Search Results (109)

Amidst the escalating demand for high-precision structural health monitoring in large-scale engineering applications, carbon fiber-reinforced polymer fiber Bragg grating (CFRP-FBG) sensors have emerged as a pivotal technology for fatigue life evaluation, owing to their exceptional sensitivity and intrinsic immunity to electromagnetic interference. A time-series predictive architecture based on long short-term memory (LSTM) networks is developed in this work to facilitate intelligent fatigue life assessment of structures subjected to complex cyclic loading by capturing and modeling critical spectral characteristics of CFRP-FBG sensors, specifically the side-mode suppression ratio and main-lobe peak-to-valley ratio. To enhance model robustness and generalization, Principal Component Analysis (PCA) was employed to isolate the most salient spectral features, followed by data preprocessing via normalization and model optimization through the integration of the Adam optimizer and Dropout regularization strategy. Relative to conventional Backpropagation (BP) neural networks, the LSTM model demonstrated a substantial improvement in predicting the side-mode suppression ratio, achieving a 61.62% reduction in mean squared error (MSE) and a 34.99% decrease in root mean squared error (RMSE), thereby markedly enhancing robustness to outliers and ensuring greater overall prediction stability. In predicting the peak-to-valley ratio, the model attained a notable 24.9% decrease in mean absolute error (MAE) and a 21.2% reduction in root mean squared error (RMSE), thereby substantially curtailing localized inaccuracies. The forecasted confidence intervals were correspondingly narrower and exhibited diminished fluctuation, highlighting the LSTM architecture’s enhanced proficiency in capturing nonlinear dynamics and modeling temporal dependencies. The proposed method manifests considerable practical engineering relevance and delivers resilient intelligent assistance for the seamless implementation of CFRP-FBG sensor technology in structural health monitoring and fatigue life prognostics. Full article

In this study, we conducted two steady-state visual evoked potential (SSVEP) studies to develop a practical brain–computer interface (BCI) system for communication and control applications. The first study introduces a novel visual stimulus paradigm that combines checkerboard patterns with flickering circles configured in single-, double-, and triple-layer forms. We tested three flickering frequency conditions: a single fundamental frequency, a combination of the fundamental frequency and its harmonics, and a combination of two fundamental frequencies. The second study utilizes personalized visual stimuli to enhance SSVEP responses. SSVEP detection was performed using power spectral density (PSD) analysis by employing Welch’s method and relative PSD to extract SSVEP features. Commands classification was carried out using a proposed decision rule–based algorithm. The results were compared with those of a conventional checkerboard pattern with flickering squares. The experimental findings indicate that single-layer flickering circle patterns exhibit comparable or improved performance when compared with the conventional stimuli, particularly when customized for individual users. Conversely, the multilayer patterns tended to increase visual fatigue. Furthermore, individualized stimuli achieved a classification accuracy of 90.2% in real-time SSVEP-based BCI systems for six-command generation tasks. The personalized visual stimuli can enhance user experience and system performance, thereby supporting the development of a practical SSVEP-based BCI system. Full article

With the continuous development of high-speed electric multiple units (EMUs), vibration issues of vehicles have become increasingly prominent. During operation, the underfloor equipment installed on the carbody is subjected to random multi-point vibrations transmitted from the carbody, inducing significant fatigue damage. This paper presents a comprehensive analysis of multi-channel vibration environment data for various underfloor equipment across different operating speeds obtained through on-site measurements. A spectral synthetic method grounded in statistical principles is then proposed to generate vibration environment spectra for diverse underfloor equipment. Finally, utilizing fatigue analysis in the frequency domain, the fatigue damage to underfloor equipment is assessed under different operational environments. The research results show that the vibration environment spectrum of the underfloor equipment in high-speed EMU trains differs significantly from the vibration spectrum specified in the IEC 61373 standard, especially at high frequencies. Despite this difference in spectral characteristics, the overall vibration energy values of the two spectra are comparable. Additionally, the vibration spectra of different underfloor equipment exhibit variations that can be attributed to their installation positions. As operational speed increases, the fatigue damage to the underfloor equipment exhibits exponential growth. However, the total accumulated fatigue damage remains relatively low, consistently staying below a value of 1. Full article

