Polymeric matrix composites are important to the advancement of industries such as the automobile and medicine industries. In this study, the silicon carbide (SiC) particle-reinforced polyamide12 (PA12) matrix composites were fabricated by selective laser sintering system as well as the pure PA12. The surface topographies, mechanical, and tribological properties were further examined. The results indicated that the friction and wear resistance of the composite were improved compared with the PA12 matrix. The compressive strength increased about 8.5%, shore D hardness increased about 6%. The friction coefficient decreased about 10%, the specific wear rate decreased 20% after adding silicon carbide 10% weight to PA12. The wear mechanisms were also discussed. The deformed asperities on the worn surface can withstand more tangential load, and therefore resulted in lower specific wear rate. It was found that the content of SiC particles on the surface were reduced after friction tests. According to the analysis of SEM, EDS, and FTIR results, the wear mechanisms were considered to be the abrasive and fatigue mode. This type of PA12 matrix composite might be a promising potential in marine and energy applications.

The counting of pineapple buds relies on target recognition in estimating pineapple yield using unmanned aerial vehicle (UAV) photography. This research proposes the SFHG-YOLO method, with YOLOv5s as the baseline, to address the practical needs of identifying small objects (pineapple buds) in UAV vision and the drawbacks of existing algorithms in terms of real-time performance and accuracy. Field pineapple buds are small objects that may be detected in high density using a lightweight network model. This model enhances spatial attention and adaptive context information fusion to increase detection accuracy and resilience. To construct the lightweight network model, the first step involves utilizing the coordinate attention module and MobileNetV3. Additionally, to fully leverage feature information across various levels and enhance perception skills for tiny objects, we developed both an enhanced spatial attention module and an adaptive context information fusion module. Experiments were conducted to validate the suggested algorithm’s performance in detecting small objects. The SFHG-YOLO model exhibited significant gains in assessment measures, achieving mAP@0.5 and mAP@0.5:0.95 improvements of $7.4\%$ and $31\%$, respectively, when compared to the baseline model YOLOv5s. Considering the model size and computational cost, the findings underscore the superior performance of the suggested technique in detecting high-density small items. This program offers a reliable detection approach for estimating pineapple yield by accurately identifying minute items.

To optimize and improve the impact performance of a hydraulic rock drill, it is helpful to test the stress waves of the drill and analyze the impact energy, impact frequency, and energy utilization rate. For this study, a stress wave test bench was designed and built, according to international standards, in order to study the impact process of a hydraulic rock drill under the working pressures of 18 MPa and 23 MPa. The impact energy, impact frequency, and energy utilization rate of two different hydraulic rock drill pistons in low, middle, and high gear were analyzed using a control variable method. The results demonstrate that the impact stress waves of the rock drill periodically occur in the drill rod, and then decay exponentially until they become close to zero. Moreover, the amplitude of the incident stress wave determines the rock-breaking ability of the drill. The impact energy of the short piston is greater than that of the long piston, with a maximum average value of 346.1 J; the impact frequency of the long piston is higher than that of the short piston, with a maximum average value of 62 Hz; and the energy utilization rate of the short piston is higher than that of the long piston, with a maximum average value of 56.92%, which is close to the theoretical ideal efficiency. Therefore, it can be concluded that the impact performance of a hydraulic rock drill can be effectively tested using the proposed horizontal bench, and that piston characteristics and the working pressure are the main factors affecting impact performance. Accordingly, when developing a hydraulic rock drill, it is advisable to select a shorter piston and a higher working pressure, thus allowing the drill to provide good impact performance.

Polymeric matrix composites have been widely used in the marine field. In this study, the tribological behavior under seawater-lubricated conditions of pure Polyamide 12 (PA12), micron-SiC and nanometer SiC and SiO₂ particle-reinforced PA12 composites, which are prepared by selective laser sintering (SLS), were studied. The seawater absorption, hardness, contact angle and tribology performance were investigated. The results show that the addition of micron- and nano-SiC particles and nano-SiO₂ particles could decrease the seawater adsorption and contact angle, and increase the hardness. Under seawater conditions, the addition of micro SiC particles can reduce the friction coefficient and wear loss, whereas the addition of nano-SiC and -SiO₂ particles increases the corresponding values. The specimen printed with recycled powder has a higher friction coefficient, while having a better wear resistance. However, it increases the width and depth of the wear track in some locations. The wear mechanisms of the composite specimens are also analyzed. This was the result of the combined effects of fatigue wear and abrasive wear under seawater conditions. The latter plays a dominant role under seawater conditions. This study may provide a valuable reference for the further research and application of polymeric matrix composites in marine engineering equipment.

Pearl detection with a counter (PDC) in a noncontact and high-precision manner is a challenging task in the area of commercial production. Additionally, sea pearls are considered to be quite valuable, so the traditional manual counting methods are not satisfactory, as touching may cause damage to the pearls. In this paper, we conduct a comprehensive study on nine object-detection models, and the key metrics of these models are evaluated. The results indicate that using Faster R-CNN with ResNet152, which was pretrained on the pearl dataset, mAP@0.5IoU = 100% and mAP@0.75IoU = 98.83% are achieved for pearl recognition, requiring only 15.8 ms inference time with a counter after the first loading of the model. Finally, the superiority of the proposed algorithm of Faster R-CNN ResNet152 with a counter is verified through a comparison with eight other sophisticated object detectors with a counter. The experimental results on the self-made pearl image dataset show that the total loss decreased to 0.00044. Meanwhile, the classification loss and the localization loss of the model gradually decreased to less than 0.00019 and 0.00031, respectively. The robust performance of the proposed method across the pearl dataset indicates that Faster R-CNN ResNet152 with a counter is promising for natural light or artificial light peal detection and accurate counting.

In the past decade, triboelectric nanogenerators (TENGs) have attracted significant attention across various fields due to their compact size, light weight, high output voltage, versatile shapes, and strong compatibility. However, substantial wear at solid–solid contact interfaces presents a major obstacle to the electrical output stability of TENGs. The objective of this study is to investigate the output performances of TENGs lubricated with TiO₂-doped oleic acid. The results suggest that the triboelectrical performances of the polyimide (PI) film sliding against a steel ball under 0.1 wt% TiO₂-doped oleic acid are significantly improved compared to those under dry conditions; the growth rates are 35.2%, 103.6, and 85.6%, respectively. Moreover, the coefficient of friction dropped from 0.31 to 0.066. The wear and performance enhancement mechanism are also analyzed. This study provides an effective approach to improve both the electrical performances and tribological behaviors.