Search Results (175)

The aim of this paper is the investigation of changes in modal parameters of composite pressure vessel structures with different prestress states realized by varying fiber tension. Two series of vessels was manufactured and examined with different wound tensions, the first—3 N and second—80 N, respectively. Other technological factors, such as the type and weight of carbon fiber used, as well as liner type, were kept constant. The vessels were examined with internal pressure equal to atmospheric and without pressure fittings. The modal tests were performed on storage tanks suspended on an elastic cord in the horizontal orientation to prevent the structure from being disturbed by vibrations. The examinations were focused only on the cylindrical part of the vessels. Based on modal analysis, parameters such as natural frequencies, dampings and modal shapes were determined. Research results indicate clear changes in natural frequencies and damping coefficients between the two investigated prestress states. It is interesting that natural frequencies for bending modes are higher in the case of structures with high fiber tension, while in the case of other vibration forms, the natural frequencies have smaller values in comparison with the first series. Full article

Coronary artery disease (CAD) is the third leading cause of disability and death globally. Intravascular ultrasound (IVUS) is the most commonly used imaging modality for the characterization of vulnerable plaques. The development of novel intravascular imaging and therapy devices requires dedicated open systems (e.g., for pulse sequences for imaging or thrombolysis), which are not currently available. This paper presents the development of a novel multifunctional FPGA-based pulser/receiver system for intravascular ultrasound imaging and therapy research. The open platform consists of a host PC with a Matlab-based software interface, an FPGA board, and a proprietary analog front-end board with state-of-the-art electronics for highly flexible transmission and reception schemes. The main features of the system include the capability to convert arbitrary waveforms into tristate bipolar pulses by using the PWM technique and by the direct acquisition of raw radiofrequency (RF) echo data. The results of a multicycle excitation pulse applied to a custom 550 kHz therapy transducer for acoustic characterization and a pulse-echo experiment conducted with a high-voltage, short-pulse excitation for a 19.48 MHz transducer are reported. Testing results show that the proposed system can be easily controlled to match the frequency and bandwidth required for different IVUS transducers across a broad class of applications. Full article

Due to its superior maneuverability and concealment, the micro flapping-wing aircraft has great application prospects in both military and civilian fields. However, the development and optimization of lightweight materials have always been the key factors limiting performance enhancement. This paper designs the flapping mechanism of a single-degree-of-freedom miniature flapping wing aircraft. In this study, T800 carbon fiber composite material was used as the frame material. Three typical wing membrane materials, namely polyethylene terephthalate (PET), polyimide (PI), and non-woven kite fabric, were selected for comparative analysis. Three flapping wing configurations with different stiffness were proposed. These wings adopted carbon fiber composite material frames. The wing membrane material is bonded to the frame through a coating. Inspired by bionics, a flapping wing that mimics the membrane vein structure of insect wings is designed. By changing the type of membrane material and the distribution of carbon fiber composite materials on the wing, the stiffness of the flapping wing can be controlled, thereby affecting the mechanical properties of the flapping wing aircraft. The modal analysis of the flapping-wing structure was conducted using the finite element analysis method, and the experimental prototype was fabricated by using 3D printing technology. To evaluate the influence of different wing membrane materials on lift performance, a high-precision force measurement experimental platform was built, systematic tests were carried out, and the lift characteristics under different flapping frequencies were analyzed. Through computational modeling and experiments, it has been proven that under the same flapping wing frequency, the T800 carbon fiber composite material frame can significantly improve the stiffness and durability of the flapping wing. In addition, the selection of wing membrane materials has a significant impact on lift performance. Among the test materials, the PET wing film demonstrated excellent stability and lift performance under high-frequency conditions. This research provides crucial experimental evidence for the optimal selection of wing membrane materials for micro flapping-wing aircraft, verifies the application potential of T800 carbon fiber composite materials in micro flapping-wing aircraft, and opens up new avenues for the application of advanced composite materials in high-performance micro flapping-wing aircraft. Full article

