bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of a Modal Parameter Identification Method Based on Variational Mode Decomposition in Flight Flutter Testing
Authors: Wang Shaonan 
Published: June 2024

Abstract
Signals of flight flutter testing exhibit non-stationary characteristics, closely spaced modes, and low signal-to-noise ratio, presenting challenges in data processing. In recent years, the variational mode decomposition (VMD) method has emerged as a promising approach to mitigate mode mixing and exhibit robust noise resistance. Therefore, a novel time-frequency domain modal parameter identification method based on VMD is proposed to process impulse response signals in flight flutter testing. The modal frequency and damping ratio are determined through a three-step process: VMD analysis, Hilbert transform, and least square fitting. The efficacy of the proposed method in identifying closely spaced modes and resisting noise is validated through a numerical example. Furthermore, this method is applied to analyze two types of pulse excitation signals in actual flight flutter testing: one induced by the pilot’s shaking stick and the other induced by small rocket excitation. The obtained modal parameters are compared with those from ground vibration tests and specialized software, respectively, to showcase the effectiveness and superiority of the proposed method.
Vibration signals reconstruction with diffusion model for bearing fault diagnosis
Authors: Gu Zeyu , Ma Jianwei 
Published: June 2024

Abstract
Rotating bearing plays an important role in many mechanical equipment operation, such as satellite in orbit. There are in urgent need of constructing effective prognosis and diagnosis system oriented rotating bearing. Traditional bearing fault diagnosis methods enhance fault feature with sparsity-assisted prior, which are not suitable for complex vibration signals. Meanwhile, it is difficult to extract fault feature from under-sampled vibration signals. In this paper, we firstly utilize generation diffusion model to learn probability distribution of bearing fault data. As a deep generation prior, we combine the diffusion model and reconstruction problem with regularization term. The unsupervised learning method is not restricted to specific measurement matrix. The experiment in Machinery Failure Prevention Technology (MFPT) Dataset verifies the effectiveness of our algorithm. Compared with the sparse model (L1-norm) and hierarchical hyper-Laplacian prior induced model (HHLP), our method achieves better reconstruction signal to noise ratio (SNR) performance and maintains the fault frequency information from different under-sampled data.
Study On Microvibration Test Technology For Satellite Multistage Unloading
Authors: Yao Wu , Chuang Liu , Gang Sun , Hao Sun , Qi Xin , Yicun Xie , Chunliu Zhang 
Published: June 2024

Abstract
In this paper, the structural forms of high-precision satellites are analyzed, and the new changes of boundary condition simulation when carrying out ground microvibration tests are discussed. Combined with the new requirements, the multi-stage unloading micro-vibration test method is studied, and the multi-stage unloading micro-vibration test system is designed, which lays a foundation for the follow-up micro-vibration test of a new generation of satellites.
A Decentralized Consistent Approach for Multi-Robot Simultaneous Localization and Object Tracking
Authors: Wang Xuedong , Huang Yingtao , Lu Xinyuan 
Published: June 2024

Abstract
This study focuses on the problem of multi-robot simultaneous localization and object tracking (MR-SLOT), which involves the collaborative effort of multiple mobile robots tracking a moving object on a plain. To address this challenge, this paper introduces a fully decentralized approach based on the extended Kalman filter and covariance intersection (CI), denoted as CI-SLOT. In the proposed approach, each robot can precisely track the robot-to-object correlations. Moreover information exchange occurs solely among one-hop communicating robots, and each robot only maintains the latest estimate of the object and its pose. The simulation results have shown that the performances of CI-SLOT are better than those of the state-of-the-art approaches of comparable processing and communication costs.
Orbit Determination of High Orbit Spacecraft based on BDS-3 using Extended Kalman Filter
Authors: Ma Xiangtai , Hu Yanfeng , Yu Miao , Dong Xurong , Lai Jiangfeng 
Published: June 2024

