Search Results (455)

Rolling bearings are prone to failure, meaning that research on intelligent fault diagnosis is crucial in relation to this key transmission component in rotating machinery. The application of deep learning (DL) has significantly advanced the development of intelligent fault diagnosis. This paper proposes a novel method for rolling bearing fault diagnosis based on the fractional constant Q non-stationary Gabor transform (FCO-NSGT) and VMamba-Conv. Firstly, a rolling bearing fault experimental platform is established and the vibration signals of rolling bearings under various working conditions are collected using an acceleration sensor. Secondly, a kurtosis-to-entropy ratio (KER) method and the rotational kernel function of the fractional Fourier transform (FRFT) are proposed and applied to the original CO-NSGT to overcome the limitations of the original CO-NSGT, such as the unsatisfactory time–frequency representation due to manual parameter setting and the energy dispersion problem of frequency-modulated signals that vary with time. A lightweight fault diagnosis model, VMamba-Conv, is proposed, which is a restructured version of VMamba. It integrates an efficient selective scanning mechanism, a state space model, and a convolutional network based on SimAX into a dual-branch architecture and uses inverted residual blocks to achieve a lightweight design while maintaining strong feature extraction capabilities. Finally, the time–frequency graph is inputted into VMamba-Conv to diagnose rolling bearing faults. This approach reduces the number of parameters, as well as the computational complexity, while ensuring high accuracy and excellent noise resistance. The results show that the proposed method has excellent fault diagnosis capabilities, with an average accuracy of 99.81%. By comparing the Adjusted Rand Index, Normalized Mutual Information, F1 Score, and accuracy, it is concluded that the proposed method outperforms other comparison methods, demonstrating its effectiveness and superiority. Full article

This paper addresses the critical challenge of selecting suitable pile foundations in port engineering by systematically investigating the axial bearing behavior of large-diameter steel pipe piles and prestressed high-strength concrete (PHC) piles. The study integrates both numerical simulations and field tests within the context of the Yancheng Dafeng Port Security Facilities Project. A self-balanced static load numerical model for PHC piles was developed using Plaxis 3D, enabling the simulation of load-displacement responses, axial force transfer, and side resistance distribution. The accuracy of the model was verified through a comparison with field static load test data. With the verified model parameters, the internal force distribution of steel pipe piles was analysed by modifying material properties and adjusting boundary conditions. A comparative analysis of the two pile types was conducted under identical working conditions. The results reveal that the ultimate bearing capacities of the 1# steel pipe pile and the 2# PHC pile are 6734 kN and 6788 kN, respectively. Despite the PHC pile having a 20% larger diameter, its ultimate bearing capacity is comparable to that of the steel pipe pile, suggesting a more efficient utilisation of material strength in the latter. Further numerical simulations indicate that, under the same working conditions, the ultimate bearing capacity of the steel pipe pile exceeds that of the PHC pile by 18.43%. Additionally, the axial force distribution along the steel pipe pile shaft is more uniform, and side resistance is mobilised more effectively. The reduction in side resistance caused by construction disturbances, combined with the slenderness ratio (L/D = 41.7) of the PHC pile, results in 33.87% of the pile’s total bearing capacity being attributed to tip resistance. The findings of this study provide crucial insights into the selection of optimal pile types for terminal foundations, considering factors such as bearing capacity, environmental conditions, and economic viability. Full article

The use of 3D printing holds significant promise to transform the construction industry by enabling automation and customization, although key challenges remain—particularly the control of fresh-state rheology. This study presents a novel formulation that combines potassium-rich biomass fly ash (BFAK) with an air-entraining plasticizer (APA) to optimize the rheological behavior, hydration kinetics, and structural performance of mortars tailored for extrusion-based 3D printing. The results demonstrate that BFAK enhances the yield stress and thixotropy increases, contributing to improved structural stability after extrusion. In parallel, the APA adjusts the viscosity and facilitates material flow through the nozzle. Isothermal calorimetry reveals that BFAK modifies the hydration kinetics, increasing the intensity and delaying the occurrence of the main hydration peak due to the formation of secondary sulfate phases such as Aphthitalite [(K₃Na(SO₄)₂)]. This behavior leads to an extended setting time, which can be modulated by APA to ensure a controlled processing window. Flowability tests show that BFAK reduces the spread diameter, improving cohesion without causing excessive dispersion. Calibration cylinder tests confirm that the formulation with 1.5% APA and 2% BFAK achieves the maximum printable height (35 cm), reflecting superior buildability and load-bearing capacity. These findings underscore the novelty of combining BFAK and APA as a strategy to overcome current rheological limitations in digital construction. The synergistic effect between both additives provides tailored fresh-state properties and structural reliability, advancing the development of a sustainable SMC and printable cementitious materials. Full article

