Browse Topic: Optics

Items (10,435)
In view of the problems that it is difficult to accurately control the spraying area of the mining sprinkler, and the resource waste caused by the mis-spraying material stacking area, as well as the failure of traditional radar monitoring in the complex electromagnetic environment, this paper proposes an anti-splashing system for the mining sprinkler. By combining millimeter wave radar and visual recognition fusion technology, the overall scheme of the anti-splash system is proposed. Then the control simulation of the whole system is carried out. The results show that the problem of poor control in traditional sprinkler operation can be effectively solved, and the sprinkler area can be adjusted intelligently. Finally, in order to verify the accuracy of the algorithm used in this paper, different algorithms are used for comparative experimental verification. The results show that the Modified YOLOv4 algorithm has a high accuracy of 98.75 %, which has good applicability and provides a theoretical basis for subsequent research.
Hou, Lin
g-C₃N₄, a metal-free semiconductor photocatalyst, demonstrates remarkable potential, but its practical application in pollutant degradation is significantly limited by the rapid recombination of photogenerated electron-hole pairs and low photocatalytic efficiency. To address this, a series of magnetic recyclable g-C₃N₄/CoFe₂O₄ composite photocatalysts with different CoFe₂O₄ doping ratios were innovatively designed and prepared via thermal polymerization, sol- gel, and combined with ultrasonic and heat treatment processes. The novelty of this composite design lies in the effective integration of magnetic CoFe₂O₄ with g-C₃N₄ through a heterojunction structure. It substantially boosts the absorption of visible light. Concurrently, it effectively fosters the separation and mobility of photo-induced charge carriers. The composite materials were systematically characterized by X-ray diffraction, thermogravimetric analysis, scanning electron microscopy with energy-dispersive X-ray spectroscopy, photoluminescence spectroscopy, and ultraviolet-visible diffuse reflectance spectroscopy. Using tetracycline hydrochloride as the target pollutant, the photocatalytic activity of the composites was evaluated under visible light irradiation, and the effects of initial concentration, catalyst dosage, and the influence of solution pH on degradation efficiency were also examined. The results indicated that the composite with a CoFe₂O₄ to g-C₃N₄ mass ratio of 1:3 (denoted as 3-CN/CFO) exhibited the optimal performance: a TCH degradation rate of 80.29 % within 105 minutes and a total organic carbon removal rate of 61.63 %. After five consecutive cycling experiments, the degradation efficiency remained above 70 %, demonstrating good reusability and stability. The performance improvement is attributed to the formation of heterojunctions in the composite, which effectively facilitates charge separation, inhibits carrier recombination, and enhances visible light absorption. Furthermore, the inherent magnetism of the composite permits efficient recovery, streamlining its integration into practical applications. Toward the purification of antibiotic-contaminated water, this research proposes a viable method for fabricating highly effective and recyclable photocatalysts.
Hua, LongjunChai, TianWang, YimingZhang, JingHe, Ting
Vacuum laser welding trials were carried out on 42CrMo steel, a material widely utilized in the defense sector. By employing a 30 kW fiber laser system, complete penetration welds were successfully produced on 20 mm thick 42CrMo steel plates. The resulting joints displayed satisfactory surface quality on both the top and bottom sides, with no evident defects such as cracks or porosity. A comprehensive analysis of the joint microstructure and mechanical properties was conducted. Findings reveal that the weld zone (WZ) is predominantly composed of lath martensite, accompanied by minor quantities of plate martensite, organized as columnar crystals. The joints demonstrated high tensile strength at ambient temperature, with fracture consistently occurring within the base metal (BM). Microhardness measurements indicated higher values within the weld relative to the base metal, and no pronounced softening was detected in the heat-affected zone (HAZ). Additionally, the joints exhibited commendable impact toughness, suggesting overall superior mechanical performance.
Shi, HaichengZhang, GuoyuLi, WuhongCao, DongxuLiu, Tianlei
This study investigates the interaction mechanism between ultraviolet nanosecond pulsed lasers and polyetheretherketone (PEEK). By integrating finite element simulations with experimental validation, the work explores the laser microtexturing characteristics of PEEK surfaces and evaluates the influence of microtextures on the material’s surface biocompatibility. First, the interaction between the laser and the PEEK polymer was analyzed, and a laser ablation model was established using the COMSOL Multiphysics simulation platform. Using finite element simulation, the effects of spot overlap ratio were investigated by adjusting the average laser power, while the influence of single-pulse energy on the ablation characteristics of the PEEK surface was examined by varying the scanning speed. Subsequently, ultraviolet nanosecond laser processing experiments were conducted on planar PEEK microtextures based on the simulation results. Taking surface microgrooves on PEEK as representative structures, the variations in groove depth and width under different combinations of laser parameters were analyzed. The parameters, including average laser power, scanning speed, and repetition frequency, were optimized to identify processing conditions that yield stable depth and width, along with good surface flatness. Finally, experiments have initially verified that the microtextured PEEK surface may improve biocompatibility and regulate surface wettability to a certain extent.
Wu, YifanWang, XiaohuiHan, YujieJin, Shuo
To meet the critical need for rapid response and miniaturization in laser beam expander drive systems, this study proposes an innovative actuation solution based on a hollow rotary traveling-wave ultrasonic motor. By thoroughly analyzing the optical adjustment mechanism of laser beam expanders and the electromechanical coupling behavior of ultrasonic motors, the motor structure was systematically optimized. Using a multiphysics coupling approach, the performance of stators fabricated from three distinct materials was compared, and parametric optimization was conducted. Experimental verification confirms that the developed ultrasonic motor precisely matches the load characteristics of beam-expanding optics while fulfilling the stringent requirements for both fast response and compact design. This research provides a reference for the miniaturization drive of high-precision optical systems, with promising applications in space optics and precision instrumentation.
Qiu, HaihuiNiu, ChuanhuXiao, ZhongXu, ZhangfanLi, JialiangPan, Song
The distribution of contact stress in roller bearings has a significant impact on operational performance and safety. Firstly, we established a bearing clearance change model that combines interference fit and thermal expansion effects. Then, we studied the clearance changes of key parameters’ influence under different operating conditions. Using Hertz contact theory, we analyze the nonlinear coupling relationship between clearance changes, load distribution, and contact stress. Through MATLAB analytical calculations, load and stress distribution contour maps were obtained under typical operating conditions, which provided theoretical support for bearing optimization design and reliability analysis. The result depicts that an increase in interference fit and temperature difference leads to clearance decrease, triggering a redistribution of contact stress. As clearance decreases, the maximum contact stress exhibits a nonlinear growth trend. To further enhance engineering practicality, this paper uses the MATLAB platform to develop a visualization of digital image processing software. The software enables interactive analysis throughout the entire process of clearance input, stress calculation, and graphical display.