Internal leakage within the valve body constitutes a severe potential safety hazard in industrial fluid control systems, attributable to its high concealment and the resultant difficulty in detection via conventional methodologies. Acoustic emission (AE) technology, functioning as an efficient non-destructive testing approach, is capable of capturing the transient stress waves induced by leakage, thereby furnishing an effective means for the real-time monitoring and quantitative assessment of internal leakage within the valve body. This paper conducts a systematic review of the theoretical foundations, signal-processing methodologies, and the latest research advancements related to the technology for detecting internal leakage in the valve body based on acoustic emission. Firstly, grounded in Lechlier’s acoustic analogy theory, the generation mechanism of acoustic emission signals arising from valve body leakage is elucidated. Secondly, a detailed analysis is conducted on diverse signal processing techniques and their corresponding optimization strategies, encompassing parameter analysis, time–frequency analysis, nonlinear dynamics methods, and intelligent algorithms. Moreover, this paper recapitulates the current challenges encountered by this technology and delineates future research orientations, such as the fusion of multi-modal sensors, the deployment of lightweight deep learning models, and integration with the Internet of Things. This study provides a systematic reference for the engineering application and theoretical development of the acoustic emission-based technology for detecting internal leakage in valves. Full article

Numerous rural residential buildings exhibit inadequate seismic performance when subjected to blast-induced vibrations, which poses potential threats to their overall stability and structural integrity when in proximity to blasting project sites. The investigation conducted in conjunction with the Qianshi Mountain blasting operations along the Wenzhou segment of the Hangzhou–Wenzhou High-Speed Railway integrates household field surveys and empirical measurements to perform modal analysis of rural residential buildings through finite element simulation. Adhering to the principle of stratified arrangement and composite measurement point configuration, an effective and reasonable experimental observation framework was established. In this investigation, the seven-story rural residential building in adjacent villages was selected as the research object. Strong-motion seismographs were strategically positioned adjacent to frame columns on critical stories (ground, fourth, seventh, and top floors) within the observational system to acquire test data. Methodical signal processing techniques, including effective signal extraction, baseline correction, and schedule conversion, were employed to derive temporal dynamic characteristics for each story. Combined with the Fourier transform, the frequency–domain distribution patterns of different floors are subsequently obtained. Leveraging the structural dynamic theory, time–domain records were mathematically converted to establish the structure’s maximum response spectra under blast-induced loading conditions. Through the analysis of characteristic curves, including floor acceleration response spectra, dynamic amplification coefficients, and spectral ratios, the dynamic response patterns of rural residential buildings subjected to blast-induced vibrations have been elucidated. Following the normalization of peak acceleration and velocity parameters, the mechanisms underlying differential floor-specific dynamic responses were examined, and the layout principles of measurement points were subsequently formulated and summarized. These findings offer valuable insights for enhancing the seismic resilience and structural safety of rural residential buildings exposed to blast-induced vibrations, with implications for both theoretical advancements and practical engineering applications. Full article

This study addresses the challenge of accurately modeling the dynamic behavior of industrial robots for precision manufacturing applications. Using a comprehensive experimental approach with modal impulse hammer testing and triaxial acceleration measurements, 360 frequency response functions were recorded along orthogonal measurement paths for a KUKA KR10 robot. Two dynamic models with different parameter dimensions (12-parameter and 24-parameter) were developed in Matlab/Simscape, and their parameters were identified using genetic algorithm optimization. The KUKA KR10 features Harmonic Drives at each joint, whose high transmission ratio and zero backlash characteristics significantly influence rotational dynamics and allow for meaningful static structural measurements. Objective functions based on the Frequency Response Assurance Criterion (FRAC) and Root Mean Square Error (RMSE) metrics were employed, utilizing a frequency-dependent weighting function. The performance of the models was evaluated across different robot configurations and frequency ranges. The 24-parameter model demonstrated significantly superior performance, achieving 70% overall average Global FRAC in the limited frequency range (≤200 Hz) compared to 41% for the 12-parameter model when optimized using a representative subset of 9 measurement points. Both models showed substantially better performance in the limited frequency range than in the full spectrum. This research provides a validated methodology for dynamic characterization of industrial robots and demonstrates that higher-dimensional models, incorporating transverse joint compliance, can accurately represent robot dynamics up to approximately 200 Hz. Future work will investigate nonlinear effects such as torsional stiffness hysteresis, particularly relevant for Harmonic Drive systems. Full article