As the core device for protecting the safety of the pressure-bearing system, the spring full-open safety valve is prone to various forms of valve seat sealing surface damage after long-term opening and closing impact, corrosion, and medium erosion, which may lead to internal leakage. In view of the problems that the high-frequency acoustic emission signal of the internal leakage of the safety valve has, namely, a large number of energy-overlapping areas in the frequency domain, the overall signal presents broadband characteristics, large noise content, and no obvious time–frequency characteristics. A composite denoising method, IWTD, improved wavelet threshold function with dual adjustable factors, and the improved VMD algorithm is proposed. In view of the problem that the optimal values of the dual adjustment factors a and b of the function are difficult to determine manually, an improved dung beetle optimization algorithm is proposed, with the maximum Pearson coefficient as the optimization target; the optimization is performed within the value range of the dual adjustable factors a and b, so as to obtain the optimal value. In view of the problem that the key parameters K and α in VMD decomposition are difficult to determine manually, the maximum Pearson coefficient is taken as the optimization target, and the improved dung beetle algorithm is used to optimize within the value range of K and α, so as to obtain the IVMD algorithm. Based on the IVMD algorithm, the characteristic decomposition of the internal leakage acoustic emission signal occurs after the denoising of the IWTD function is performed to further improve the denoising effect. The results show that the Pearson coefficients of all types of internal leakage acoustic emission signals after IWTD-IVMD composite noise reduction are greater than 0.9, which is much higher than traditional noise reduction methods such as soft and hard threshold functions. Therefore, the IWTD-IVMD composite noise reduction method can extract more main features out of the measured spring full-open safety valve internal leakage acoustic emission signals, and has a good noise reduction effect. Feature recognition after noise reduction can provide a good evaluation for the safe operation of the safety valve. Full article

Ascorbic acid (AA) plays a multidimensional role in human physiological and pathological processes, and the detection of its urinary concentration facilitates the diagnosis of metabolic or kidney diseases. Visual detection exhibits minimal reliance on instrumentation and is suitable for on-site analysis in routine settings. Current visual colorimetric detection methods typically rely on enzymatic or nanozyme-based catalysis. Organic neutral radicals bearing unpaired electrons represent a class of materials exhibiting intrinsic responsiveness to redox stimuli. The tris (2,4,6-trichlorophenyl) methyl (TTM) radical has attracted widespread attention for its adjustable optical properties and sensitive response to external redox stimuli. We synthesized a novel radical TTM-DMODPA and applied it for non-catalytic colorimetric detection of AA. It not only enables quantitative AA measurement via UV-vis spectroscopy (linear range: 1.25–75 μmol/L, LOD: 0.288 μmol/L) but also facilitates instrument-free visual detection using smartphone cameras (linear range: 0–65 μmol/L, LOD: 1.46 μmol/L). This method demonstrated satisfactory performance in the measurement of AA in actual urine samples. Recovery rates ranged from 97.8% to 104.1%. Consequently, this work provides a portable and effective method for assessing AA levels in actual urine samples. Full article

The deformation characteristics of the surrounding rock in tunnel groups are considered critical for the design of support structures and the assurance of the long-term safety of deep-buried diversion tunnels. The deformation behavior of surrounding rock in tunnel groups was investigated to guide structural support design. Field tests and numerical simulations were performed to analyze the distribution of ground stress and the ground reaction curve under varying conditions, including rock type, tunnel spacing, and burial depth. A solid unit–structural unit coupled simulation approach was adopted to derive the two-liner support characteristic curve and to examine the propagation behavior of concrete cracks. The influences of surrounding rock strength, reinforcement ratio, and secondary lining thickness on the bearing capacity of the secondary lining were systematically evaluated. The following findings were obtained: (1) The tunnel group effect was found to be negligible when the spacing (D) was ≥65 m and the burial depth was 1600 m. (2) Both P_0.3 and P_max of the secondary lining increased linearly with reinforcement ratio and thickness. (3) For surrounding rock of grade III (IV), 95% u_lim and 90% u_lim were found to be optimal support timings, with secondary lining forces remaining well below the cracking stress during construction. (4) For surrounding rock of grade V in tunnels with a burial depth of 200 m, 90% u_lim is recommended as the initial support timing. Support timings for tunnels with burial depths between 400 m and 800 m are 40 cm, 50 cm, and 60 cm, respectively. Design parameters should be adjusted based on grouting effects and monitoring data. Additional reinforcement is recommended for tunnels with burial depths between 1000 m and 2000 m to improve bearing capacity, with measures to enhance impermeability and reduce external water pressure. These findings contribute to the safe and reliable design of support structures for deep-buried diversion tunnels, providing technical support for design optimization and long-term operation. Full article