Abstract
The positioning of highly elliptical orbit (HEO) spacecraft is very important in deep space exploration and other missions. The Beidou Navigation Satellite System (BDS-3), which was completed in 2020, has put forward new ideas for using GNSS technology to make up for the lack of earth-based TT&C systems. At the same time, the selection of the gravity field order and the perturbation forces must be considered when using dynamical methods for HEO spacecraft positioning. In this paper, simulation experiments are carried out based on the Two-Line Orbital Element (TLE) data of BDS. Two HEO satellites with different semimajor-axis (67509.6 km, 212857.3 km) are selected as the target spacecraft orbits. The single point positioning (SPP) method and Extended Kalman Filter (EKF) method are used for HEO spacecrafts positioning respectively. The experiments show that a 20×20 order gravity field model can be chosen for the orbital integral of HEO spacecraft orbits, and the integration error caused by solar gravity and lunar gravity should be taken into account with the change of orbital altitude. Adding Geostationary Orbit (GEO) and Inclined GeoSynchronous Orbit (IGSO) navigation satellites improved the visibility of these two orbits by 19.45% and 16.64%, respectively, and improved the GDOP value by 14.1% and 3.8%, respectively, compared to observing MEO satellites only. The use of the EKF method can effectively improve the positioning accuracy of the HEO spacecraft compared to the SPP method. For the spacecraft in HEO-1, the RMS value of the positioning errors of the EKF method was 67.82 m, and the accuracy of each direction was improved by 44.28%, 38.85%, and 38.62%, respectively. For the spacecraft in HEO-2, the positioning errors in the x direction of EKF method was within 12 km and within 2 km in the y and z directions. The accuracy of these three directions was improved by 84.91%, 79.24%, and 58.64%, respectively.
Incipient Bearing Fault Extraction based on an Adaptive Multi-stage Noise Reduction Method
Authors: Tian Shaoning , Feng Guojin , Meng Zhaozong , Liu Xiaoang , Zhen Dong , Gu Fengshou 
Published: June 2024

Abstract
Considering the strong nonlinear and non-stationary characteristics of rolling bearing vibration signals, this paper proposes a multi-stage noise reduction method using adaptive variational mode decomposition and modulation signal bispectrum (AVMD-MSB) to extract the fault features of rolling bearings. Firstly, the AVMD is employed to adaptively select VMD parameters K and α and decompose the signal into a series of Intrinsic mode functions (IMFs), which allows an adaptive selection of the parameters of VMD. Then, all IMF components are reconstructed with weights according to the index of correlation kurtosis to avoid accidental omission of the IMFs containing important fault information. Finally, MSB is implemented to further suppress residual noises and interference components in the signal, precisely extract the bearing fault features. Numerical simulation and case study show that the AVMD-MSB is more advantageous in extracting fault characteristics from rolling bearing vibration signals compared with AVMD-Envelope and conventional VMD-MSB.
The influence of corrosion time on the observation of metallographic structure of 20CrMnMo
Authors: Liu Qing , Yang Suliang , Liu Huan , Chen Ke , He Xindang 
Published: June 2024

Abstract
20CrMnMo is one of the most widely used alloy steels, and its mechanical properties are closely related to the metallographic structure of the material. Clearly obtaining the distribution pattern of metallographic structure is of great significance for studying the mechanical properties of 20CrMnMo. In this paper, 20CrMnMo samples were subjected to corrosion treatment at different times, and the microstructure of the samples was observed by optical microscope (OM) and Scanning electron microscope (SEM). Through optical microscope observation, the metallographic structure images under different magnification and corrosion time were compared and analyzed, and the best corrosion time interval for metallographic structure observation was obtained; On this basis, by using Scanning electron microscope and EDS, the microscopic images at higher magnification were obtained, and the mechanism of corrosion time on the metallographic structure was further analyzed and explained.
Research on Thermocouple Integration Method of Hollow Thin-Walled Turbine Rotor Blade Surface
Authors: Fang Jianfeng 
Published: June 2024

Abstract
The hollow thin-walled structure is increasingly used in advanced aero-engine turbine rotor blades, and the traditional surface temperature measurement method based on groove buried couple is no longer applicable. In this paper, a new thermocouple integration method is proposed. The laser additive manufacturing process is used to generate thermocouple embedding channels on the surface of turbine blades. After the thermocouple is embedded, it is pre-fixed, and the thermocouple protection is realized by supersonic flame spraying technology. The strength of the thermocouple integrated structure of the turbine blade is verified by finite element analysis. Based on CFD analysis, the influence of thermocouple integration on the efficiency, pressure ratio and temperature distribution of the turbine blade is studied. The high-speed rotation test shows that the thermocouple integrated structure has high strength and reliability and meets the measurement requirements. This method can provide technical support for the surface temperature measurement of hollow thin-walled turbine rotor blades.
Modeling and Analysis of Inertial-Hydraulic Power take-off Device
Authors: Jia Han , Pei Zhongcai , Tang Zhiyong 
Published: June 2024

Abstract
This paper introduces a novel power output device that combines inertia and hydraulics, which captures vibrations caused by external forces acting on the carrier in space using the sensitive gyroscope of the inertia system. The captured random mechanical energy is then converted into hydraulic energy, rectified and regulated by the hydraulic system, and transformed into stable output energy. The influence of gyroscope angular momentum on the energy capturing capability is investigated through the development of a dynamic model. Additionally, a hydraulic power output system is designed, and the effect of hydraulic accumulator parameters on energy absorption fluctuations is analyzed. This research offers valuable insights for the design and optimization of the device.
Horizontal Tail Flight Load Prediction Method for Large UAVs based on Machine Learning
Authors: Hu Xiaomin , Pan Xiangyu , Wang Jiulong 
Published: June 2024