This study investigates the dynamic characteristics of three-dimensional (3D) printed acrylonitrile butadiene styrene (ABS) cantilever beams using Experimental Modal Analysis (EMA). The effects of Fused Deposition Modelling (FDM) process parameters—specifically infill pattern, infill density, nozzle size, and raster angle—on the natural frequency, mode shapes, and damping ratio were examined. Although numerous studies have addressed the static mechanical behaviour of FDM parts, there remains a significant gap in understanding how internal structural features and porosity influence their vibrational response. To address this, a total of seventy-two specimens were fabricated with varying parameter combinations, and their dynamic responses were evaluated through frequency response functions (FRFs) obtained via the impact hammer test. Damping characteristics were extracted using the peak-picking (half power) method. Additionally, the influence of internal porosity on damping behaviour was assessed by comparing the actual and theoretical masses of the specimens. The findings indicate that both natural frequencies and damping ratios are strongly influenced by the internal structure of the printed components. In particular, gyroid and cubic infill patterns increased structural stiffness and resulted in higher resonant frequencies, while low infill densities and triangle patterns contributed to enhanced damping capacity. Response Surface Methodology (RSM) was employed to develop mathematical models describing the parameter effects, providing predictive tools for applications sensitive to vibration. The high R² values obtained in the RSM models based on the input variables show that these variables explain the effects of these variables on both natural frequency and damping ratio with high accuracy. The models developed (with R² values up to 0.98) enable the prediction of modal behaviour, providing a valuable design tool for engineers optimizing vibration-sensitive components in fields such as aerospace, automotive, and electronics. Full article

Stereo-digital image correlation (DIC) is promising in structural vibration testing due to its advantages of non-contact, full-field, and high-spatial resolution. However, thousands of full-field displacement maps generated by stereo-DIC hamper its practical applications. Furthermore, with the evaluated mode shapes, how to accurately reveal the embedded/hidden damage positions without a reference dataset is another critical problem. For the purpose of resolving those issues, a complete method is proposed, consisting of (1) an adaptive kernel function construction method for low-rank-representing the full-field displacement maps while retaining both global and local shape features, (2) an enhanced frequency domain decomposition approach for noise-robust mode shape estimation based on the kernel functions, and (3) extracting and fusing local shape features of multiple mode shapes for more accurate damage localization. Finally, numerical and experimental case studies are investigated to verify the effectiveness and accuracy of the proposed low-rank representation method in modal parameters and damage identification. In addition, it is found that the mode shape and damage characteristics of displacement fields can be captured by the first 20 principal components, and the first six modes provide robust damage localization results. Full article

As a forward-looking development in air traffic control (ATC), remote towers rely on virtualized information presentation, which may exacerbate visual fatigue among controllers and compromise operational safety. This study proposes a visual fatigue recognition model based on multimodal physiological signals. A 60-min simulated remote tower task was conducted with 36 participants, during which eye-tracking (ET), electroencephalography (EEG), electrocardiography (ECG), and electrodermal activity (EDA) signals were collected. Subjective fatigue questionnaires and objective ophthalmic measurements were also recorded before and after the task. Statistically significant features were identified through paired t-tests, and fatigue labels were constructed by combining subjective and objective indicators. LightGBM was then employed to rank feature importance by integrating split frequency and information gain into a composite score. The top 12 features were selected and used to train a multilayer perceptron (MLP) for classification. The model achieved an average balanced accuracy of 0.92 and an F1 score of 0.90 under 12-fold cross-validation, demonstrating excellent predictive performance. The high-ranking features spanned four modalities, revealing typical physiological patterns of visual fatigue across ocular behavior, cortical activity, autonomic regulation, and arousal level. These findings validate the effectiveness of multimodal fusion in modeling visual fatigue and provide theoretical and technical support for human factor monitoring and risk mitigation in remote tower environments. Full article

