simulations provide a visual and quantitative approach to studying the interaction between rigid mechanical components and flexible agricultural crops. This method is an important tool for the design of modern agricultural production equipment. Obtaining accurate material model parameters for crops is a prerequisite for ensuring the reliability and accuracy of numerical simulations. To address the issue of unclear mechanical constitutive model parameters for industrial hemp stalks, this study utilized the theory of composite materials to establish a mechanical constitutive relationship model for industrial hemp stalks. Compression, tensile, and bending tests on different components of the stalk were conducted, using a computer-controlled universal testing machine, to obtain their elastic parameters. Combined with the measured basic material parameters and contact parameters of industrial hemp stalks, a finite-element numerical simulation model of industrial hemp stalks was established. By conducting Plackett–Burman and central composite experiments, it was determined that among the six measured parameters, the anisotropic plane Poisson’s ratio of the phloem and the isotropic plane Poisson’s ratio of the xylem have a significant influence on the maximum bending force of the stalk. Parameter optimization was carried out, using the relative error of the maximum bending force as the optimization objective, resulting in an anisotropic plane Poisson’s ratio of 0.054 for the phloem and an isotropic plane Poisson’s ratio of 0.28 for the xylem of industrial hemp stalks. To validate the accuracy and reliability of the optimized parameters, a numerical simulation was conducted and compared with the physical experiments. The simulated value obtained was 405.81 N while the actual measured value was 392.55 N. The error between the simulated and measured values was only 3.4%, confirming the effectiveness of the model. The precise parameters for the mechanical characteristics of industrial hemp stalk material obtained in this study can provide a parameter basis for future research on the numerical simulation of mechanized industrial hemp harvesting and retting.