To improve the operational efficiency of wind turbines and optimize the operation and maintenance costs of wind farms， this paper combines time-domain feature index analysis with multi-sensor information fusion technology to propose a wind turbine gearbox state monitoring method based on grey wolf optimization （GWO） algorithm‑support vector machine （SVM）. Firstly， different time-domain statistical eigenvalues representing vibration energy are calculated， and parallel stacking is used for feature level and data level fusion to obtain an information fusion matrix. Secondly， on this basis， establish a fault diagnosis classification model based on GWO-SVM. Finally， the proposed method is validated and analyzed using the measured data of the gearbox collected from the QPZZ-Ⅱ rotating machinery vibration test. The results show that this method is significantly better than other traditional methods， and its classification and diagnostic accuracy demonstrate significant advantages.
Background: General aviation pilots are, anecdotally, referred to as “weekend warriors” due to their flying infrequency. Considering that flight skills erode with irregular practice/reinforcement, we determined whether private pilots (PPLs) fly/train sufficiently to operate safely in the context of slow flight, a skill critical for safe operations and which rapidly atrophies with <~51 h flight time/8 months per prior research. Method: Slow-flight-related aviation accidents (2008–2019) were per the NTSB Access<sup>R</sup> database, and fatal mishap rates were calculated using general aviation fleet times. Eight-month flight histories of airplanes in single PPL ownership were captured retrospectively using FlightAware<sup>R</sup>. PPL survey responses were collected between January and March 2025. Statistical tests employed proportion/Independent-Samples Median Tests and a Poisson Distribution. Results: The slow-flight-related fatal accident rate (2017–2019) trended downwards (<i>p</i> = 0.077). In-flight tracking of 90 airplanes revealed an 8-month median flight time of 6 h, which is well below the aforementioned 51 h requisite for safe operations. Of the aircraft flown < 51 h, only 9% engaged in slow-flight practice. In the online survey, only the upper quartile of 126 PPLs achieved the aforementioned time requisite for preserving slow-flight skills, but nevertheless, 89% of respondents attested to being flight-proficient. Conclusions: Persistence in slow-flight-related fatal accidents likely partly reflects PPLs’ deficiency in in-flight time/slow-flight practice.
Damage detection is a critical link of aviation equipment development，field operation and maintenance，which directly affects the development process and service safety of aircraft structure. In recent years，domestic and foreign scholars and scientific research institutions have carried out a lot of research works in the field of ultrasonic nondestructive testing. Based on this，this paper，guided by the needs of damage detection in the development and operation of aviation equipment，briefly analyzes the characteristics and requirements of typical structural damage of aviation equipment and in-situ detection. This paper focuses on summarizing the latest research progress of ultrasonic theories and methods，advanced detection sensor designs and special detection device research and development. Furthermore，incorporating new issues，ideas and directions emerging from technological research and engineering practice，this paper summarizes and forecasts the main challenges and future development trends in areas such as damage detection technologies for heterogeneous materials，transducer design methods for complex-shaped structures，and the equipment research and development and engineering application of new non-contact testing devices.
The development of advanced air mobility—an eco-friendly, next-generation transportation system—is underway and garners significant attention. Due to the novel propulsion concept of eVTOL (electric Vertical Take-Off and Landing) and its operation in low altitude, urban environment, regulations for commercialization have not yet been established. Consequently, related research on passenger safety in emergency landings is ongoing, and this study focuses on enhancing the crashworthiness of advanced air mobility. To ensure the crashworthiness of advanced air mobility, civil airworthiness standards were referenced to determine the appropriate test conditions, and a design criterion for developing an energy-absorbing structure was derived. In this study, lattice structures are considered for designing an energy-absorbing structure that satisfies the design criterion, and finite element analysis is conducted to predict the performance of lattice structures. Based on the predicted data, surrogate models are constructed using the Kriging method according to the type of lattice structure. To verify the data obtained from numerical models, representative structures are manufactured using EBM (Electron Beam Melting) technology, and compressive tests are conducted to obtain the force–displacement curves. The test data are compared with the numerical data, and it is confirmed that the test data show good agreement with the numerical data. After this confirmation, the constructed surrogate models are utilized to select a lattice-based energy-absorbing structure that satisfies the crashworthiness-related design criterion. Finally, a crash simulation of a vertical drop test is carried out using the selected lattice structure, and results indicate that the resulting acceleration due to the collision is below the human tolerance limit, thereby verifying the crashworthiness of the energy-absorbing structure.