Pang, YiqingCai, HongbinRen, Siyang
Fatigue design is a key common quality technology for improving the quality control capability of China’s automotive products. The fatigue of materials is a multi-scale damage evolution process. Characterizing and processing the large number of three-dimensional defects inside the material, which have different shapes and distributions, and predicting the material’s lifespan based on the cross-scale damage evolution mechanism, is one of the key technologies for fatigue optimization design. This paper discusses the research methods for the fatigue life of aluminum alloy materials. Firstly, based on the staged fatigue damage experiments, the three-dimensional defect features are obtained through CT scanning and reconstruction, and a defect characterization and processing method based on k-d tree and multi-scale feature pyramid is established to accurately represent the topological and geometric relationships of non-uniformly distributed three-dimensional defects. Secondly, a mathematical model for the evolution of micro-damage and macro-cracks is constructed, and the cross-scale transformation of defects is achieved through hierarchical and recursive methods, revealing the cross-scale evolution mechanism of fatigue damage in aluminum alloy materials. Finally, a remaining life prediction model based on defect information and feature weights is established through the support vector regression algorithm (SVR). This research method can provide technical support for the fatigue life optimization design application of lightweight materials such as aluminum alloys.
Zhang, LiangxiaNiu, ZhijunCheng, FangfangChen, HaoYang, Yali
Laser directed energy deposition (LDED) is widely used in various fields due to its fine forming structure and superior performance. However, the characteristics of the hot forming process result in significant residual tensile stress in the formed materials, which affects the capability and useful life of the mechanism accessory. The hybrid manufacturing technology of shot peening (SP) and LDED has a significant influence on the elimination of defects and the improvement in microstructure of formed materials and reducing residual stress, but it also has limitations. To solve the problems, such as the introduction of powders and the difficulty in recycling and classification when using heterogeneous materials for shot peening in hybrid processes, this paper proposes a method of strengthening with the same material, establishes a thermal shot peening simulation model for the hybrid process, and conducts experimental verification. The research finds that the average generated stress of SP in hybrid manufacturing technology is -215.6 MPa, and the thickness of the strengthening layer is about 40 μm. The subsequent hot forming process will eliminate part of the induced stress by SP on the previous deposition, but the deposited stress on the surface is reduced compared with that in the single process. The hybrid manufacturing technology of SP and LDED, based on the same material, effectively utilizes the residual heat from the forming process, providing feasibility for engineering applications.
Zhang, XiaoyuZhang, MinLi, DichenJiang, YunfengChen, XinjinFei, YaHu, YingLiu, Yuyang
The primary mirror support truss of large-aperture segmented telescopes, serving as a critical load-bearing component of the optical system, has its structural stability directly determining the optical imaging quality. This paper adopts a collaborative design method integrating topology optimization and size optimization to address issues, including excessive weight and unreasonable stiffness distribution in traditional support truss designs. First, based on the topology optimization theory of the Solid Isotropic Material with Penalization variable density method, topology optimization was performed on the initial truss structure using finite element simulation software, with the volume fraction as a constraint and the objective of maximizing structural stiffness to determine the optimal material distribution model. Subsequently, the truss structure was reconfigured based on the topology optimization results. Finally, the cross-sectional dimensions of the truss members were selected as optimization variables, and size optimization was performed using the NSGA-II multi-objective optimization algorithm with the objectives of minimizing structural weight and minimizing weighted compliance, while considering constraints such as stress and displacement. The results show that the optimized support truss achieves a 3.9% reduction in weight and a 35.47% decrease in elastic strain energy. This effectively meets the high-precision and lightweight design requirements for telescope support structures and provides a feasible technical solution for the design of large-aperture telescope support trusses.
Tan, DeliGuo, LiquanGao, DedongLiu, ChuanjieDai, XiaodongHuang, Lei
This study aims to verify the accuracy and stability of a system used for measuring and analyzing the welding deformation of vehicle bodies under different welding parameters. A 3D laser scanner was employed to capture the surface topography data of the vehicle’s front deck before and after welding. In order to determine the welding deformation, PolyWorks software was utilized for deformation analysis, which processed the 3D scanning data and compared the post-welding data set. A dedicated vehicle body welding deformation measurement system was developed, including hardware configuration and software development. The BP neural network algorithm was adopted to predict the welding deformation, and the results indicated that the deviation between the predicted values and the average experimental measurements was less than 10%. This confirmed the practicality of the BP neural network in predicting welding deformation and highlighted its effectiveness in technical support for the optimization of welding parameters and deformation control in automotive manufacturing.
Li, LinaZhang, YiqiSun, HongchangWei, Xiezhen
The driving cycle is the basic model of certification of vehicle fuel consumption and emissions, or calibration of powertrains. Standard regulatory driving cycles, such as WLTC, in general assume flat roads during their generation and fail to take into account the strong effect that road gradients have on vehicle operation and driving energy consumption. Such a shortcoming, then, leads to gross mismatches in adaptability when used for urban environments with typical hilly topography. To solve this problem, in this paper, we proposed a method for building driving cycles that consider the impact of slope with actual driving data. Initially, high-precision onboard data collectors were used to generate a total sum of 21, 350 km of driving data from the Munich area, thus creating a diversified driving data set with details such as vehicle speed, slope, and environmental information. Subsequently, joint probability distributions of “speed-acceleration” and “slope-slope change rate” are proposed by using the Micro-trip Method, and a novel chi-squared test algorithm is used to obtain a higher fidelity of urban driving cycle representative of typical conditions. Results of the driving cycle results show that the driving cycle built was close to the actual kinematics, indicating a deviation of less than 5%, and can capture the average uphill characteristic of 1.7%, which is quite well represented. Finally, in fact, validation of whole vehicle environmental chamber tests further demonstrates that the energy consumption prediction error of the developed driving cycle is just 2.2%, much lower than 19.1% error of WLTC. It highlights the importance of considering slope parameters in improving the accuracy of energy consumption calibration for an EV operating on complex slope terrains. Furthermore, it underscores that converting the real-world driving data into lab-based driving cycles can reduce the cost and time of actual road tests for Chinese companies going to the overseas markets, thereby offering support for the international marketing strategy of a global database.