Abstract
In today’s rapidly developing large UAVs field, flight safety and reliability are essential considerations. Flight load is one of the important factors affecting the load capacity of large UAVs, so the research on load prediction technology can improve flight safety and the reliability of air transportation. This paper first introduces the collection and processing method of flight load data, then uses the machine learning method-BP neural network to predict flight load, establishes the BP neural network model to predict flight load with flight parameters, and optimizes the model according to error analysis. Finally, the accuracy and practicability of the model are verified by analysing the fitting of the training set and the test set, and the error distribution of the true value of shear, bending moment, torque and the absolute percentage of the predicted value, and the model is evaluated.
Study on the mechanical properties and optimization methods of high-strength high-modulus carbon fibre composite with the cap structure
Authors: Dong Zhicheng , Wang Jianing , Wan Xiaopeng 
Published: June 2024

Abstract
The application of high-strength, high-modulus carbon fiber with excellent properties such as high modulus, conductivity, and thermal conductivity has been increasingly widespread in aerospace flight, deep space exploration, and near-space vehicles. In recent years, with the continuous enhancement of functional requirements for products in these domains, there is a growing need to optimize the typical structure of such carbon fibers to enhance their load-bearing capacity. Therefore, in this study, we first conducted basic mechanical performance tests on specimens of T1100/5405 composite materials to obtain fundamental mechanical performance parameters of the material. Subsequently, compression and bending performance tests were performed on a typical hat-shaped structure to understand its actual load-bearing capacity and failure modes. The results indicate that the compressive failure load and bending failure load of the hat-shaped structure are 474.44 kN and 27.365 kN, respectively. Additionally, by combining the fundamental mechanical performance parameters of the composite material, the mechanical performance of the hat-shaped structure was simulated and verified using finite element analysis software, with the model validated using experimental data. Finally, layering parameters of the established finite element model were optimized, resulting in an increase of the structure’s load-bearing capacity under compression and bending loads to 662.629 kN and 31.9059 kN, respectively. In conclusion, the optimization approach presented in this paper for the T1100/5405 composite material’s hat-shaped structure is efficient. It yields noticeable improvements, significantly enhancing the load-bearing capacity of the typical structure in various application scenarios.
Study on Thermodynamic Coupling Performance of Multi-Level Lattice Structures
Authors: Yan Jiaqi , Han Tianyi , Huang Heyuan 
Published: June 2024

Abstract
With the development of hypersonic vehicle, the design of heat-resistant and load-bearing surface of hypersonic vehicle has gradually become a key technology affecting its combat effectiveness. As a new type of lightweight and high-strength structure, lattice structure has excellent mechanical properties such as ultra-light, high specific strength and high specific stiffness, and special properties such as vibration reduction, heat dissipation and sound absorption. Among them, the multi-level lattice structure can increase the bearing efficiency of the structure at low relative density, and increase the heat transfer area at the same time, so as to improve the heat protection and bearing capacity of the structure. This study includes three aspects of high temperature out-of-plane compression test, high temperature numerical simulation comparison, and structural optimization for the designed multi-level pyramid lattice, in order to obtain the bearing capacity of the multi-level pyramid lattice at 350°C, and further improve the bearing performance by optimizing the core structure. Through experiments and verification, the multi-level pyramid lattice designed and optimized in this study can further meet the requirements of thermal protection and load-bearing performance of aircraft compared with the single-level pyramid lattice, and can provide a reference for the study of high temperature mechanical properties of lattice structures, the design of new multi-level lattice structures and the engineering application of lattice structures.
The microstructures and mechanical properties of the TC4 titanium alloy fabricated by laser composite manufacturing technology
Authors: Kun He , Suming Chen , Yazhou Zhang 
Published: June 2024

Abstract
The effective combination of traditional forging and laser three-dimensional forming technology can play a crucial role in the preparation of large metal part with fine structures, thereby accelerating the manufacturing cycle of parts and reducing costs. This study used laser composite manufacturing technology to perform complete annealing heat treatment on TC4 titanium alloy structural part produced from traditional forgings. The analysis of microscopic structure, chemical composition, and mechanical properties has verified that the overall mechanical properties consistency of the composite manufacturing part has been effectively improved. The results indicate that laser composite manufacturing part have good metallurgical bonding, and there is no component segregation phenomenon in the composite manufacturing area. After complete annealing, the α lath in the composite manufacturing part is coarsened, the strength of the laser forming area is reduced, and the consistency of mechanical properties of the forging area and the laser forming area is enhanced. The consistency of strength of the two areas is increased from 78% before heat treatment to 84%.
Surface Defect Detection: A feature-based transfer learning approach
Authors: Abdul Majeed Anwar P.P. , Abdullah Muhammad Amirul , Ab. Nasir Ahmad Fakhri , Mohd Razman Mohd Azraai , Chen Wei , Yap Eng Hwa 
Published: June 2024