The damage location detection of the fiber-reinforced composite thin plate (FCTP) is studied through the curvature modal shape scanning method (CMSSM), utilizing the advantages of the sensitivity of curvature modal shapes to local stiffness changes and the high measurement accuracy of a laser vibrometer. Firstly, our research begins with the construction of a laser scanning frame model for the FCTP. Subsequently, during the analysis of modal shape data extraction principles, the two-dimensional five-spot-tripling surface smoothing method is developed, so that the quantitative index for damage location detection of the FCTP, i.e., the damage localization index, can be derived. The operating deflection shapes of the FCTP at different natural frequencies are obtained, and the self-developed laser scanning vibration testing system is employed to scan and measure the vibration. Then, a TC500 fiber/epoxy composite plate is utilized as an experimental object to perform a damage identification experiment. It has been proven that this approach can detect the fiber breakage location of the FCTP with high accuracy. Finally, the influence of parameters such as boundary constraint, excitation level, and laser scanning rate on the damage detection results is also discussed. Through studies on influencing parameters, practical guidance is provided for the application of the damage identification approach of the FCTP. Full article

In aerospace applications, titanium matrix composites (TMCs) must balance high strength, thermal stability, and vibration resistance. This study investigates the microstructural evolution and multi-property correlations in single-phase ZrC-reinforced (TMC1) and dual-phase ZrC-NbC-co-reinforced (TMC2) TMCs via SEM/TEM, XRD, tensile testing, and ANSYS simulations. The in situ reaction (Ti + ZrC/NbC → TiC + Zr/Nb) and NbC-induced grain boundary pinning drive microstructural optimization in TMC2, achieving 30% higher reinforcement homogeneity and 5 μm grain refinement from 15 μm to 10 μm. TMC2’s tensile strength reaches 1210 MPa, a 15% increase over TMC1, with an elongation at a break of 4.74%, 2.2 times that of TMC1. This performance stems from synergistic Hall–Petch strengthening and nano-TiC dispersion strengthening. Modal simulations show TMC2 exhibits a first-mode natural frequency of 98.5 kHz, 1.1% higher than TMC1’s 97.4 kHz, with maximum displacement reduced by 2.3%. These improvements correlate with TMC2’s elevated elastic modulus (125 GPa vs. 110 GPa) and uniform mass/stiffness distribution. The ZrC-NbC synergy establishes a microstructural framework for the concurrent enhancement of static and dynamic properties, offering critical insights for a high-performance TMC design in extreme environments. Full article

Acoustic monitoring presents a promising, non-invasive modality for assessing animal welfare in precision livestock farming. In poultry, vocalizations encode biologically relevant cues linked to health status, behavioral states, and environmental stress. This study proposes an integrated analytical framework that combines signal-level statistical analysis with machine learning and deep learning classifiers to interpret chicken vocalizations in a welfare assessment context. The framework was evaluated using three complementary datasets encompassing health-related vocalizations, behavioral call types, and stress-induced acoustic responses. The pipeline employs a multistage process comprising high-fidelity signal acquisition, feature extraction (e.g., mel-frequency cepstral coefficients, spectral contrast, zero-crossing rate), and classification using models including Random Forest, HistGradientBoosting, CatBoost, TabNet, and LSTM. Feature importance analysis and statistical tests (e.g., t-tests, correlation metrics) confirmed that specific MFCC bands and spectral descriptors were significantly associated with welfare indicators. LSTM-based temporal modeling revealed distinct acoustic trajectories under visual and auditory stress, supporting the presence of habituation and stressor-specific vocal adaptations over time. Model performance, validated through stratified cross-validation and multiple statistical metrics (e.g., F1-score, Matthews correlation coefficient), demonstrated high classification accuracy and generalizability. Importantly, the approach emphasizes model interpretability, facilitating alignment with known physiological and behavioral processes in poultry. The findings underscore the potential of acoustic sensing and interpretable AI as scalable, biologically grounded tools for real-time poultry welfare monitoring, contributing to the advancement of sustainable and ethical livestock production systems. Full article

The development of reliable sensor networks for vibration monitoring is essential for the preventive conservation of buildings and structures. The identification of natural frequencies is crucial both for sensor network planning, to ensure optimal placement, and for operation, to detect frequency shifts that may indicate structural damage. However, traditional frequency detection methods, such as peak picking of the Spectrum or Power Spectral Density (PSD), are highly dependent on structural and environmental conditions. In highly variable vibrational environments, such as cultural heritage sites, stadiums, and transportation hubs, these methods often prove inadequate, leading to false modal identification. This study applies coherence analysis to vibrational measurements as a more reliable alternative that overcomes the limitations of traditional frequency extraction techniques. To evaluate its effectiveness, Magnitude-Squared Coherence (MSC), Squared Cross-Spectrum (SCS), and Wavelet Coherence (WC) were tested and compared with PSD analysis. Vibrational data were collected from a sensor network deployed at the Civil Museum of Castello Ursino (Catania, Italy), a site characterized by high structural complexity and variable visitor-induced vibrations. Results demonstrate that coherence analysis surpasses the limitations of traditional frequency identification techniques, with SCS and WC outperforming MSC in distinguishing resonance frequencies and providing a more stable and reliable frequency estimation. This approach enhances sensor network design by improving frequency detection, ensuring data reliability, and supporting long-term monitoring through instrumental drift detection, thus strengthening structural health monitoring in heritage sites. Full article