Tian, LichenJiang, PingGao, WangLiang, YongkaiMa, KunqiYu, Hanzhengnan
To address the challenges of binocular vision ranging under complex environmental conditions—such as illumination variations, occlusion, and textureless regions, which result in unreliable and non-robust performance—this paper proposes a multi-source heterogeneous sensor fusion ranging method integrating 4D millimeter-wave radar with the YOLOv5-Monster framework. This method is capable of overcoming the issue of limited ranging accuracy in monocular or binocular vision algorithms under non-ideal imaging conditions. This study achieves high-precision spatial perception through the following specific pipeline: First, Zhang’s calibration method is used to obtain the intrinsic and extrinsic parameters of the binocular camera, and stereo rectification is performed on the raw images. Next, a lightweight YOLOv5 network is employed for object detection, while a high-performance Monster network is utilized to generate dense disparity maps, thereby accomplishing initial depth estimation. To mitigate the inherent depth estimation errors of vision-only systems, 3D point cloud data from a 4D millimeter-wave radar is further introduced. By applying a Kalman filter algorithm, the millimeter-wave radar point cloud and visual outputs are fused, achieving spatiotemporal synchronization and optimal state estimation across modalities and effectively correcting biases in visual ranging. Experimental results show that within the full range of 4 to 150 meters, the relative error of the proposed method remains below 5%. Specifically, the relative errors are 1.25% (absolute error: 0.05 m) at 4 meters, 1.40% at 5 meters, 2.99% at 75 meters, and 4.91% at 150 meters. Compared with the vision-only Monster-YOLOv5 baseline method, the relative error at 150 meters is reduced from 13.16% to 4.91%, representing an accuracy improvement of over 60%. Meanwhile, in terms of long-distance error control, the proposed method significantly outperforms traditional stereo matching approaches such as SGBM+YOLOv5 and BM+YOLOv5, reducing errors by more than 20 percentage points. These results verify that deep multi-modal fusion can enhance environmental adaptability and measurement reliability, providing a high-precision and highly robust solution for distance estimation in intelligent perception systems, which holds important theoretical and engineering significance.
Li, FugaiXie, YuwenSu, HaoLiu, DongleiWu, Qiong
Laser welding technology for aluminum alloy electrode and busbar connections: addressing challenges in battery module assembly. In this work, a CFD framework was built in ANSYS Fluent using a Gaussian rotating heat-source representation, while a VOF approach was used to capture the transient gas–liquid interface in deep-penetration welding. A three-dimensional, transient, thermal-fluid coupled numerical model of the dual-layer heterogeneous aluminum alloy laser deep penetration weld pool was established concurrently with laser deep penetration welding experiments. Results indicate: Peak flow velocities in the weld pool during welding are concentrated along the weld centerline, with flow vectors predominantly directed axially along the weld. Once a quasi-steady keyhole regime is established, vaporization-induced recoil pressure becomes the primary driver governing melt circulation. The liquid metal first impinges on the pool bottom along the keyhole wall and then recirculates upward near the pool boundary, producing strong vortical motion. These findings are intended to support parameter selection and process optimization for laser welding of layered dissimilar aluminum components used in battery tab–busbar assemblies.
Lv, WenjunWu, Yan
Craters are the primary landmarks used for visual navigation in missions exploring small celestial bodies. However, obtaining high-quality, annotated crater data is often challenging due to limited imaging conditions and strict mission constraints. Conventional semantic segmentation models struggle with limited data and are challenging to train effectively. To overcome this limitation, this study introduces a few-shot segmentation approach for crater detection on small celestial bodies. Our method includes a prototype representation module that constructs class-level prototypes to quickly associate crater regions with their semantic features. This paper also designs an iterative learning module that gradually improves the segmentation output, helping the model better capture detailed edges and structures. Tests on a simulated few-shot dataset demonstrate that our method provides reliable and accurate crater segmentation, achieving a mean intersection-over-union (mIoU) of 88.7, outperforming traditional fully supervised methods.
Li, ShuaiZhu, Shengying
To address the challenges faced by micro flapping-wing flying robots in visual navigation—specifically, the large volume of visual information and the difficulty in transforming it into usable intelligent visual data—this paper proposes a clustering-based data-driven approach for directional and image perception. The aim is to enable intelligent visual navigation for flapping-wing robots. The proposed method performs clustering analysis on gyroscope data from the flapping-wing robot to extract directional features. Simultaneously, it applies clustering techniques to visual images captured by the robot to identify intelligent features such as edges. This approach enables the robot to acquire multiple optimized perceptual data types, thereby enhancing the behavior control system. Through the use of clustering analysis, the method not only improves the effectiveness of visual navigation but also extracts features related to visual targets and environmental information, providing technical support for visual target tracking. The experimental platform consists of a flapping-wing robot equipped with an onboard camera, and the proposed clustering-driven visual image perception approach has been experimentally validated. Experimental results demonstrate the high feasibility and effectiveness of the method in practical applications. The main contributions of this study lie in two aspects: (1) a clustering-driven visual image perception method for flapping-wing robots, and (2) a clustering-based approach for identifying posture and behavioral patterns of flapping-wing flying robots.
Li, ZixuanDing, WeiZhang, FengSong, MinLiu, ZhaomingMiao, LeiLiu, HaotianBai, NingTian, ShenCui, LongWang, Hongwei
Optical navigation serves as a critical modality for autonomous guidance during small celestial body landing missions. To address the inherent strong nonlinearities in both the lander’s dynamic model and optical observation model, this paper investigates an invariant extended Kalman filter algorithm based on Lie group structures. First, we establish the state model and optical observation model on the special Euclidean group. Subsequently, a linearized right-invariant error dynamics equation is derived using invariance theory, along with the formulation of state prediction models. Furthermore, the feature vector observation model is modified into a right-invariant observation form, enabling state correction through exponential mapping of innovation vectors. Numerical simulations using asteroid Eros 433 demonstrate that the proposed invariant extended Kalman filter (InEKF) outperforms the conventional extended Kalman filter (EKF) in both estimation accuracy and convergence speed. Notably, the algorithm eliminates the need for online Jacobian matrix computations, satisfying the stringent navigation requirements for autonomous landing operations. The results validate the effectiveness of Lie group-based filtering in handling the nonlinear geometry of pose estimation for irregular celestial bodies.
Liu, ZhengdongZHU, Shengying
Autonomous optical navigation is one of the important navigation methods for the small bodies approach phase. To improve optical navigation performance during the approach phase to a small body, this paper presents a method for extracting the target centroid from sequential optical images. The process begins with fitting a minimum enclosing ellipse to the detected contours in each frame to obtain an initial estimate of the centroid. Building upon this, edge corner points across adjacent images are matched using normalized cross-correlation, and their displacement is tracked using optical flow techniques. The observed pixel trajectories are analyzed, and a predictive model of pixel motion is formulated based on the geometric relationship between the detector and the small body. By combining the directly extracted centroids with the predicted motion of key pixels, a fusion strategy is developed to improve the reliability of the centroid estimation. Finally, numerical simulation results demonstrate that the method significantly improves the accuracy of centroid extraction, thereby enhancing the overall performance of optical navigation during approach operations.
Liu, JingZhu, Shengying
This paper proposes a multi-source dynamic error compensation algorithm for the transfer alignment of airborne optoelectronic payloads. This method addresses performance limitations of micro-inertial navigation systems (micro-INS) in complex dynamic environments, specifically those arising from accumulated device noise and the inability to perform static alignment due to installation errors. The algorithm’s core is the Extended Kalman Filter (EKF) technology. By constructing a “velocity + attitude” matching model between the UAV’s master inertial navigation system (MINS) and the optoelectronic payload’s slave inertial navigation system (SINS), it leverages high-precision MINS navigation information to correct SINS errors. Utilizing a 21-dimensional state space equation and measurement equation, the algorithm achieves real-time estimation and compensation of various errors, including attitude misalignment angles, sensor biases, installation errors, and flexure deformation. Simulation results demonstrate significant alignment accuracy improvement. Post-lever arm effect compensation, velocity errors are stably controlled within 0.01 m/s. Concurrently, flexure deformation angle compensation substantially reduces misalignment angle fluctuations across all directions, enhancing system stability and maintaining low misalignment angles. These findings validate the proposed error compensation strategy’s effectiveness.