High-resolution sub-meter satellite data play an increasingly crucial role in the 3D real-scene China construction initiative. Current research on 3D reconstruction using high-resolution satellite data primarily focuses on two approaches： Multi-stereo fusion and multi-view matching. While algorithms based on these two methodologies for multi-view image 3D reconstruction have reached relative maturity， no systematic comparison has been conducted specifically on satellite data to evaluate the relative merits of multi-stereo fusion versus multi-view matching methods. This paper conducts a comparative analysis of the practical accuracy of both approaches using high-resolution satellite datasets from diverse geographical regions. To ensure fairness in accuracy comparison， both methodologies employ non-local dense matching for cost optimization. Results demonstrate that the multi-stereo fusion method outperforms multi-view matching in all evaluation metrics， exhibiting approximately 1.2% higher average matching accuracy and 10.7% superior elevation precision in the experimental datasets. Therefore， for 3D modeling applications using satellite data， we recommend adopting the multi-stereo fusion approach for digital surface model （DSM） product generation.
This paper presents a new technique for estimating the two-dimensional direction of departure (2D-DOD) and direction of arrival (2D-DOA) in bistatic uniform planar array Multiple-Input Multiple-Output (MIMO) radar systems. The method is based on the reduced-dimension (RD) MUSIC algorithm, aiming to achieve improved precision and computational efficiency. Primarily, this pioneering approach efficiently transforms the four-dimensional (4D) estimation problem into two-dimensional (2D) searches, thus reducing the computational complexity typically associated with conventional MUSIC algorithms. Then, exploits the spatial diversity of array response vectors to construct a 4D spatial spectrum function, which is crucial in resolving the complex angular parameters of multiple simultaneous targets. Finally, the objective is to simplify the spatial spectrum to a 2D search within a 4D measurement space to achieve an optimal balance between efficiency and accuracy. Simulation results validate the effectiveness of our proposed algorithm compared to several existing approaches, demonstrating its robustness in accurately estimating 2D-DOD and 2D-DOA across various scenarios. The proposed technique shows significant computational savings and high-resolution estimations and maintains high precision, setting a new benchmark for future explorations in the field.
The complex layout of the airport surface, coupled with interrelated vehicle behaviors and densely mixed traffic flows, frequently leads to operational conflict risks. To address this issue, research was conducted on the recognition of characteristics and risk assessment for airport surface operations in mixed traffic flows. Firstly, a surface topological network model was established based on the analysis of the physical structure features of the airport surface. Based on the Monte Carlo simulation method, the simulation framework for airport surface traffic operations was proposed, enabling the simulation of mixed traffic flows involving aircraft and vehicles. Secondly, from various perspectives, including topological structural characteristics, network vulnerabilities, and traffic complexity, a comprehensive system for feature indices and their measurement methods was developed to identify risk hotspots in mixed traffic flows on the airport surface, which facilitated the extraction of comprehensive risk elements for any node’s operation. Finally, a weighting rule for risk hotspot feature indices based on the CRITIC–entropy method was designed, and a risk assessment method for surface operations based on TOPSIS–gray relational analysis was proposed. This method accurately measured risk indices for airport surface operations hotspots. Simulations conducted at Shenzhen Bao’an International Airport demonstrate that the proposed methods achieve high simulation accuracy. The identified surface risk hotspots closely matched actual conflict areas, resulting in a 20% improvement in the accuracy of direct risk hotspot identification compared to simulation experiments. Additionally, 10.9% of nodes in the airport surface network were identified as risk hotspots, including 3 nodes with potential conflicts between aircraft and ground vehicles and 21 nodes with potential conflicts between aircraft. The proposed methods can effectively provide guidance for identifying potential “aircraft–vehicle” conflicts in complex airport surface layouts and scientifically support informed decisions in airport surface operation safety management.