Muscle activity during exercise is typically assessed using oximeters, to evaluate local oxygen saturation (SmO₂), or surface electromyography (sEMG), to analyze electrical activation. Despite the importance of combining these analyses, no study has evaluated both of them during specific swimming exercises in combination with mechanical power output. This study aimed to assess muscle activity during an incremental test on a swim-bench utilizing oximeters and sEMG. Nine male swimmers performed a five-steps test: PRE (3 min at rest), STEP 1, 2, and 3 (swimming at a frequency of 25, 30, and 40 cycle/min for a duration of 2, 2, and 1 min, respectively), and POST (5 min at rest). Each swimmer wore two oximeters and sEMG, one for each triceps brachii. Stroke frequency and arm mechanical power (from ~13 to ~52 watts) estimated by the swim-bench were different among all steps, while no differences between arms were found. SmO₂ (from ~70% to ~60%) and sEMG signals (from ~20 to ~65% in signal amplitude) showed a significant increase among all steps. In both arms, a large/very large correlation was found between mechanical power and SmO₂ (r < −0.634), mechanical power and sEMG onset/amplitude (r > 0.581), and SmO₂ and sEMG amplitude (r > 0.508). No correlations were found between the slope of the sEMG spectral indexes and the slope of SmO₂; only sEMG detected electrical manifestation of muscle fatigue through the steps (p < 0.05). Increased muscle activity, assessed by both oximeters and sEMG, was found at mechanical power increases, revealing both devices can detect effort variation during exercise. However, only sEMG seems to detect peripheral manifestations of fatigue in dynamic conditions. Full article

The luminous environment, shaped by daylight and electric light, significantly influences visual performance, physiological responses, and perceptual experiences. While these light sources are often perceived as distinct due to their differing effects on occupants’ cognition and well-being, the underlying mechanisms remain unclear. Nine lighting conditions were evaluated, combining three spectral types—daylight (DL), conventional LED (CLED), and daylight LED (DLED)—with three horizontal illuminance levels (300 lx, 500 lx, and 1000 lx). Twelve healthy subjects completed visual performance tasks (2-back working memory test), physiological measurements (heart rate variability and critical flicker frequency), and subjective evaluations. The results revealed that 500 lx consistently yielded the most favorable outcomes: 2-back task response speed improved by 6.2% over 300 lx and 1000 lx, and the critical flicker frequency difference was smallest, indicating reduced fatigue. DLED lighting achieved cognitive and physiological levels comparable to daylight. Heart rate variability analyzes further confirmed higher alertness levels under 500 lx DLED lighting (LF/HF = 3.31). Subjective ratings corroborated these findings, with perceived alertness and comfort highest under DLED and 500 lx conditions. These results demonstrate that DLED, which offers a balanced spectral composition and improved uniformity, may serve as an effective lighting configuration for supporting both visual and non-visual performance in indoor settings lacking daylight. Full article

Fatigue failure, generated by local multi-axial random state stress, frequently occurs in many engineering fields. Therefore, it is customary to perform experimental vibration tests for a structural durability assessment. Over the years, a number of testing methodologies, which differ in terms of the testing machines, specimen geometry, and type of excitation, have been proposed. The aim of this paper is to describe a new testing procedure for random multi-axial fatigue testing. In particular, the paper presents the experimental set-up, the testing procedure, and the data analysis procedure to obtain the multi-axial random fatigue life estimation. The originality of the proposed methodology consists in the experimental set-up, which allows performing multi-axial fatigue tests with different normal-to-shear stress ratios, by choosing the proper frequency range, using a single-axis exciter. The system is composed of a special designed specimen, clamped on a uni-axial shaker. On the specimen tip, a T-shaped mass is placed, which generates a tunable multi-axial stress state. Furthermore, by means of a finite element model, the system dynamic response and the stress on the notched specimen section are estimated. The model is validated through a harmonic acceleration base test. The experimental tests validate the numerical simulations and confirm the presence of bending–torsion coupled loading. Full article