Zhang, LuLi, MaoWang, ShiyongLei, Chao
This paper focuses on autonomous drone landing scenarios. Addressing the core requirements of accurate landing site assessment and intuitive visual presentation, it conducts in-depth research on the application of 3D LiDAR (TOF technology) point cloud data. LiDAR captures point cloud data containing 3D coordinates and reflection intensity values. While sparse, non-uniform, and disordered, its high measurement accuracy and strong anti-interference capabilities make it a key sensor for landing terrain perception. Based on a review of recent research results from related teams, this study designed and implemented a comprehensive technical solution: First, raw point cloud data is acquired via the UDP protocol combined with an SDK interface. Preprocessing is then performed using voxel grid filtering (downsampling) and radius filtering (denoising). The assessment area is then divided into a row-by-column grid. A sliding window method is used to calculate the elevation difference, empty grid ratio, flatness, and slope of each grid. Based on these attributes, the grids are classified into six categories: Risk, Warning, Blank, Unknown, No Landing, and Landing. Finally, a grid attribute coloring method and OpenGL 3D rendering are used to generate the visual scene. Through the development of verification programs and moving obstacle experiments, it has been proven that the solution can efficiently process point cloud data and accurately identify safe landing areas, providing key technical support for the engineering realization of the autonomous landing function of drones, and also laying the foundation for the intelligent development of drone landing decisions in complex environments.
Guo, HangyuShi, Zhe
When quadrotor unmanned aerial vehicles (UAVs) operate in urban low-altitude airspace, especially within complex environments, their sensor perception signals are highly susceptible to blockages, deviations, and the inclusion of high-frequency noise. These factors, in turn, induce nonlinear variations in the UAVs’ flight mechanical properties, giving rise to abnormal flight stability issues such as attitude jitter, altitude fluctuations, and trajectory deviations. To address these challenges, this paper puts forward a method aimed at enhancing the positional accuracy of quadrotor UAVs, which is based on Extended Kalman Filter (EKF) multi-sensor fusion. In conjunction with the redundant configuration of sensors, a proportional-integral controller is specifically designed to allow optical flow sensors to compensate for the speed data generated by inertial sensors. Building on the EKF method, a comprehensive data fusion model is established, encompassing both position and speed states. Leveraging the MATLAB platform, trajectory flight simulations are conducted, utilizing multi-sensor data fused via EKF, with the sensor suite including GPS, IMU, Optical Flow sensors, and Barometers. The simulation results demonstrate that this proposed method can effectively mitigate the adverse impacts of environmental interference and sensor noise on the positional accuracy of quadrotors. By continuously correcting position information and accurately estimating position states, it significantly improves the UAVs’ flight position accuracy. This research outcome lays a robust and theoretically sound foundation for in-depth investigations on critical issues related to general aviation applications, such as the safe and efficient autonomous flight, adaptive and reliable intelligent navigation, and ultra-precise and mission-critical operations of quadrotor UAVs, thereby significantly contributing to the sustained and innovative advancement of the field.
Cui, NanLiu, WenzhiLiu, HanqiWang, JingruiWang, ZhizhongZhi, Haonan
In this study, high-speed back-illuminated imaging and laser-induced fluorescence (LIF) methods were employed to investigate the impingement behavior of millimeter-sized single isooctane drops on a dry solid wall and various liquid films, including isooctane and glycerol solution films of different concentrations. Various fuel spray impingement scenarios in gasoline direct injection engines were examined. High-speed back-illuminated imaging was primarily used to examine the impact of fuel drops on a dry wall and a fuel film of the same composition as the drops. The LIF method was used to examine the impact of fuel drops on the glycerol solution film, allowing for the distinction between fuel drops and the glycerol solution film. The impingement behavior varied depending on the Weber number of the incident drop and the wall condition. When fuel drops impacted the solid dry wall vertically, they spread into a circular liquid film. The outer edge of the liquid film folded and bulged, and upon reaching the maximum spreading diameter, it maintained equilibrium and did not retract. When isooctane fuel drops impacted the isooctane film, they broke and splashed, with thinner films producing stronger splashes. Additionally, the Weber number of the fuel drops significantly influenced the crown shape and splashing after impact. The impingement behavior of fuel drops on the glycerol solution film was also investigated, focusing on the liquid film morphology after impact. Based on the experimental data, empirical correlations were established between the critical Weber numbers for transitions among different crown morphologies and the dimensionless film thickness under varying film viscosities.
Yang, TianLu, LiliGuo, ZongweiSong, EnzheYao, ChongNing, YilinKe, Yun
This paper presents an innovative study in exploring, evaluating, and implementing deep-learning architectures for the calibration of multimodal sensor systems. The aim of this paper is to leverage the use of sensor fusion to achieve dynamic, real-time alignment between 3D LiDAR and 2D camera sensors. Static calibration methods are tedious and time-consuming, which is why we propose utilizing conventional neural networks (CNNs) coupled with geometrically informed learning to solve this issue. We leverage the foundational principles of extrinsic LiDAR–camera calibration tools such as RegNet, CalibNet, and LCCNet by exploring open-source models that are available online and compare our results with their corresponding research papers. Requirements for extracting these visual and measurable outputs involved tweaking source code, fine-tuning, training, validation, and testing of each of these frameworks for equal comparisons. This approach aims to investigate which of these advanced networks produces the most accurate and consistent predictions. Through a series of experiments, we reveal some of their shortcomings and areas for potential improvements. We find that LCCNet yields the best results among all the models that we validated.
Karramreddy, Venkat Sai RaxitMitchell, Liam
This paper presents a monocular vision-based system for high-precision missile pose measurement using ArUco markers and Perspective-n-Point (PnP) algorithms. By deploying 6 × 6 ArUco markers on a cylindrical missile mock-up, the system establishes 3D-2D correspondences between structured-light-scanned models and camera images to solve the PnP problem. The proposed approach integrates optimized ArUco marker recognition — leveraging adaptive thresholding, contour simplification, and grid-based validation — with the Efficient PnP (EPnP) algorithm to achieve real-time pose estimation. Experimental validation demonstrates angular accuracy of ± 0.3° in roll/pitch/yaw and positional accuracy of ± 2 mm within a 2 m range under controlled conditions. The system exhibits robustness against partial occlusions and motion blur, with degraded performance (± 1.2°, ± 5 mm) in extreme scenarios. Key innovations include a streamlined marker detection pipeline and adaptive pose refinement using Levenberg-Marquardt optimization. This work provides a cost-effective, non-contact solution for flight tests, with potential applications in weapon separation testing.