Li Songyuan, Li Yachao, Zhang Hao, Zhang Weike, Wang Jiadong, Guo Liang
Interrupted-sampling repeater jamming (ISRJ) generates a number of controllable false targets in the range dimension of radar signal by using the principle of signal undersampling and the characteristics of matched filtering. Based on the characteristics of ISRJ sampling function, this paper presents a design method of phase coded waveform and mismatched filter for ISRJ. According to the parameters of pulse width and repetition frequency of interference, a phase coded signal of mismatched filtering suitable for suppressing ISRJ is designed before the radar transmits the signal. According to the ISRJ sampling function and the coded signal designed before transmission, a mismatched filter to suppress ISRJ is constructed to reduce the interference energy after receiving the echo with interference. The simulation results show that compared with traditional unprocessed phase coded signals, the optimized signals of the proposed method exhibit better anti-jamming capability.
This study examines the effects of microgravity and space radiation on
astronauts’ muscle and bone health during space missions. Microgravity leads to
muscle atrophy and alterations in muscle tissue composition, whereas space radiation
impacts bone cells by increasing osteoclast activity and decreasing osteoblast
activity. The findings underscore the critical need for preventive measures, postmission
rehabilitation, and the use of specialized equipment and technology—such
as microgravity-adapted treadmills and nutritional supplements—to sustain astronaut
health. This study lays the groundwork for developing effective protection and
intervention strategies for long-duration space exploration, highlighting the necessity
of a thorough understanding of how the space environment affects the human body to
ensure optimal health and performance in space.
Ihor Turkin, Andrii Zelenkov, Viacheslav Leznovskyi
et al.
This paper proposes hardware and software solutions and a data processing method for vibration diagnostics of industrial equipment, which uses discrete Fourier transform and Allan dispersion to increase the accuracy and stability of measurement processes and result processing. The object of this study is the use of vibration diagnostic methods to implement the concept of maintenance of industrial equipment based on monitoring its current and future condition. The subject of this research is the hardware and software solutions for vibration diagnostics systems and methods for processing measurement results. The purpose of this work is to develop a new resource-saving IoT-oriented wireless solution for vibration diagnostics, where the contact method and MEMS accelerometers are used to measure vibration parameters and to evaluate the effectiveness of new methods and algorithms for processing experimental data. The task: justify the need to find new hardware and software solutions and methods of processing the obtained results for the implementation of the service concept based on the tracking of vibration indicators of technical equipment; provide basic hardware and software solutions for the implementation of the cloud platform of vibration diagnostics; develop methods of processing results; check the developed methods and algorithms using mathematical modeling methods and in an on-site experiment; compare the effectiveness of own and competitive solutions; draw conclusions and formulate a plan for further research. Conclusions. It has been proven that the combination of known analysis methods in the time and frequency domains with multi-level processing gives better results than analogous methods. The developed hardware and software tools and the method of processing measurement results effectively implement the contact method of vibration measurement, which provides the possibility of tracking the state of technical equipment. The developed equipment for the calibration of vibration acceleration sensors can reduce accelerometer errors. Further areas of research are the search for the optimal distribution of calculations on IoT levels, reducing the computational complexity of algorithms, increasing the time of continuous autonomous operation of the lower-level microcontroller, creating micro services for time-series analysis, and researching the dependence of the technical state of the equipment on the calculated Allan deviation.
This paper presents a fast trajectory optimization method combining the hp-Legendre pseudospectral method and convex optimization for the 6-Degree-of-Freedom rocket-powered landing problem. To accelerate calculations, this paper combines the Legendre pseudospectral method with a linearization method for convexification, and an hp method that can divide the mesh is introduced to reduce the computational workload. In terms of accuracy, a trust region update strategy that can control the solution process is presented to approximate the original problem iteratively. Convergence analysis is provided as evidence, substantiating that any solution produced by the hp-Legendre pseudospectral convex method is not only feasible but potentially optimal for the original problem. The effectiveness of the proposed method is demonstrated by numerical experiments. When compared, the proposed method achieves higher calculation accuracy in solving the 6-Degree-of-Freedom rocket-powered landing trajectory problem, while taking into account rocket attitude control.
