Surface texture and titanium nitride (TiN) coating have been established as effective methods for enhancing the tribological property of mechanical friction pairs. This study aims to investigate the tribological performance of dimple-textured surfaces with TiN coating under oil-lubricated conditions using a pin-on-disc wear experiment. Four types of pin samples with various end surfaces were designed, including bare rod samples, TiN-coated samples, textured samples, and TiN-coated/textured samples. The surface texture consists of a series of cylindrical micro-dimples with a diameter of 150 μm and a depth of 40 μm fabricated on the end surface of the pin. TiN coating treatment on the textured surface of the end face was performed by vacuum sputtering coating equipment. The study focuses on measuring and comparatively analyzing the friction coefficient, wear morphology, and binding force of the pin-disc friction pairs among the experiments. Compared with bare rod samples, TiN-coated/textured samples will reduce the friction coefficient (COF) of the pin-on-disc friction pair by at least 20% under oil-lubricated conditions in a 50 N normal contact load. The results indicate that the synergistic effect of dimple surface texture and TiN coating optimizes friction performance and reduces wear, highlighting the novelty of this study. Furthermore, the study identifies the hydrodynamic lubrication effect of the surface morphology formed by the dimple surface texture as a key factor in improving lubrication performance and reducing friction. Additionally, the dimple surface texture enables the mitigation of third body wear due to the wear debris storage function of the micro-dimples. This research provides valuable insights for the design and fabrication of mechanical friction pairs with high wear resistance under oil-lubricated conditions.

Pattern recognition of lower-limb movements based on mechanomyography (MMG) signals has a certain application value in the study of wearable rehabilitation-training devices. In this paper, MMG feature selection methods based on a chameleon swarm algorithm (CSA) and a grasshopper optimization algorithm (GOA) are proposed for the pattern recognition of knee and ankle movements in the sitting and standing positions. Wireless multichannel MMG acquisition systems were designed and used to collect MMG movements from four sites on the subjects thighs. The relationship between the threshold values and classification accuracy was analyzed, and comparatively high recognition rates were obtained after redundant information was eliminated. When the threshold value rose, the recognition rates from the CSA fluctuated within a small range: up to 88.17% (sitting position) and 90.07% (standing position). However, the recognition rates from the GOA drop dramatically when increasing the threshold value. The comparison results demonstrated that using a GOA consumes less time and selects fewer features, while a CSA gives higher recognition rates of knee and ankle movements.

Based on existing ballistic penetration experimental studies, this work investigates the anti-penetration performance of interlayer hybrid composite panels composed of kevlar and uhmwpe (ultra-high-molecular-weight polyethylene). The results validate that Kevlar exhibits superior suitability as the impact-facing layer compared to uhmwpe. Building on this finding, we employed ballistic limit velocity test and numerical simulation methods to analyze the damage modes and anti-penetration performance of panels penetrated by 1.1 g fragments. Additionally, the penetration process was simulated using Ls-dyna, enabling the prediction of interlayer hybrid ratios with superior anti-penetration performance under three specific conditions. The underlying mechanisms were further elucidated. The results showed that under the condition of equal areal density, the hybrid composite panel with kevlar as the impact-facing layer mixed with uhmwpe demonstrates enhanced anti-penetration performance when the mass ratio of kevlar to uhmwpe is approximately 25%. Under the condition of identical layer count, the panel achieves superior ballistic resistance when the mass ratio of kevlar to uhmwpe reaches 70%. Under the condition of constant thickness, the optimal anti-penetration performance is observed when the mass ratio of kevlar to uhmwpe is 53%. Using materials with high shear strength on the surface layer of the target plate and materials with high tensile strength and high elongation at break on the back layer can better enhance the synergistic effect between the hybrid composite material layers.

Surface texture and titanium nitride (TiN) coating have been established as effective methods for enhancing the tribological properties of mechanical friction pairs. This work aims to investigate the lubrication performance of rhombic-textured TiN-coated surfaces under oil-lubricated conditions using a pin-on-disk test mode. A total of 17 sets of samples were designed, including a control sample (with no rhombic texture and no TiN coating), a TiN-coated sample and rhombic-textured TiN-coated samples. The rhombic surface texture was fabricated using the end surface of a brass bar. TiN coating deposited TiN on the textured surface. This study focuses on measuring and comparatively analyzing the lubrication load capacity, friction coefficient (COF) and binding force of TiN coatings/substrates in the pin-on-disk friction test mode. Compared with the bare control sample, a rhombic texture can enhance lubrication load-carrying capacity by generating hydrodynamic lubrication effects, thereby reducing friction. Additionally, a rhombic texture enables the mitigation of third-body wear due to wear debris. This research provides valuable insights into the design and fabrication of mechanical friction pairs with high wear resistance under oil-lubricated conditions. For lubrication property enhancement, the influence of groove depth was larger than that of the length of the rhombic side.

The whole-stalk harvesting and baling of reeds (Phragmites australis (Cav.) Trin. ex Steud) require a header with high efficiency and low loss rate. Based on an analysis of reed characteristic parameters, this paper proposes a T-shaped layout header design for whole-stalk reed harvesting. The design employs bilateral transverse conveying chains and a longitudinal clamping conveying chain, coordinated with a baler at its end, to achieve integrated harvesting and baling of whole reed stalks, thereby improving efficiency. By analyzing the relationship between key header parameters, such as the height of the lifting lugs on the transverse conveying device, the speeds of the transverse and longitudinal conveying chains, and the forward speed of the header, and the posture of the reeds, the causes of header loss during reed harvesting with the T-shaped header are identified. On this basis, a set of design criteria for the key parameters of the T-shaped whole-stalk reed header is established. A T-shaped reed whole-stalk harvesting header was designed according to these criteria and tested in harvesting experiments with varying preset values for forward speed and lower transverse conveying chain speed. Experimental data show that under optimally matched parameters, the header achieves a low average loss rate (L_h ≤ 2.0%) and a high average harvesting efficiency at the rated forward speed (up to 1.0 hm²/h, including baling), verifying the correctness of the theoretical analysis and the design criteria. The research results provide theoretical and experimental support for the design of conveying systems in headers for tall-stalk crops such as reeds.

An accurate simulation model is crucial for the analysis of the correct modal information of the ginkgo seed–stem system (ginkgo subsystem). This underpins the provision of technical rationale for efficient and low-damage precision vibrational harvesting operations in ginkgo cultivation. In this study, based on the modal parameters of the ginkgo subsystem, a finite element model updating method is proposed to correct the elastic modulus of the stem with the natural frequency of the first bending mode. The large difference in the modal results calculated before and after model updating reveals that model updating is a critical step in the finite element analysis of crop subsystems. Then, an uncertainty parameter modeling method is proposed to investigate the modal variability of the ginkgo subsystem by finite element analysis. The results show that the stem length is a key parameter affecting the variability of natural frequencies, and the seed weight is a minor parameter. The variability of the ginkgo seed’s gravity center offset has a negligible effect on the natural frequencies of the system. The first natural frequency of the ginkgo subsystem can be utilized for vibrational harvesting. In addition, since the difference between the upper and lower limits of the first natural frequency of the ginkgo subsystem does not exceed 1 Hz, a specific excitation frequency can cause most ginkgo subsystems to resonate. This result facilitates the determination of precise excitation frequencies for efficient and low-damage ginkgo vibrational harvesting, ensuring both economic and ecological benefits in the management of ginkgo plantations.