Wang, RuiyangZhang, Chaofan
In order to reduce traffic accidents caused by cars straying from lanes, a lane line recognition and deviation warning system based on machine vision is designed. It mainly includes image preprocessing, lane line detection, and the design of a deviation warning model. “In this study, an ROS-based intelligent vehicle-mounted camera is adopted for road image collection. To reduce the computational load of data processing while guaranteeing the algorithm’s accuracy and reliability, grayscale conversion and region of interest (ROI) extraction are implemented to finish the image preprocessing stage. Additionally, a fusion strategy of global and local thresholds is introduced to enhance both the operational speed and detection accuracy of the algorithm” use the Canny operator for the edge feature extraction; and complete the fitted lane lines with the improved Hough transform. Finally, based on the Kalman filter and camera viewpoint conversion coefficient algorithm, the lane line offset is detected in real time, and the deviation is judged in combination with the monitoring interface. Simulation experiments show that the system is able to effectively recognize the lane line and judge the deviation status under the condition of setting the offset threshold of 70 pixels, which significantly improves the accuracy and real-time performance of the lane deviation warning and provides effective technical support for reducing traffic accidents.
Wang, XufengZhang, ChunshuWang, YanChen, YihuiJi, Rui
Gyroscopic effects split circumferential traveling-wave resonances of rotating structures into forward and backward branches. This work first analyzes the splitting in the co-rotating (Lagrangian) frame to provide physical intuition for the evolution of the two branches with spin speed. A transformation to the inertial (Eulerian) frame is then derived, showing that the observed frequencies are shifted by a kinematic Doppler-like term that acts with opposite sign on the forward and backward waves, leading to different Campbell-diagram slopes depending on the observation frame. The resulting framework is validated experimentally on a freely rotating, unloaded tire using two complementary sensing modalities: wireless on-tire accelerometers (co-rotating view) and a scanning laser Doppler vibrometer (inertial view). A frequency-domain SVD-based identification (FDD/ODS-SVD) is used to extract poles and deformation patterns over a range of spin speeds, enabling Campbell diagrams in both frames. The application of the proposed transformation maps the co-rotating branches onto the inertial observations, yielding consistent forward/backward splitting between the two measurement systems.
del Fresno Zarza, JavierNaets, Frank
This SAE Aerospace Recommended Practice (ARP) provides information and guidance for the control of hazardous laser exposure in the navigable airspace. This ARP does not address techniques that pilots can apply to mitigate laser illuminations during a critical phase of flight. Such mitigation strategies are described in ARP6378.
G-10T Laser Safety Hazards Committee
This document applies to laser proponents involved with the use of laser systems outdoors. It may be used in conjunction with AS4970, ARP5535, ARP5572, and the ANSI Z136 series of laser safety standards.
G-10T Laser Safety Hazards Committee
In the two months since Microvision bought Luminar and acquired key tech and talent, the sensor company has been busy. In that time, they've merged key lidar units from each company and created a perception software stack to run it in a convincing demo of its ADAS and autonomous capabilities. The company is also pushing innovative lidar tech into the defense drone and antidrone markets, already working with a German defense supplier that works with NATO member countries.
Clonts, Chris
Polymeric optical materials such as Cyclo Olefin Polymer (COP) are adopted in aerospace lighting systems due to their excellent optical clarity, dimensional stability, moldability and weight saving advantages over glass. However, their relatively low toughness and the presence of residual molding stress make them prone to crack initiation during mechanical fastening. During its installation, crack formation was consistently observed around self-tapping screw interfaces, raising concerns over reliability, maintainability, and compliance with durability requirements. A structured Design of Experiments (DOE) was performed to identify root causes and evaluate potential mitigation methods. The investigation revealed that residual stresses in the COP material, combined with localized stress concentrations during screw tightening, were the primary drivers of crack initiation. Two complementary process improvements were identified and validated as part of mitigation plan: (i) annealing of the optics prior to assembly to relieve internal stress, and (ii) using step-torquing method to fasten the screws, to gradually distribute applied loads and reduce localized stress peaks. Post-assembly observation over three days confirmed a significant reduction in crack initiation. The combined annealing and step-torquing approach demonstrated a substantial reduction in crack generation probability, providing a practical and repeatable process for enhancing the robustness of polymeric optic assemblies. This work contributes a generalizable methodology for mitigating assembly-induced failures in advanced polymer materials and supports broader adoption of lightweight, high-performance optics in aerospace applications.
S, NikhilSingh, Abhimanyu KumarKatageri, PraveenSP, PradeepChandra, Praveen
This study systematically evaluated the wear resilient performance of AZ61 magnesium alloy reinforced with 15 wt.% SiC and diverse amounts of multi-walled carbon nanotubes (MWCNTs) under dry sliding circumstances adopting pin-on-disc apparatus (ASTM G99). To identify the influence of factors like sliding speed (SS) (1-3 m/s), axial load (AL) (10-30 N), and MWCNT concentration (0-3 wt.%) that affect tribological performance, experiments were developed using a Central Composite Design (CCD) under Response Surface Methodology (RSM). SEM micrographs revealed a dispersion optimum near 2 wt.% MWCNT, where CNTs anchor to SiC and bridge the α-Mg matrix, while 3 wt.% shows agglomerates and micro-voids. Findings showed that wear loss (WL) and friction coefficient (CoF) was greatly amplified by increasing AL owing to localized heating and contact stresses. A compacted tribolayer was formed by increasing SS, which decreased WL but marginally raised the CoF. At low AL (10 N), SS (2.09 m/s), and 2.12 wt.% MWCNT, the wear resistance was significantly improved by improving load transfer and creating a lubricating carbon-rich coating, resulting in a decreased WL of 0.006 g. The CoF persisted within the range of 0.19 to 0.28. Agglomeration of MWCNTs caused increased WL and CoF when the MWCNT content is increased above 2 wt.%. Worn-surface microscopy at the optimum showed fine wear tracks and a continuous carbon/oxide glaze, evidencing a lubricious CNT-rich third-body film, whereas high AL/low MWCNT produced deep grooves and delamination.
Senthilkumar, N.
Additive Manufacturing (AM) process involves building part layer by layer. Some of the AM processes ( Laser and Electron beam based) generate a melt pool during printing process. This melt pool can be captured periodically during AM process using special optical arrangements. These images capture high intensity melted zone, heat affected zone, splattered molten metal particles and overall shape of the melt pool. These images carry similar characteristics for good AM processes within a range. When there is an anomaly the above said characteristics of the melt pool changes, for example a low intensity melted zone signifies low energy condition which can lead to defects like balling etc. Hence the captured image at this condition appears significantly different from other images. The common defects which can be detected by analyzing melt pool images are porosity, spatter, lack of fusion, cracks, balling and keyhole instability. There are many machine learning methods available to quantify this (supervised and unsupervised). The proposed approach does not require a trained machine learning (ML) model from scratch but rather utilize a pretrained self-supervised vision transformer (ViT) model DINO v2. The melt pool images acquired during the additive manufacturing (AM) process are processed by DINO v2 ViT model. These future vectors or embeddings for all printing instances are extracted and stored for downstream processing. Zero shot classification (accept or reject) of an AM printing instance is done by comparing the production printing instance image with a baseline printing instance image at the same spatial coordinates using Euclidean distance metric. This baseline Euclidean distance metric is established from multiple printed instances of the baseline coupons and by calculating root mean square deviation (RMSD) at each spatial coordinate of the print instances. The deviations of the production print instances are calculated by calculating RMSD of the Euclidean distances of embeddings of the melt pool images with that of baseline image embeddings at the same spatial coordinates. The deviations observed can be correlated to actual defects by analyzing AM printed parts layer by layer at each spatial coordinates using destructive or non-destructive testing techniques. The scope of this paper is only on establishing the deviation calculation methodology.
