To enhance the wear resistance and service life of flat dies, samples were subjected to surface engineering. An hBN enriched Ni60A/TiC composite coating was applied to 20CrMnTi steel using laser cladding technology. The coatings were extensively characterized by Scanning Electron Microscopy (SEM), Energy-Dispersive Spectroscopy (EDS), X-Ray Diffraction (XRD), X-Ray Photoelectron Spectroscopy (XPS), microhardness testing, 3D profilometry, tribological testing, and electrochemical analysis to assess their microstructure, phase composition, elemental distribution, microhardness, tribological properties, and corrosion resistance. It was determined that adding 0.75 % h-BN to the Ni60A/TiC composite coating resulted in optimal performance. The coating was primarily composed of hard phases such as TiC and CrB, along with solid lubricants, and exhibited both abrasive and adhesive wear resistance. The element distribution within the coating was uniform. The wear rate and wear depth were measured at 0.9 & times; 10-5 mm3/(N & sdot;m) and 5.92 mu m, respectively, representing an 87 % reduction in wear depth compared to the uncoated substrate and significantly enhancing wear resistance. Furthermore, the 0.75 % h-BN coating markedly improved corrosion resistance, with a corrosion potential of -0.1722 V and a corrosion current density of 1.5497 & times; 10- 7 A.

This paper proposes an improved Secretary Bird Optimisation Algorithm named RS-TDSBOA aimed at enhancing path planning efficiency for mobile robots operating in large-scale, intricate environments, such as warehousing and logistics. The proposed algorithm integrates a Tent–Bernoulli dual chaotic mapping to enrich the diversity of the initial population, introduces a random search strategy guided by the optimal fitness value to strengthen global exploration in later iterations, and applies an adaptive t-distribution perturbation mechanism to reduce the probability of the algorithm becoming trapped in a local optimum. To comprehensively assess the algorithm’s performance, extensive simulations were performed on 23 benchmark test functions, validating the effectiveness of the proposed improvement strategies. Furthermore, in complex path planning scenarios with a size of 50×50, RS-TDSBOA achieved substantial improvements of 17.5% - 33.5% in average path length compared with the original SBOA. When compared with other state-of-the-art algorithms, including GTO and SSA, the proposed method demonstrated superior performance, achieving path length reductions of 5.5% - 44.0%. Especially in extreme environments such as dense obstacles and mazes, the algorithm can still maintain a 100% success rate in path planning, showing excellent robustness. Overall, the results confirm that RS-TDSBOA exhibits a strong capability to identify the optimal solution, along with high effectiveness and stability when addressing large-scale and complex path planning problems.

To achieve precise feeding, this study coupled a Discrete Element Method (DEM)-based virtual test platform with the Response Surface Method (RSM) to quantitatively evaluate and optimize the effects of traveling speed (X₁), scraper rotation speed (X₂), and conveyor belt speed (X₃) on unit feeding amount (Y₁) and feeding uniformity (Y₂). A simplified core model of the feeding device was established in EDEM, and the cohesive characteristics of Total Mixed Ration (TMR) were characterized using the Hertz–Mindlin with JKR Cohesion contact model. A three-factor, three-level Box–Behnken experimental design was employed to fit quadratic regression models for Y₁ and Y₂. The results indicated that both models were statistically significant (P < 0.0001). The significant influencing factors for Y₁ were ranked as X₁ > X₂ > X₃, while those for Y₂ were ranked as X₂ > X₃ > X₁. Based on the analysis of interaction effects among parameters and multi-objective desirability optimization (targeting Y₁ = 10–12 kg·m⁻¹ and maximizing Y₂), the optimal combination was determined as X₁ = 3.05 km·h⁻¹, X₂ = 84.9 r·min⁻¹, and X₃ = 326.5 r·min⁻¹. After rounding for engineering application, X₁ = 3 km·h⁻¹, X₂ = 85 r·min⁻¹, and X₃ = 330 r·min⁻¹ yielded verification results of Y₁ = 11.49 kg·m⁻¹ and Y₂ = 91.54%, with prediction deviations below 5%. Within the studied geometric and parameter ranges, the material flow remained continuous and stable, without persistent arching or blockage. Therefore, the analysis primarily focused on uniformity and throughput. This study provides executable operational parameters and a transferable parameter design approach applicable to cohesive feed systems