Abstract
Surface defect detection is critical for maintaining product quality in manufacturing. In this work, we apply a feature-based transfer learning approach for surface defect classification on the NEU surface defect database. The database contains defects across 6 categories captured under various conditions. We utilised two pretrained convolutional neural network (CNN) architectures - VGG16 and InceptionV3 - by removing the final classification layer and using the CNN as a fixed feature extractor. The output feature vectors were classified using a logistic regression (LR) model. The data was split into train, validation, and test sets with a 70:15:15 ratio. The VGG16-LR model achieved classification accuracy (CA) of 100%, 98%, and 99% for the train, validation, and test sets respectively. The InceptionV3-LR model attained CA of 100%, 91%, and 92% for train, validation, and test. The results demonstrate the effectiveness of transfer learning with CNN feature extraction for surface defect detection on challenging multi-category industrial datasets. Further work includes tuning hyperparameters and evaluating additional architectures.
Prediction of aircraft cabin noise by statistical energy analysis
Authors: Song Xiao , Xu Jiaxin , Lin Ziqi 
Published: June 2024

Abstract
The noise level in the aircraft cabin is an important indicator on market competitiveness, and it is a considerable challenge to reduce the noise in the cabin at a relatively small cost, so efficient and accurate forecasting tools are required. In the aviation industry, Statistical Energy Analysis (SEA) is widely used to predict mid- and high-frequency noise in aircraft cabins. It has the advantages of simple method and low requirement of structure details. This paper models the cabin of a certain type of aircraft, and uses statistical energy methods to predict the noise level in the cabin during ground and cruise conditions. Among them, the prediction result of the cabin noise on the ground is in good agreement with the test results above 250Hz, which verifies the correctness of the model. During cruise, the pressure fluctuation on the outer surface of the front fuselage is dominated by turbulent boundary layer noise. The analysis shows that the Robertson model can predict turbulent boundary layer noise well, and the difference between the predicted single-point spectrum and the experimental value is less than 1dB. The cabin noise predicted by only loading the turbulent boundary layer noise source is consistent with the experimental results, but the sound pressure level in some frequency bands is low.
Optimising liquid impingement jet arrays for concentrated heat sources
Authors: Elliott J W , Byrne G , Robinson A J 
Published: June 2024

Abstract
This work seeks to investigate jet array impingement liquid cooling of CPU processors that utilise Integrated Heat Spreaders. In this study, single and centralised heat sources of various sizes (10 mm to 20 mm) were investigated, and a series of single and multi-objective optimisation studies were carried out to determine the optimum arrangement of microjets for different heat source sizes based on variable geometric inputs of the jet orifice plate. The results indicated that the design of the optimum jet orifice strongly depends on the size of the heat source as well as whether the target optimisation strategy is to achieve minimum thermal resistance, or both minimum thermal resistance and minimum pumping power simultaneously. A clustering of quite different orifice designs in optimal zones is observed, where approximately the same hydraulic and/or thermal performance is observed.
Highly-turbulent packed bed heat exchange: modelling, experiment and validation
Authors: Simpson H , Lagarde J 
Published: June 2024

Abstract
SynchroStor Ltd. is developing a system for Pumped Thermal Energy Storage (PTES) based on the closed Brayton cycle principle. A numerical model of the gas-solid heat exchanger used by the cycle was developed in MATLAB to both evaluate the performance of the proposed arrangement and act as a design tool. A series of physical tests were run on a reduced-scale experimental test rig to assist with validation of the model. Thermal resistance due to radial conduction through the solid particles was found to be a critical feature of the model for SynchroStor’s design conditions; model outputs matched temperatures measured at each thermocouple station of the test rig with accuracies better than ±4.0%. The model was experimentally-validated for flows with superficial Reynolds numbers (Re) in the range 4,300 to 11,100.
Study of the thermal dynamic behavior of a rectangular enclosure with fins embedded in PCM
Authors: El Hanafi Abderrahmane , Blet Nicolas , Kheiri Abdelhamid , Remy Benjamin 
Published: June 2024

Abstract
This paper investigates the behavior of a Thermal Energy Storage (TES) system with Phase Change Material (PCM) embedded in fins. A commercial Computational Fluid Dynamics software is used to study the behavior of the system. A validation of the numerical model is done by comparing the numerical results with the measured melting fraction as function of time, determined from measurement of the temperature fields, for two lengths of fins. A dimensionless number is suggested to analyze the effect of the fins on the heat transfer in the medium. This study presents some results on the evolution of the liquid fraction and the Nusselt number. Results show that although the small conductivity of the PCM, the convection and conduction play a key role in heat transfer, their importance depends on the length of the fins. Furthermore, some feature of the behavior of the system without fins have been conserved by analyzing the Nusselt number.