Kuppusamy, Balasundar
Aircraft lighting systems play a vital role in ensuring operational safety, visibility, and regulatory compliance. Exterior lighting systems are essential for aircraft identification, navigation, collision avoidance, and ground operations under varying environmental conditions. These systems typically include navigation lights, anti-collision lights, landing and taxi lights. An aircraft lighting system comprises light sources, optical elements, electronic control units, power interfaces, wiring harnesses, and mechanical mounting structures. Among these components, optics are critical as they control light distribution, intensity, color accuracy, and efficiency while withstanding harsh aerospace environments such as vibration, thermal cycling, and aerodynamic loads. Aircraft exterior lights are subjected to severe thermo-mechanical stresses due to aerodynamic loading, vibration, and thermal cycling. The use of high-performance optical polymers such as Cyclo Olefin Polymers (COP) provides excellent light transmission and stability; however, their relatively lower mechanical toughness makes them susceptible to stress-induced cracking during assembly. In the baseline configuration, the Circuit Board Assembly (CBA) was fastened directly onto the optic using self-tapping screws. During assembly, frequent crack initiation was observed in the optic around the fastener locations, leading to concerns regarding reliability and maintainability. To address this issue, a redesigned mounting approach was developed that eliminated direct fastener penetration into the optic. Instead, the CBA is retained using a precision clamping mechanism, thereby distributing assembly loads uniformly and avoiding localized stress concentrations. COP material was retained due to its superior optical characteristics and compliance with photometric requirements for aircraft lighting applications. The redesigned optic-CBA interface was validated through Highly Accelerated Life Test (HALT), incorporating combined vibration, temperature, and thermal shock profiles. Test results confirmed that the new clamping design prevented crack formation, improved mechanical robustness, and ensured long-term optical performance. This paper presents the problem definition, root cause analysis of fastener-induced cracking, the design rationale for adopting a clamp-based mechanism, and detailed HALT validation results. The study highlights the importance of integrating material properties, fastening strategies, and environmental testing in the design of aerospace lighting systems. The proposed design methodology provides a pathway to enhance reliability and lifecycle performance of critical optical components in aircraft applications.
Vialta, FredericoS, NikhilKatageri, PraveenSP, PradeepSingh, Abhimanyu Kumar
Polypropylene, a commodity plastic, is the semi-crystalline thermoplastics widely used in high volume for general purpose application. Polypropylene is the macro molecules of soft and weak backbone, which by reinforcement of fillers in different forms such as fiber, spheroids, nanotubes, flakes, etc., can influence its mechanical, thermal, electrical, creep resistance, and flame resistance properties for use in aerospace applications. Currently, polycarbonate and nylon plastics are used in aerospace applications, however, they are expensive compared with polypropylene. In this thesis, efforts are put to study the effect of reinforcement fillers in the properties of polypropylene composite, primarily the mechanical and flammability properties. The matrix element, polypropylene co polymer and reprocessed polypropylene blended in equal ratio, are coupled with the dispersing phases such as graphene, mica, fumed silica, and polydimethylsiloxane polymer. Effect of graphene as reinforcing filler at different weight % to polypropylene composite’s properties are studied and compared with that of the neat polypropylene. Effect of coupling agent, Aminopropyltriethoxysilane (APTES), on mineral fillers and Polydimethylsiloxane polymer (PDMS) used for crosslinking with the polypropylene matrix is also studied and compared using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM) techniques.
Govindaraju, Parthasarathy
Compliance verification in aerospace systems often relies on labor-intensive workflows that demand extensive manual effort to produce structured review documentation and requirement matrices. These processes can span dozens of hours per review, are vulnerable to inconsistencies due to non-standardized annotations, and depend heavily on individual interpretation of fragmented technical sources. With a growing backlog of review tasks and a steady influx of new requests, the need for scalable automation has become increasingly important. This study presents a modular automation framework designed to streamline compliance assessments through intelligent document parsing, requirement extraction, and matrix generation. The system integrates optical character recognition, computer vision, and natural language processing techniques to process both scanned and digital documents. By digitizing data across multiple hardware configurations and automating extraction from diverse technical records, the framework enables consistent evaluation across a broad spectrum of requirement categories. Automation scripts and standardized templates facilitate rapid population of compliance matrices, reducing manual hand-offs and minimizing reliance on specialized expertise. Implementation led to a 39% reduction in turnaround time and a 62% increase in monthly throughput, demonstrating measurable efficiency gains in the compliance review process. This framework exemplifies how intelligent automation can drive operational efficiency, deliver measurable cost savings, and pioneer data-driven and scalable innovation in aerospace compliance engineering.
Mirani, HarshBaviskar, Yash G.
Under a microscope, a bouquet of lollipop-like structures, each smaller than a grain of sand, waves gently in a petri dish of liquid. Suddenly, they snap together, like the jaws of a Venus flytrap, as a scientist waves a small magnet over the dish. What was previously an assemblage of tiny passive structures has transformed instantly into an active robotic gripper.
Medical imaging technology is advancing rapidly, bringing new opportunities and challenges for machine designers. Systems that once required dedicated hospital rooms and significant floor space are becoming more compact, faster, mobile and capable of delivering increasingly detailed clinical insight. From advanced CT scanners to imaging platforms integrated with surgical robotics, imaging equipment is evolving toward more point-of-care (POC) solutions to meet rising expectations for diagnostic accuracy, procedural guidance and operational efficiency.
As satellites take on more onboard processing - from Earth imaging to autonomy - spacecraft computing designers are pushing for higher performance under tight thermal and radiation constraints. Here's how suppliers are approaching heat removal, radiation mitigation and production-scale space-grade computing for LEO and beyond.
Space vehicle and satellite development programs are driving demand for new small- and medium-sized satellites across commercial and defense imaging, data collection, and other space-based applications.