In order to obtain accurate contact parameters for the discrete element simulation of salt particles used in animal husbandry, the principle of particle contact scaling and dimensional analysis were used for particle scaling. Firstly, the Plackett Burman experiment was used to screen the parameters that significantly affect the angle of repose: salt salt rolling friction coefficient, salt salt recovery coefficient, and salt steel rolling friction coefficient. Considering the influence of other parameters, a combination of bench and simulation experiments was used to calibrate the contact parameters between salt particles and steel plates used in animal husbandry in EDEM. Finally, through the stacking test, steepest climbing test, and orthogonal rotation combination test, the salt salt rolling friction coefficient was obtained to be 0.23, the salt salt recovery coefficient was 0.544, and the salt steel rolling friction coefficient was 0.368, which were verified through bench tests. The experimental results show that the relative error between the actual value of the stacking angle and the simulation results is 0.6 used for discrete element simulation of salt particles for animal husbandry, providing reference for the design of quantitative feeding screws and silos.

A laser-cladded Ni60A/TiC composite coating with added nano SiO2 was prepared on the surface of 20CrMnTi. The effects of varying contents of nano SiO2 on the wear and corrosion resistance of the Ni60A/TiC composite coating were investigated. The optimal nano SiO2 content for the Ni60A/TiC composite coating was established. The wear resistance was optimal when 1 wt% nano SiO2 was incorporated. The nano SiO2 addition refined the coating's grain structure and enhanced its wear resistance. However, incorporating 1.5 wt% SiO2 diminished the coating's mechanical properties. With SiO2 integrated, the coating's primary phases included TiC, CrB, SiC, MnO2, and Cr2O3. The coating with 1 wt% nano SiO2 underwent adhesive and abrasive wear, featuring uniform element distribution, a wear rate of 1.0 x 10-5 mm3/(N & sdot;m), a friction coefficient of 0.66, and a wear depth of 7.15 mu m. This reduced the wear depth by 84.4 % compared to the substrate, significantly enhancing the composite coating's wear resistance. The coating with 1 wt% nano SiO2 also exhibited considerably improved corrosion resistance, with a self-corrosion potential of-0.2435 V and a self-corrosion current of 4.5244 x 10-7 A.

This study addresses the lack of accurate discrete element method (DEM) models for Glycyrrhiza glabra stem harvesting and crushing devices. By analyzing the stem microstructure and intrinsic properties, physical parameters (Poisson’s ratio, shear modulus, restitution, and friction coefficients) and bonding parameters (contact stiffnesses, critical stresses, bonding radius) were calibrated using DEM simulations. Plackett–Burman, Steepest Ascent, and Box–Behnken experimental designs optimized these parameters through angle of repose and radial compression tests. Validation showed a 3.58

The temperature inside the sheep barn has a significant effect on sheep growth; therefore, providing a suitable thermal environment for the barn is essential. Considering the uneven heating problem of existing heating equipment in livestock barns, we designed an air-duct heating equipment using electricity to ensure a comfortable temperature for sheep with a suitable airflow rate. A computational fluid dynamics (CFD) method was used to simulate the temperature and velocity fields inside the sheep barn, check the heating effectiveness, and ensure uniformity. To determine the optimal opening direction and size of the heating equipment, simulation tests with various opening directions and sizes were conducted using the flow velocity and uniformity of the flow field as the key factors. The CFD simulation results showed that for the investigated sheep barn, a downward opening with diameter of 60 mm was the most effective for heating. Finally, in winter, a heating test was conducted during the decreasing, stable, and increasing periods of outdoor temperatures to verify the heating effectiveness in the experimental sheep barn. During the decreasing and stable periods of outdoor temperature, the indoor temperatures increased by 2 and 5 degrees C, respectively, in 70 min. Conversely in the increasing period of outdoor temperature, the temperature inside the barn increased by 11 degrees C and continued to rise. Our results showed that the expected heating effect of sheep barns was achieved, which can provide a reference for the environmental regulation of livestock barns.