As the operating conditions of metro vehicles become more complex, the fatigue damage of metro bogie frames under actual operating conditions becomes increasingly difficult to evaluate realistically. After a period of operation of metro trains, the load excitation on the frame and its vibrations become more intense, which causes elastic resonance and leads to fatigue damage. Therefore, it is of high importance to establish test load conditions that match the actual operating environment to conduct fatigue reliability research on frames. To address this problem, in this study, we developed a high-precision force measurement frame and performed a long-term field test. The load optimization factor was used to quantify the load amplitude amplification near the modal frequency caused by the frame elastic resonance. The real load conditions and damage conditions of the fatigued weak position were obtained. Additionally, the square of the difference between the damage calculated via the load spectrum and the measured damage was used as the objective function; the calibrated test load spectrum fully covered the fatigued weak position damage as the constraint condition. The load spectrum calibration coefficient was obtained via multi-objective optimization through a genetic algorithm. The results showed that the damage calculated using the calibrated load agreed well with the real damage, and the ratio of the equivalent stress amplitude between the two was in the range of 1–2. The calibrated test load spectrum obtained in this study can be used for the structural optimization and fatigue reliability design of the later frame. The findings reported here can also be applied to other dynamic systems where fatigue failure is a critical issue. Full article

Objectives: Syncope is a common cause of the transient loss of consciousness, with neurally mediated syncope (NMS) and particularly vasovagal syncope (VVS) being the most prevalent types among older children and adolescents. VVS is primarily caused by heightened parasympathetic activity triggered by emotional or postural stimuli, resulting in a temporary disruption of circulation. Although anamnesis and physical examination play key roles in diagnosing VVS, additional diagnostic methods are necessary in unclear cases. This study aims to evaluate the long-term outcomes of pediatric patients with syncope, focusing on clinical characteristics, diagnosis, and treatment approaches. Methods: A retrospective analysis was conducted on 455 pediatric patients aged 8–21 years who presented with syncope at our cardiology clinic between 2005 and 2023. Patients diagnosed with cardiac syncope, epilepsy, or postural orthostatic tachycardia syndrome (POTS) were excluded. The remaining 283 patients were categorized into two groups: those with confirmed VVS—based on a comprehensive evaluation, including medical history, physical examination, and electrocardiography—and those suspected of VVS who lack a confident diagnosis after an initial assessment requiring tilt table testing. Clinical features, diagnostic methods, and treatment outcomes were analyzed. Results: The study cohort had a mean age of 13.5 ± 1.6 years, with a female predominance of 69%. Among patients who underwent tilt table testing (TTT), 74.8% exhibited a positive response, with mixed-type syncope being the most prevalent (51%). Syncope recurrence was significantly higher in the TTT group (54%) compared to the clinically diagnosed group (15%) (p < 0.001). Relapse risk was strongly associated with the syncope subtype, particularly cardioinhibitory type 2B (OR: 2.3, 95% CI: 1.1–4, p < 0.01), and episode frequency (OR: 1.7, 95% CI: 1.3–2.5, p = 0.03). Beta-blocker therapy was selectively administered and demonstrated a reduced relapse risk in a univariate analysis. Conclusions: VVS is a significant health issue in pediatric patients and the therapeutic modalities available encompass various interventions, including modifications to lifestyle, adequate hydration, and pharmacological therapies. TTT was found to be an effective diagnostic tool for identifying high-risk patients and is recommended for appropriate cases in pediatric VVS diagnosis in accordance with the guidelines, with the objective of refining therapeutic methodologies and ultimately augmenting patient prognoses. Full article