This study investigates the unsteady aerodynamic response, wake evolution, and vortex dynamics of an ultra-large floating offshore wind turbine (FOWT) under coupled motion–wave conditions. A high-fidelity aero–hydrodynamic CFD model is employed for the IEA 22 MW reference turbine. Platform pitch and surge motions are prescribed via sinusoidal functions, and wave conditions are independently introduced by considering two representative sea states (H = 4 m and 7 m) and a no-wave case. Results show that pitch and combined pitch–surge motions significantly amplify unsteady aerodynamic effects, increasing peak power from 81.1 MW (P5S0) to 92.6 MW (P5S5), with periodic negative power output and severe dynamic stall. Under strong motion, waves further raise peak power to 93.4 MW (H7P5S5), indicating a coupled amplification effect. Dynamic stall is mainly triggered by pitch motion, expanding in scope and duration with motion amplitude; wave effects on stall remain limited. Platform motion also enhances wake recovery by increasing inflow shear and turbulence, leading to higher turbulent kinetic energy (TKE) and a reduced velocity deficit (ΔŪ). Waves compress the low-speed wake core and reduce ΔŪ from 0.248 (no-wave case) to 0.204 under H7 conditions at x/D = 3.0, with the effect being particularly evident under combined motion. Vortex visualization reveals that platform movement leads to vortex merging, ring thickening, and deflection, with combined motion creating the strongest mixing. Wave-generated vortices interact with tip vortices near the surface, becoming more intense under larger wave heights. In general, platform motion is the main factor in FOWT unsteady aerodynamics, while waves have secondary but cooperative effects by changing inflow structures and aiding wake recovery. This study offers theoretical support and engineering guidance for aerodynamic design optimization and wind farm layout of next-generation ultra-large floating offshore wind turbines.
Xie, BinSun, HaiyingChen, Ye
Robotic ultrasound scanning technology is a research hotspot in the field of medical imaging, and can achieve standardized and high-precision data acquisition. However, large force tracking errors occur during scanning, especially in complex human tissues, which can severely degrade image quality and diagnostic accuracy. Therefore, we propose an adaptive speed-regulated impedance control strategy to address this challenge, which innovatively combines the spline real-time interpolation and impedance control for constant force tracking. Firstly, the discrete ultrasound scanning paths are fitted to generate a smooth and synchronized interpolation trajectory. Then, the speed of the reference trajectory is adjusted in real time based on the Taylor formula to reduce the force tracking error. Experimental verification was conducted, and the results showed that the force tracking error increases with the increase of trajectory speed. In addition, at high speeds (e.g., 10 mm/s), the mean/variance of the force tracking error of the proposed method (0.3067N/0.2784) is reduced by 31.1%/37.4% respectively compared with the mean/variance of the traditional impedance control (0.4452N/0.4448), fully demonstrating the effectiveness of the proposed control strategy.
Min, KangZhang, LeShi, YudongFang, JinMo, HangjieLi, Xiaojian
Pulsed lasers serve as critical components across a diverse spectrum of modern applications, ranging from precision manufacturing and medical equipment to advanced defense systems. Their performance is fundamentally governed by the pulsed power supplies that act as their energy source, where output characteristics such as stability, rise time, and efficiency directly dictate the quality and reliability of the laser output. Aligned with the prevailing industrial trend towards miniaturization and digital control in semiconductor laser pump drivers, this paper introduces a high-power, high-repetition-frequency pulsed laser power supply. The proposed design is architect ed around a phase-shifted full-bridge charging network for efficient energy transfer and a modular, switched-mode constant-current pulsed discharge network for precise output shaping. This integrated architecture provides versatile and independent control over key output parameters, including current amplitude, pulse width, and repetition frequency, offering significant flexibility for various operational requirements. The adopted switched-mode constant-current driving technique presents a substantial advantage over conventional linear constant-current methods. It drastically reduces conduction losses inherent in linear regulators, which is a decisive factor for enhancing overall system efficiency, particularly in demanding long-pulse application scenarios where thermal management is challenging. This work comprehensively details the systematic modeling, in-depth analysis, and tailored control design undertaken for both the front-end charging network and the rear-end pulse-forming modules. To validate the design methodology and practical performance, a functional prototype was developed and subjected to rigorous testing. Experimental results confirm that the prototype achieves a maximum constant-current pulsed output of 400 A, featuring a remarkably fast rise time of less than 10 μs. Furthermore, it demonstrates a wide range of operable pulse widths up to 1000 μs and sustains a maximum repetition frequency of 1000 Hz, thereby meeting the stringent demands of advanced high-power pulsed laser systems.
Huang, DeLu, JiaweiYang, ZhiqingXv, ZiyiXing, Hui
To address the growing demand for waste management, improve the efficiency and accuracy of waste classification, reduce costs, promote environmental protection and circular economy development, and solve environmental pollution and resource waste problems through technological innovation. This paper proposes an intelligent mobile waste classification and collection robot system. The system consists of a picking mechanical arm subsystem, a waste classification and collection subsystem, a self-moving chassis subsystem, and a solar tracking power generation subsystem. The picking mechanical arm subsystem actively collects waste through a mechanical arm combined with machine vision technology and deposits it into the waste classification device, while the waste classification and collection subsystem completes functions such as classification, compression, collection, and dumping, utilizing a navigation and positioning-driven chassis to achieve autonomous waste collection, simultaneously employing an AI (Artificial Intelligence) interactive voice broadcast device for waste classification promotion. The operation and control of each subsystem are fed back to the client through remote network connection devices, achieving “unified network management.”
Xia, YingZhu, HuabingJia, RuitongHe, YifanHou, WentaoFu, ShaozaoLin, Jiaoyang
End-to-end autonomous driving in urban environments faces three core challenges. First, camera and LiDAR sensor heterogeneity causes cross-modal perception inconsistencies and sensor fusion instability. Second, diffusion models suffer from training instability due to scale variance and distribution changes, which limits generalization. Third, traditional trajectory decoders lack structured interaction with semantic elements, thereby undermining planning rationality. To address these issues, CMFPNet introduces an integrated framework with three key modules. The HGCF-Backbone integrates LiDAR and camera features using channel focus, deformable cross-focus, and state space modeling to enhance semantic alignment. The NST module maps physical trajectories to normalized space, employing truncated diffusion sampling for stable generation in just 2–4 steps. The NDA models trajectory generation as a semantic narrative, utilizing a six-stage semantic attention flow incorporating BEV context, interactive dynamics, and self-states. Experiments on the NAVSIM dataset demonstrate CMFP Net’s superiority over existing baselines, showing outstanding generalization and trajectory stability in challenging scenarios. Notably, the truncated sampling strategy achieves an 8–10× acceleration during inference while maintaining decision accuracy and reducing computational costs. CMFPNet provides a scalable, semantically consistent solution for diffusion-based autonomous driving with significant potential in both research and practical deployment.