In response to the poor performance of long-distance small target recognition tasks and real-time intelligent monitoring, this paper proposes a deep learning-based recognition method aimed at improving the ability to recognize and monitor various behaviors of captive ewes. Additionally, we have developed a system platform based on ELFN-YOLO to monitor the behaviors of ewes. ELFN-YOLO enhances the overall performance of the model by combining ELFN with the attention mechanism CBAM. ELFN strengthens multiple layers with fewer parameters, while the attention mechanism further emphasizes the channel information interaction based on ELFN. It also improves the ability of ELFN to extract spatial information in small target occlusion scenarios, leading to better recognition results. The proposed ELFN-YOLO achieved an accuracy of 92.5%, an F1 score of 92.5%, and a mAP@0.5 of 94.7% on the ewe behavior dataset built in commercial farms, which outperformed YOLOv7-Tiny by 1.5%, 0.8%, and 0.7% in terms of accuracy, F1 score, and mAP@0.5, respectively. It also outperformed other baseline models such as Faster R-CNN, YOLOv4-Tiny, and YOLOv5s. The obtained results indicate that the proposed approach outperforms existing methods in scenarios involving multi-scale detection of small objects. The proposed method is of significant importance for strengthening animal welfare and ewe management, and it provides valuable data support for subsequent tracking algorithms to monitor the activity status of ewes.

Objective The flat die, a key component of flat die granulators, is subject to severe wear. Laser cladding technology is used widely, and the wear resistance of the flat die can be improved using laser cladding technology. Nickel -based self -fluxing alloy powder has excellent wear resistance and corrosion resistance at a lower cost. TiC ceramic particles were added to the nickel -based self -fluxing alloy powder to enhance the wear resistance of the coating. The previous study showed that the coating had the best all-round performance when the volume fraction of additive TiC was 25%. However, few studies have examined the optimal process parameters for the laser cladding of Ni60A-TiC composite coatings with 20CrMnTi steel as the substrate. Therefore, the Ni60A- 25 % TiC composite coating was prepared on the surface of 20CrMnTi steel by laser cladding. This study examined the effects of the laser power, scanning speed, and powder feeding speed on the microstructure and wear resistance of the Ni60A-25 % TiC coating.Methods The Ni60A-25 % TiC powder was mixed evenly using a QM-QX4 ball mill. A three -factor, three -level orthogonal experiment was designed with the test factors of laser power, scanning speed, and powder feeding speed. Cladding coatings were prepared with different technological parameters. A CFT-I surface comprehensive tester was used for the friction and wear tests. The mass before and after wear was measured using a BSM-220. 4 electronic balance. X-ray diffraction (XRD), three-dimensional surface topography, scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and microhardness tester were used to characterize the phase composition, 3D morphologies, microstructure, element distribution, and element valence and microhardness of the coatings, respectively.Results and Discussions The coating after laser cladding was dense and showed good metallurgical bonding with the substrate (Fig. 3). The dilution rate and microhardness of the cladding layer were used as evaluation indices. The factors affecting the quality of the cladding layer in descending order were the powder feeding speed, scanning speed, laser power which was obtained by the extreme difference (Table 6) and variance (Table 7) analysis. XRD revealed the main phase composition in the coating to be SiO2, Cr2O3, and TiC. The coating phase varied slightly with the different process parameters (Fig. 4). The friction and wear test showed that the frictional state differed according to the process parameters. The friction coefficient of the coating samples was small, and the wear process was stable. Among them, S3 sample had the lowest wear rate of 1. 5x10-5 mm3/(N center dot m). The microscopic morphology at the abrasion area of the sample was analyzed (Fig. 7). Abrasive wear occurred on the surfaces of the S3 and S4 samples; the wear surfaces were relatively smooth, and the coatings were covered with oxide films, such as SiO2 and Cr2O3, in the friction process. The surface of the S1, S5, and S7 samples mainly showed adhesive wear. The surface of S2, S6, S8, and S9 samples mainly showed abrasive and adhesive wear. The wear resistance of the S10 substrate was poor, and the surface showed abrasive wear, adhesive wear, and plastic deformation, and severe furrows and pits appeared. The above analysis showed that S3 showed better wear resistance. The hardness and wear resistance of the coating was enhanced by the synergistic effect of dispersion strengthening and solid solution strengthening. XPS showed (Fig. 10) that the solid lubricant film of the S3 coating was comprised mainly of oxides, such as SiO2, Cr2O3, TiO2, and NiO.Conclusions Using the dilution rate and microhardness as evaluation indices, the factors affecting the quality of the cladding layer from the largest to smallest were the powder feeding speed, scanning speed, and laser power. The composite coating showed a significantly lower wear rate compared to the substrate. The Ni60A-25 % TiC composite coating with the best all-around performance was produced at a laser power of 1. 4 kW, scanning speed of 7 mm/s, and powder feeding speed of 21 g/min. Severe furrows and fatigue wear were observed on the substrate surface, and the wear of the cladding layer was mainly abrasive. Oxide particles, such as SiO2, Cr2O3, TiO2, and NiO, generated by friction can be used as solid lubricants to form oxide films on the friction layer surface that can prevent further wear of the friction layer and improve the wear resistance of the coating.