Background: Both aging and cognitive fatigue are significant factors influencing alpha activity in the brain. However, the interactive effects of age and mental fatigue on the alpha spectrum and functional connectivity have not been fully elucidated. Methods: Using resting-state EEG data from an open-access dataset (younger: N = 198; older: N = 227) collected before and after a 2 h cognitive task block, we systematically examined the effects of aging and mental fatigue on alpha (8–13 Hz) oscillations via an aperiodic-corrected power spectrum, the weighted phase lag index (wPLI), and graph theory analysis. Results: In both spectral power and network efficiency, mental fatigue primarily modulates low alpha in younger individuals, while high alpha reflects stable age-related changes. The aperiodic offset and exponent decrease with age, while mental fatigue leads to an increase in the exponent. Notable interactions between age and mental fatigue are observed in low-alpha power, the aperiodic exponent, and the network efficiency of both low- and high-alpha bands. Conclusions: This study provides valuable insights into the differential modulation patterns of alpha activity by age and mental fatigue, as well as their interactions. These findings advance our understanding of how aging and mental fatigue differentially and interactively shape neural dynamics. Full article

Fatigue cracks in blades pose a significant threat to the safe operation of rotating machinery. Currently, the application of non-contact displacement sensors in blade vibration measurements has enabled the widespread analysis of nonlinear dynamic characteristics, such as natural frequency deviations and spectral anomalies, to enhance crack fault diagnosis in rotating machinery. However, these two dynamic characteristics are not distinguishable for crack changes, especially for incipient cracks, leading to potential misdiagnosis. In this paper, a dynamic characteristic called the envelope diagram image of vibration responses (EDIVR) was extracted from blade tip displacement signals collected during acceleration–deceleration cycles for crack diagnosis. Initially, considering the breathing effect of fatigue cracks, a structural dynamics finite element model of a blade containing a breathing crack is established to calculate its dynamic response under aerodynamic force. Subsequently, the sensitivity of three characteristics (natural frequency, frequency spectrum, and EDIVR) to crack fault changes is quantitatively compared based on the simulated response signals. Experimental validation confirms the accuracy of the proposed dynamic model and the effectiveness of the proposed feature. The study shows that under identical operational conditions, blades with cracks of equivalent depth and location exhibit maximum sensitivity to crack detection when EDIVR dynamic characteristics are employed as the fault diagnostic criterion. Moreover, this characteristic is less susceptible to signal noise interference compared to other dynamic characteristics, enhancing its potential for crack diagnosis in engineering applications. Full article

An early indicator of aging may appear around the eyes and the surrounding eye infrastructure. With aging, there come diminishing changes in vascular microcirculation and the accumulation of hemoglobin by-products that gather in the fatty pads beneath the eyes as dark circles, akin to skin bruising. In addition, the extracellular matrix that surrounds the eye is exposed to external threats like UV radiation, weather and pollution, as well as lifestyle choices that create fatigue. This causes the eyes to express wrinkles well before they begin to appear on the rest of the face, particularly in the corners of the eyes called the crow’s feet region. Consumers spend considerable amounts of resources combatting these effects. If consumers could treat some of the sources of these problems, in advance of the inevitable influences of aging, a kind of prejuvenation of the eye infrastructure, then perhaps the inevitable outcomes of aging apparent around the eyes could be slowed. This paper examines the development and in vitro testing of two unique botanical extracts, one based on a traditional medicine mushroom called Phellinus linteus (Huang Sang) and the other based on a traditional medicine root from the plant Angelica polymorpha sinensis (Dong Quai). When combined, these two extracts create a blend called ANGEL-EYE EFX^® [INCI: Water (and) Glycerin (and) Phellinus Linteus Extract (and) Angelica polymorpha sinensis Root Extract]. There are several key biomolecules of interest present in this blend, including hispolon, dihydrozingerone, and arginine, as demonstrated using advanced liquid chromatography/mass spectral analyses. The individual extracts were also broadly examined using human genomic microarray assays and then more specifically for their ability to influence several important skin proteins associated with undereye skin aging, including CYGB (Human Cytoglobin), OXSR1 (Oxidative Stress Response Kinase-1), LCE3B (Late Cornified Envelope-3B), EGFR (Epidermal Growth Factor Receptor), VEGFA (Vascular Endothelial Growth Factor-1), and NINJ1 (Ninjurin-1). It was found that the treatment of Normal Human Epidermal Keratinocytes (NHEKs) with increasing concentrations of the active blend between 0.05 and 2.0% showed statistically significant increases in all the proteins noted except VEGFA, which showed a statistically significant decrease in protein expression with the treatment of the Angelica polymorpha sinensis extract at 1.0%. Full article