Qu, YanweiMo, Hangjie
This article focuses on the problem of high labor cost, low processing efficiency and poor automation of the existing equipment in the postharvest processing of Chinese cabbage. It will design and produce an automated Chinese cabbage processing method called Smart Fresh Pack. Root removal, leaf removal, washing, loading, weighing, packaging and labeling functions were integrated, and smart dexterous intelligence was applied to core concepts and this can be used in the bulk production scenario of supermarkets in the city and countryside Compared with traditional assembly line equipment, obvious advantages in terms of structure, function and processing capacity: Key innovations include: Low-pressure air jet cleaning replaces water washing, which prevents a second contamination and weighing error due to surface moisture; pneumatic gripper and multi-DOF robotic arms combine to package and dynamically weigh simultaneously, streamlining these tasks; machine vision relies on an SSD-MobileNetV2 visual model with Sobel edge detection to locate and identify wilted leaves; and pairing with a multi-threaded control structure for millisecond level closed-loop response. I used Fischertechnik models to build and simulate, checking whether the motion logic of this design is reasonable, whether the stresses are safe, and whether the airflow cleaning is effective. This machine finishes the complete processing of one cabbage just within one minute, its modular and its maintainance and scalability aspects are also there, it gives small and medium size agricultural entities a low cost but also very effective clean vegetable processing route, this is truly good for making progress with the auto, standard and green developments within agric prd processing.
Chen, YuhuiZhang, YixuanRuan, JiaZhu, HuayunHe, LianzhengZhao, Ping
This paper presents the design of a novel intelligent monitoring platform for low and medium altitudes, aiming to offer a new solution for the development of intelligent equipment operating in this airspace. Current monitoring tasks are primarily performed by fixed-wing and multi-rotor UAVs, but these platforms face significant technical bottlenecks in flight endurance and monitoring precision. This research aims to address these deficiencies. The platform is based on a small-scale unmanned airship featuring a semi-rigid, hybrid lift-body structure. Improvements were made upon the traditional ellipsoidal hull; the hull profile was optimized using a geometric superposition method, introducing an aerodynamic camber line with a maximum camber (m) of 4% to enhance aerodynamic performance at small angles of attack. In terms of its energy system, the platform is powered by a purely electric energy system composed of solar panels and batteries; solar energy is used during the day, while surplus energy is stored in the batteries for night operations, thereby effectively extending flight endurance. For intelligent monitoring, the platform integrates an intelligent recognition and positioning system based on machine vision, which is deployed on a Jetson Nano and utilizes a YOLO11 instance segmentation model. The team has experimentally proven that the platform can effectively achieve intelligent monitoring in low and medium altitude airspace. Furthermore, the structural integrity of the gondola and the aerodynamic advantages of the modified hull have also been verified via simulation analysis. This work provides a new design concept for intelligent monitoring equipment. The platform can also be applied to scenarios such as forest fire prevention, precision agriculture, and long-term ecological monitoring, offering a new solution for the design of unmanned intelligent monitoring equipment.
Song, ZiangGao, WenxuanCao, XiaochuanZheng, XingZhao, Chong
The aging of the population has been a key issue worldwide, with mobility and fall of the elderly an important problem to be solved. In this paper, we propose an elderly mobility assist system based on the intelligent power-assisted device consisting of an assistive cane and an intelligent companion. It has the functions of standing support after falling, daily support and on-site rest. The assistive cane adopts a two-stage expansion mechanism of crank and slider structure, which forms a stable triangular support after unfolding, so that the patient can stand safely. The intelligent companion platform is driven by drive wheels, equipped with pushrod motors and vacuum suction devices, it can automatically approach the user and form an stable support column when the cane is in the out-of reach range; the control system is designed by combining microcontroller, camera object recognition, wristband remote control, to realize automatic steering and autonomous navigation at differential speed. The overall design satisfies the requirements of safety and strength through mechanical verification and stress analysis. The proposed system can help the elderly people to recover from falls better and enhance their independence and safety in their daily walks.
Yu, ChenxiWang, LongyiZhu, HuayunDong, YanMi, RuixueZhu, Lihong
The Army requires rotorcraft drive systems to operate for 30 minutes following a loss of lubrication event to make an emergency landing. Coatings research has shown great promise for loss of lubrication, but coating repeatability and quality control is a primary hurdle. The Army partnered with Acree Technologies via a Small Business Innovation Research (SBIR) effort to develop an optimized gear coating for loss of lubrication. The research culminated in a system level transmission experiment that maintained flight relevant torque and speed through a helicopter gearbox without oil for three hours. The authors decided to shutdown the experiment for inspection after three hours of operation without oil because the temperature and vibration signals maintained steady state conditions without signs of failure. Teardown analysis showed the transmission gear surfaces did not scuff, scanning electron microscope analysis showed coating remained on the gear teeth, and cross-sectional SEM analysis showed a measurable coating thickness remaining on the gear teeth after three-hours of operation without oil.
Riggs, MarkPomplon, WilliamFetty, JasonMilligan, RyanWoods, RonWong, KelvinMatzke, CalebJacques, KellyHood, Adrian
This study investigates the aerodynamic response of a small-scale UAV propeller under steady and transient conditions at low Reynolds numbers (104–105;). In this regime, phenomena such as laminar separation, transition, and the formation of recirculation bubbles strongly influence airfoil performance. In addition, the flow response to rapid changes in rotational speed is still poorly understood, as most existing models assume quasi-steady behavior. Experiments were conducted in a low-speed wind tunnel using a commercially available 10-inch class propeller (X500 V2 1045). The propeller was subjected to controlled rotor speed ramps, and phase-locked particle image velocimetry (PIV) was combined with synchronized load measurements to track the flow evolution during acceleration and deceleration. A hysteresis was observed in the thrust response when comparing increasing and decreasing rotational speed at identical operating conditions. At the same time, the PIV measurements reveal that the inflow field and the effective angles of attack at the blade scale evolve dynamically throughout the transient. These findings highlight the importance of transient trajectories in low-Reynolds-number propeller operation and show that quasi-steady models are insufficient to describe the observed aerodynamic behavior.
Ratz, ManuelMendez, Miguel AlfonsoSciacchitano, AndreaSchram, Christophe
This paper presents an experimental investigation of ship airwake-rotor interaction under cruise-only and longitudinal gust conditions (cruise + gust). A model-scale NATO Generic Destroyer and rotorcraft were tested using time-resolved stereoscopic particle image velocimetry, a six-axis force/torque load cell, and flush pressure sensors. Flow structures, pressure distributions, and spectral energy within the pilot workload-relevant frequency bands were analyzed. High-pressure regions on the ship deck surface show the interactions between the ship recirculation region and rotor ground effects from downwash. The reduced forward velocity within the airwake leads to decreased thrust and a nose-down pitching moment across the ship deck. For high-disk-loading rotorcraft, the rotor ground effects are less important than the ship airwake effects. The power spectral densities of CT, CMx, and CMy decrease toward higher frequencies, while the PSDs of CFx and CFy retain comparatively higher energy at the upper end of the full-scale pilot workload frequency band. A maximum increase of 54.3% in the CMy pilot workload factor in the cruise + gust conditions is observed at Ldeck, which denotes a significant rise in the demand of pilot inputs near the ship stern. The overall pilot workload factor in the cruise + gust case increased by 35.6% compared to cruise-only at 1.5Ldeck, and decreases into the deck. Overall, gust-driven airwake dynamics intensify rotor loading and increase pilot workload demands during shipboard helicopter operations.
Yon, StevenLi, Sicheng Kevin
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