In response to the issues of high honeysuckle-picking costs and low efficiency in honeysuckle picking, this study has devised a comb-brush-type picking device, considering the unique characteristics of honeysuckle plants. We elucidated the device’s structure and operational principles and designed critical components within the picking mechanism. Subsequently, through theoretical analysis, we identified the primary factors influencing the device’s operational performance. We then used the honeysuckle picking rates, honeysuckle breakage rates, and impurity rates as assessment metrics. Utilizing a one-factor test, we determined the permissible ranges for each factor. Employing the response surface methodology, we analyzed the interactions among these factors and conducted model parameter optimization. This optimization identified the optimal parameter combination: a forward speed of 3.99 km/h, a driving shaft speed of 316.53 rpm, and a picking teeth length of 70 mm. Finally, we performed verification tests using these optimized parameters. The results demonstrated that the maximum relative error between test verification values and model-optimized predictions was 4.86%. This outcome confirms that the comb-brush-type honeysuckle-picking device can meet the operational requirements of mechanized harvesting and offers valuable insights for developing harvesting devices for vine plants.

Sheep aggression detection is crucial for maintaining the welfare of a large-scale sheep breeding environment. Currently, animal aggression is predominantly detected using image and video detection methods. However, there is a lack of lightweight network models available for detecting aggressive behavior among groups of sheep. Therefore, this paper proposes a model for image detection of aggression behavior in group sheep. The proposed model utilizes the GhostNet network as its feature extraction network, incorporating the PWConv and Channel Shuffle operations into the GhostConv module. These additional modules improve the exchange of information between different feature maps. An ablation experiment was conducted to compare the detection effectiveness of the two modules in different positions. For increasing the amount of information in feature maps of the GhostBottleneck module, we applied the Inverted-GhostBottleneck module, which introduces inverted residual structure based on GhostBottleneck. The improved GhostNet lightweight feature extraction network achieves 94.7% Precision and 90.7% Recall, and its model size is only 62.7% of YOLOv5. Our improved model surpasses the original model in performance. Furthermore, it addresses the limitation of the video detection model, which was unable to accurately locate aggressive sheep. In real-time, our improved model successfully detects aggressive behavior among group sheep.

To address the challenges of non-uniform mixing in total mixed diet forage and the high power consumption of the required device, we developed a segmented spiral total mixed diet device. This development involved theoretical analysis to determine the structural parameters of the main body of the segmented spiral blades, the churn, and the creation of a test bed for the segmented spiral total mixed diet device. Taking mixing speed, mixing time, filling coefficient, and segmented spiral blade spacing as test factors and mixing uniformity and energy consumption per unit mass as test indexes, the optimal combination of operating parameters of the device was determined by using a four-factor, three-level orthogonal test method. The results of the validation test showed that the mixing uniformity of the device under these conditions was 93.41%, the energy consumption per unit mass was 4723.69 J, and the errors between the mixing test values of the device and the optimized values of the model were all less than 5%. This study can provide a reference for improving the working quality of the segmented spiral TMR mixer.