Expected lives of mechanical parts and structures depend upon the environmental conditions, their dynamic behaviours and the task-oriented spectra of different loadings. This paper exploits contactless full-field mobilities, estimated by Scanner Laser Doppler Vibrometry (SLDV), in the real manufacturing, assembling and loading conditions of the thin plate tested, whose structural dynamics can be described in broad frequency bands, with no distorting inertia of sensors and no numerical models. The paper derives the mobilities into full-field strain Frequency Response Functions (FRFs), which map, by selecting the proper complex-valued broad frequency band excitation spectrum, the surface strains. From the latter, by means of the constitutive model, dynamic stress distributions are computed, to be exploited in fatigue spectral methods to map the expected life of the component, according to the selected tasks’ spectra and the excitation locations. The results of this experiment-based approach are thoroughly commented in sight of non-destructive-testing, damage and failure prognosis, Structural Health Monitoring, manufacturing and maintenance actions. Full article

Generating chaos from originally non-chaotic systems is a promising issue. Indeed, chaos has been successfully applied in many fields to improve system performance. In this work, a Buck converter is chaotified using a combination of the switching piecewise-constant characteristic and of anticontrol of chaos feedback. For electromagnetic compatibility compliance reasons, this feedback control method is able, at the same time, to achieve low spectral emissions and to maintain a small ripple of the output voltage and the inductance current. This new feedback implies a fast and non-linear switching action of the Buck MOSFET on a period of the ramp generator. Thus, it is essential to analyze its thermal performance. This is why we propose an original analysis of the influence of anticontrol of chaos and switching frequency variation on junction temperature: we investigate the correlation between the lifetime of the power electronic switching component and its thermal stress due to the addition of chaos. It appeared that a reduction in the current ripple did not degrade the MOSFET junction thermal performance, despite the fast switching of the MOSFET. Furthermore, a small degradation in the MOSFET lifetime was indicated for chaotic behavior versus periodic behavior. Thus, this leads to the conclusion that using anticontrol of chaos produces a low accumulated fatigue effect on a Buck converter semiconductor. Full article

In engineering, the study of the dynamic response of structures subjected to non-deterministically variable loads is particularly important, especially when considering the damage that such loads can cause due to fatigue phenomena. This is the case, for example, of the vibrations that a satellite must withstand during the launch phase. In the preliminary design phases, it is very useful to have semi-analytical calculation methodologies that are sufficiently reliable but, at the same time, simple. In the technical literature, there are numerous publications that deal with the study of the random dynamic response of beam models. In general, the presented studies are rather complex, and the dynamic solutions are often obtained in the time domain. The case of a linear elastic uniform cantilever beam model is considered here, for which the analytical expressions of the transfer functions for acceleration, displacement, bending moment, and bending stress are calculated, taking as input the acceleration assigned to the root section or an external lateral load. Knowing the spectral density of the input loads, the spectral densities of all the above-mentioned variables are calculated along the beam axis, assuming stationary and ergodic random processes. Using the spectral density of each output variable, the effective value (RMS) is obtained via integration, which allows for a preliminary estimate of the severity of the working conditions of the beam. The spectral density of the responses also allows us to quickly highlight the contribution of each natural vibration mode as the spectrum of the load varies. The results were obtained using simple spreadsheets available to the reader. Full article