Normalized point clouds (NPCs) derived from unmanned aerial vehicle-light detection and ranging (UAV-LiDAR) data have been applied to extract relevant forest inventory information. However, detecting treetops from topographically normalized LiDAR points is challenging if the trees are located in steep terrain areas. In this study, a novel point cloud normalization method based on the imitated terrain (NPCIT) method was proposed to reduce the effect of vegetation point cloud normalization on crown deformation in regions with high slope gradients, and the ability of the treetop detection displacement model to quantify treetop displacements and tree height changes was improved, although the model did not consider the crown shape or angle. A forest farm in the mountainous region of south-central China was used as the study area, and the sample data showed that the detected treetop displacement increased rapidly in steep areas. With this work, we made an important contribution to theoretical analyses using the treetop detection displacement model with UAV-LiDAR NPCs at three levels: the method, model, and example levels. Our findings contribute to the development of more accurate treetop position identification and tree height parameter extraction methods involving LiDAR data.
Florin COSTACHE, Sandra-Elena NICHIFOR, Mihaela-Luminita COSTEA
et al.
This paper presents the automatic approach procedure of a flying vehicle, attached to an ABB 7600 robot, and a mobile platform, attached to a Stewart platform. Due to a nonlinear dynamic behavior, it is necessary to implement complex control, stabilization and guidance schemes. The proposed solution for this system includes the development of an algorithm based on a backstepping control method, the controller design methodology being based on Lyapunov's stability theory. The proposed command law requires that the states are known, but it is also necessary to introduce a series of state estimators. Tracking a mobile platform is critical in surveillance, reconnaissance and tracking missions, with the control methodology defining a clear distinction between translational and rotational dynamics. The proposed algorithm is developed by separating two types of states involving an inverse kinematics, known as algebraic kinematics, in which the dynamic movements of the two pieces of equipment are used. The dynamics of the ABB 7600 robot involves a movement with seven degrees of freedom, while the Stewart platform can be used with a movement of six degrees of freedom. The proposed algorithm is implemented in both Matlab software and experimental testing. This paper provides results in terms of generating dynamics for both devices that can be used for simulating different scenarios of aerospace missions.
The icing of aircraft on the ground is an important flight safety issue. Aircraft must be de-iced and anti-iced to remove and protect the aircraft from freezing and frozen contamination, respectively, before and during takeoff. Winter de-icing and anti-icing operations are nonetheless costly, require a significant amount of time, and rely on extensive infrastructures. The essential equipment is often not available at smaller airports and remote locations, thereby preventing departures under a range of winter conditions. For sites located in northern Canada, this limitation results in frequent takeoff delays or cancellations during a significant portion of the year. As part of Canada’s Department of National Defence Innovation for Defence Excellence and Security research program, this study aimed to develop a practical solution to mitigate these limitations. This solution involves mounting a ground de-icing/anti-icing system onto a drone for a system that can be readily acquired and stored at smaller airports and remote locations or even be transported within the aircraft itself to ensure the possibility of performing de-icing/anti-icing operations at sites lacking the standard infrastructure. This paper presents the conception and design of a drone-based system that should allow winter operations at small and remote airports where it is not yet available. To do so, a spraying system satisfying the industry requirements is designed and integrated to a selected drone. The calculations were theoretically confirmed as a concept, and a prototype was built to perform laboratory and flight test in the next part of the study.