针对全混合日粮搅拌机工作过程中存在的工作部件易磨损等问题,为全混合日粮搅拌机设计与优化提供参考依据,本文以含水率为试验因素,利用英斯特朗 8801 型万能试验机对不同含水率下不同品种甘草茎秆开展了压缩、蠕变与应力松弛特性试验研究.试验结果表明:当含水率为 50%时,光果甘草茎秆在弹性阶段的最大抗压强度为 10 MPa;随着含水率的增加,甘草茎秆的蠕变曲线逐渐向上移动,当含水率为 50%时光果甘草茎秆的蠕变曲线明显高于其他 2 个品种,而在其他含水率时 3 个品种的蠕变曲线较为相似,说明 Burgers四元件模型可以很好的反映甘草茎秆的蠕变特性;随着含水率的增加,甘草茎秆应力松弛曲线逐渐向下移动,胀果甘草茎秆的应力松弛曲线在 3 个含水率下均高于其他 2 个品种,Maxwell五元件模型可以很好的反映甘草茎秆的应力松弛特性.

In order to solve the problems of low efficiency and subjectivity of manual observation in the process of group-sheep-aggression detection, we propose a video streaming-based model for detecting aggressive behavior in group sheep. In the experiment, we collected videos of the sheep's daily routine and videos of the aggressive behavior of sheep in the sheep pen. Using the open-source software LabelImg, we labeled the data with bounding boxes. Firstly, the YOLOv5 detects all sheep in each frame of the video and outputs the coordinates information. Secondly, we sort the sheep's coordinates using a sheep tracking heuristic proposed in this paper. Finally, the sorted data are fed into an LSTM framework to predict the occurrence of aggression. To optimize the model's parameters, we analyze the confidence, batch size and skipping frame. The best-performing model from our experiments has 93.38% Precision and 91.86% Recall. Additionally, we compare our video streaming-based model with image-based models for detecting aggression in group sheep. In sheep aggression, the video stream detection model can solve the false detection phenomenon caused by head impact feature occlusion of aggressive sheep in the image detection model.

During granulation, a serious wear problem may be found in flat die as a key component of a flat die pellet mill. Specific to this problem, Glycyrrhiza uralensis was selected as the wear-causing material to investigate the wear mechanism of the flat die. Additionally, carburizing steel (20Cr and 20CrMnTi) and stainless steel (4Cr13) commonly used in flat die were adopted to conduct wear tests. To explore the influence of Glycyrrhiza uralensis powder and rods on friction and wear properties of the above three types of steel materials, a CFT-I general-purpose tester for surfaces was applied under dry friction conditions. Moreover, x-ray diffractometer (XRD), three-dimensional profilometry, scanning electron microscopy (SEM) and energy disperse spectroscopy (EDS) were used to analyze the phase compositions, surface morphologies, and elementary compositions of the samples. As demonstrated by relevant results, the influence of Glycyrrhiza uralensis on the flat die is primarily embodied in abrasive, adhesive, and fatigue wear, and a thermal oxidation reaction occurs on the surface of the flat die. By comparing the wear conditions of the three steel materials between the powder and rods of Glycyrrhiza uralensis, it is found that flat die damages caused by glycyrrhiza rods are more severe than those of its powder. Additionally, the lowest friction coefficients are generated by 20CrMnTi, which are 0.40 and 0.88, respectively. In terms of the mean wear depth, its values are 1.2 and 2 μm, which are below those of 20Cr and 4Cr13. The results herein reveal that flat die made of 20CrMnTi have excellent wear and ductile fracture resistance characteristics. Hence, this study may provide a theoretical guide for selecting flat die materials.

为了实现羊用电动撒料车投料量的精确控制,使投料量更加均匀,对其投料驱动电机转速实时追踪精确调整,设计了一种基于模糊PID控制算法的羊用电动撒料车精确投料控制系统,并通过对刮板电机转速、送料带电机转速实时调节,实现了电动撒料车投料量的精确控制.利用MatLab的SIMULINK平台进行系统仿真,验证模糊PID控制算法的优越性,借助基于单片机的硬件控制器在DYS-5型电动撒料车上进行了试验研究.结果表明:系统能够稳定精确地调节各个电机转速,使两个电机的误差转速分别控制在10.8％和4.6％以内,使电动撒料车在正常撒料情况下的投料均匀度增加了9.31％,提高了电动撒料车的作业效率和作业质量,使撒料更加智能化.