With the expansion of high-rise building construction in China, tower cranes have become indispensable key equipment in the construction industry. To ensure the safety and structural reliability of tower cranes under complex working conditions, this paper takes a typical 40 m-high flat-arm tower crane as the research object. For the first time, the orthogonal test method was used to monitor the stress of key components (the root of the tower body and the root of the boom). The stress distribution characteristics of the tower crane structure under different working conditions were systematically analyzed. Then, based on the power spectral density analysis method, the natural frequency of the tower crane structure was identified. The influence of key structural parameters, such as lifting position, rope length, and lifting weight, on the stress of the tower crane was quantitatively studied through orthogonal experiments, revealing the multi-parameter coupling effect. The results show that the stress at the measuring point at the root of the tower body is significantly higher than that at the root of the boom. This indicates that the root of the tower body is the primary stress-bearing part of the tower crane structure, highlighting the need to focus on its fatigue performance and safety assessment. Based on the power spectral density analysis of the root stress of the tower crane, the natural frequencies of the tower crane structure were accurately identified. The first-order frequency was 0.10 Hz, and the second-order frequency was 0.20 Hz, providing data support for the study of the tower crane’s dynamic characteristics. The orthogonal test analysis shows that the influences of lifting position, rope length, and lifting weight on the stress of the tower crane are consistent, with no significant differences. The effects of lifting position and rope length on stress are dominant, while the influence of lifting weight is relatively small. These research findings provide an important basis for the lightweight design and safety assessment of tower cranes. Full article

A numerical tool is developed to simulate the random vibration-response-only-based fatigue delamination diagnosability in thermoplastic coupons. That is the ability to both detect damage and identify its current severity, aiming to establish a virtual framework for optimizing diagnosability methods. The numerical tool employs the FE method. It comprises two modules: a fatigue delamination module and a random vibration module. The first module implements a fatigue crack growth model based on the cohesive zone modeling method to predict delamination accumulation, while the second module uses an experimentally verified FE model of the delaminated coupon to predict its random vibration response. Delamination accumulation is evident in the ‘predicted’ FE-based power spectral densities. The model’s capability to diagnose delamination is demonstrated using seven different damage metrics based on simulated random vibration responses, enabling damage detection and severity assessment (increasing trend guides to distinguishing each fatigue state from its counterparts). Comparisons with their experimentally obtained counterparts are also used in the assessment. The procedure clearly suggests that the proposed numerical tool may be reliably used for virtually assessing the efficacy of random vibration-based fatigue damage diagnosability for any given structure and also to aid the user in selecting the method’s parameters for virtual diagnosability optimization. Full article

Probabilistic random vibration can speed up wear and tear on several components of the tracked vehicle, including the track system, drivetrain, and suspension. Extended exposure to high levels of vibration can cause structural damage to the vehicle frame and other critical components. Assessing random vibration in track vehicles requires a comprehensive approach that considers both the root causes and potential consequences of the vibrations. This random vibration significantly influences the structural performance of suspension arm which is key component of tracked vehicle. Damage due to fatigue is conventionally computed using time domain loaded signals with stress or strain data. This approach generally holds good when loading is periodic in nature but not be a good choice when dynamic resonance is in process. In this case an alternative frequency domain fatigue life analysis is used where the random loads and responses are characterized using a concept called Power spectral density (PSD). The current research article investigates the fatigue damage characteristics of a tracked vehicle suspension arm considering the dynamic loads induced by traversing on smooth and rough terrain. The analysis focusses on assessing the damage and stress response Power spectral density (PSD) ground-based excitation which is termed PSD-G acceleration. Quasi Static Finite Element Method based approach is used to simulate the operational conditions experienced by the suspension arm. Through comprehensive numerical simulations, the fatigue damage accumulation patterns are examined, providing insights into the structure integrity and performance durability of the suspension arm under varying operational scenarios. The obtained stress response PSD data and fatigue damage showed that the rough terrain response exhibits higher stresses in suspension arm. The accumulated stresses in case of rough terrain may prompt to brittle failure at specific critical locations. This research contributes to the advancement to the design and optimization strategies for tracked vehicle components enhancing their reliability and longevity in demanding operational environments. Full article