Commercial operations of uncrewed aerial vehicles (UAVs or drones) are expanding, with medical logistics using UAVs as part of health service supply chains being targeted. The ability to transport cargos that include items classified as Dangerous Goods (DG) is a significant factor in enabling UAV logistics to assist medical supply chains, but DG regulations for air transport have developed from the perspective of crewed aircraft and not UAVs. This paper provides an important audit of the current DG regulations, best practice in their application and the development of much-needed new governance that will be required to fully exploit UAVs for the safe transport of DG in medical logistics. Findings from the audit provide a summary of the circumstances and potential challenges resulting from the application of DG regulations as they stand to UAV operations, particularly for medical logistics, and convenient guidance on the practical implications of DG regulations for UAV operators. The main conclusion is that this is an under-researched domain, not yet given full consideration in a holistic way by regulators, governments, industry bodies, practitioners or academia.
Ali H. Wheeb, Rosdiadee Nordin, Asma’ Abu Samah
et al.
Telecommunications among unmanned aerial vehicles (UAVs) have emerged recently due to rapid improvements in wireless technology, low-cost equipment, advancement in networking communication techniques, and demand from various industries that seek to leverage aerial data to improve their business and operations. As such, UAVs have started to become extremely prevalent for a variety of civilian, commercial, and military uses over the past few years. UAVs form a flying ad hoc network (FANET) as they communicate and collaborate wirelessly. FANETs may be utilized to quickly complete complex operations. FANETs are frequently deployed in three dimensions, with a mobility model determined by the work they are to do, and hence differ between vehicular ad hoc networks (VANETs) and mobile ad hoc networks (MANETs) in terms of features and attributes. Furthermore, different flight constraints and the high dynamic topology of FANETs make the design of routing protocols difficult. This paper presents a comprehensive review covering the UAV network, the several communication links, the routing protocols, the mobility models, the important research issues, and simulation software dedicated to FANETs. A topology-based routing protocol specialized to FANETs is discussed in-depth, with detailed categorization, descriptions, and qualitatively compared analyses. In addition, the paper demonstrates open research topics and future challenge issues that need to be resolved by the researchers, before UAVs communications are expected to become a reality and practical in the industry.
In this study, the problem of the low probability of intercept (LPI) performance optimisation for a joint radar‐communications system (JRCS) is investigated, which can simultaneously estimate surveillance channel parameters from the target returns and decode the received communications signals. The primary purpose of the proposed LPI performance optimisation strategy is to improve the LPI performance of a JRCS by optimising the energy spectral density of radar waveform design and the communications power allocation while maintaining a predetermined mutual information threshold for parameter estimation and a certain communications data rate for information delivery. The traditional isolated sub‐band (TISB) situation, radar isolated sub‐band (RISB) situation, and communications isolated sub‐band (CISB) situation are analysed. Subsequently, the technique of Lagrange multipliers and the Karush–Kuhn–Tuckers optimality conditions are employed to solve the resulting optimisation problems. Moreover, the successive interference cancellation method is adopted to process the received radar‐communications compound signal. Finally, several numerical simulations are conducted to demonstrate the theoretical calculations and to validate the effectiveness of the proposed LPI performance optimisation strategy. It is also shown that the achievable LPI performance in RISB and CISB situations is much better than that in TISB situation.
An optimization technique called shape-linked optimization, which is different from the traditional optimization method, is introduced in this paper. The research introduces an updated wing optimization design in an effort to adapt to continuous structure changes and shapes while optimizing for a lighter weight of the structure. The changing tendencies of the thickness of wing skins and the cross-section areas of the wing beams are fitted to continuous polynomial functions, whose coefficients are designed as variables, which is a different engineering approach from the size variants of the thickness and the area in the traditional optimization. The structural strength, stiffness, and stability are constraints. Firstly, this research unearths the significance of utilizing a modernized optimization process which alters the production of the traditional 12 or over 12 segment wing design and applies new approaches and methods with less variables that contribute to expedited design cycles, decreased engineering and manufacturing expenditures, and a lighter weight aircraft with lower operating costs than the traditional design for the operators. And then, this paper exemplifies and illustrates the validity of the above claims in a detailed and systematic approach by comparing traditional and modernized optimization applications with a two-beam wing. Finally, this paper also proves that the new optimized structure parameters are easier than the size optimization to process and manufacture.