This study investigates the influence of rare-earth La2O3 content on the wear resistance of a laser clad coating. Different contents of nano-rare-earth La2O3 were added to a Ni60a/SiC composite powder to analyse the phase composition, element distribution and friction and wear characteristics of the coating to determine the optimum amount of rare-earth La2O3 to be added. The results showed that the coating with 2 wt% La2O3 added based on the Ni60a/SiC composite powder exhibited the best comprehensive properties. X-ray diffraction and X-ray photoelectron spectroscopy analyses showed that new phases were formed in the coatings with 2 wt% La2O3 mainly consisted of hard phases such as Cr7C3 and CrC. Scanning electron microscopy revealed that the coating grain with 2 wt% La2O3 was refined, the density increased and the distribution of coating elements was more uniform. The wear surface coating was slightly peeled off, and a friction coefficient of 0.63 and a wear depth of 15.79 mu m were achieved, which were 3% and 86% lower than those of the 65Mn matrix, respectively. The wear amount was 0.002 g. The wear surface experienced an oxidation reaction.

为提高饲草揉切机中揉切刀片的耐磨性,采用激光熔覆技术在65Mni钢表面制备Ni60a/SiC复合粉末熔覆层.分析镀层的显微硬度、物相组成和摩擦磨损性能,以得到最佳激光熔覆工艺参数组合.结果表明,影响熔覆层硬度的工艺参数主次顺序依次是光斑直径,激光功率和扫描速度,熔覆层有新物相的析出,主要包括NiCrO3与Cr3Ni2SiC等硬质相.最佳激光熔覆参数组合为激光功率2 000 W,扫描速度400 mm/min和光斑直径3 mm,在此参数下的熔覆层显微硬度为870 HV0.1,并且熔覆层与基体呈现良好的冶金结合,在相同的磨损试验环境下,此熔覆层的磨损形式主要是磨粒磨损,磨损量为0.003 g,相比65Mn基体磨损参数,摩擦因数降低29％,磨痕深度降低83％,复合涂层的耐磨性明显增加,本研究在提高刀片的使用寿命方面具有较好的参考价值.

针对带勺式马铃薯排种器作业过程中存在漏播问题,分析排种器工作过程,设计漏播检测与补种系统.对检测模块、补种模块、单片机模块、显示模块和声光报警模块进行电路设计、硬件选型和机械结构设计,针对整个控制系统的控制要求编写控制程序,实现马铃薯漏播检测与补种控制.采用高速摄像技术,对补种模块动作的响应速度进行分析,结果显示,可以满足排种器在当前最快运行速度6.8 km/h下的连续补种需求.搭建试验台进行系统漏播检测与补种的成功率性能测试,结果表明,当取种带线速度为0.14 ～ 0.54 m/s时,原始漏播率为5.9％～11.4％,经该系统补种后,最终漏播率为0.9％ ～2.1％,该漏播检测模块漏播检测成功率为100％,补种模块的补种成功率平均为83.0％,在试验速度范围内,随着取种带线速度的增大,该系统漏播检测仍准确,且补种成功率较为稳定.

针对秋后残膜回收作业视觉导航中的路径规划问题,提出一种作业路径提取方法.提取根茬、残膜和行间茎秆碎叶三类图片的颜色空间特征和纹理特征,按8:2构成训练集和测试集;以检测根茬为目标,搭建随机森林模型对样本图片进行分类,通过特征重要性和相关性对特征进行降维,使用网格搜索确定随机森林模型的最优模型参数;基于根茬主干保持的直立特点,把检测到的每一个根茬上下顶点作为特征点,通过最小二乘法对所有特征点进行拟合即为作业导航线.试验结果表明,通过特征选择将30维特征降到16维,单幅图像处理时间从0.24 s降到0.16 s.在模型最优参数下,测试集准确率为92.5％.选取450幅10×20像素图片进行分类测试,准确率为91.8％,根茬检测准确率(敏感性)为90.7％.选择200幅ROI区域大小为100×200像素的田间作业图片进行导航线拟合试验,其包括不同天气、不同俯角以及非正常驾驶图片,成功拟合出171幅图像.该根茬检测方法具有较高的稳定性和准确性,可为不同作物根茬检测以及路径提取提供参考.