Certain industries will bear a disproportionate share of the burden of climate change. Climate change risk perceptions can impact workers’ mental health and well-being; increased climate change risk perceptions are also associated with more favourable adaptive attitudes. It is, therefore, important to understand whether climate risk perceptions differ across workers between industries. We conducted an online survey of British Columbians (16+) in 2021 using social media advertisements. Participants rated how likely they believed their industry (Natural Resources, Science, Art and Recreation, Education/Law/Government, Health, Management/Business, Manufacturing, Sales, Trades) would be affected by climate change (on a scale from “Very Unlikely” to “Very Likely”). Ordinal logistic regression examined the association between occupational category and perceived industry vulnerability, adjusting for socio-demographic factors. Among 877 participants, 66.1% of Natural Resources workers perceived it was very/somewhat likely that climate change would impact their industry; only those in Science (78.3%) and Art and Recreation (71.4%) occupations had higher percentages. In the adjusted model, compared to Natural Resources workers, respondents in other occupations, including those in Art and Recreation, Education/Law/Government, Management/Business, Manufacturing, Sales, and Trades, perceived significantly lower risk of climate change-related industry impacts. Industry-specific interventions are needed to increase awareness of and readiness for climate adaptation. Policymakers and industry leaders should prioritize sectoral differences when designing interventions to support climate resilience in the workforce. Full article

This study investigates the dynamic relationship between bearing gearbox condition indicators (BGCIs) and the lubrication oil temperature within the framework of health and usage monitoring system (HUMS) applications. Using the dynamic autoregressive distributed lag (DARDL) simulation model, we quantified both the short- and long-term responses of condition indicators to shocks in oil temperature, offering a robust framework for a counterfactual analysis. To complement the time-domain perspective, we applied a wavelet coherence analysis (WCA) to explore time–frequency co-movements and phase relationships between the condition indicators under varying operational regimes. The DARDL results revealed that the ball energy, cage energy, and inner and outer race indicators significantly increased in response to the oil temperature in the long run. The WCA results further confirmed the positive association between oil temperature and the condition indicators under examination, aligning with the DARDL estimations. The DARDL model revealed that the ball energy and the inner race energy have statistically significant long-term effects on the oil temperature, with p-values < 0.01. The adjusted R² of 0.785 and the root mean square error (MSE) of 0.008 confirm the model’s robustness. The wavelet coherence analysis showed strong time–frequency correlations, especially in the 8–16 scale range, while the frequency-domain causality (FDC) tests confirmed a bidirectional influence between the oil temperature and several condition indicators. The FDC analysis showed that the oil temperature significantly affected the BGCIs, with evidence of feedback effects, suggesting a mutual dependency. These findings contribute to the advancement of predictive maintenance frameworks in HUMSs by providing practical insights for enhancing system reliability and optimizing maintenance schedules. The integration of dynamic econometric approaches demonstrates a robust methodology for monitoring critical mechanical components and encourages further research in broader aerospace and industrial contexts. Full article

At present, the redundant structures are one of the most effective methods for solving magnetic levitation bearing coil failure. Coil failure causes residual effective magnetic poles to form different support structures and even asymmetrical structures. For the magnetic bearing with redundant structures, how to construct the electromagnetic force (EMF) that occurs under different support structures to achieve support reconstruction is the key to realizing fault tolerance control. To reveal the support reconstruction mechanism of magnetic bearing with a redundant structure, firstly, this paper takes a single-degree-of-freedom magnetic suspension body as an example to conduct a linearization theory analysis of the offset current, clarifying the concept of the current distribution matrix (CDM) and its function; then, the nonlinear EMF mode of magnetic bearing with an eight-pole is constructed, and it is linearized by using the theory of bias current linearization. Furthermore, the conditions of no coils fail, the 8th coil fails, and the 6–8th coils fail are considered, and, with the maximum principle function of EMF, the corresponding current matrices are obtained. Meanwhile, based on the CDM, the corresponding magnetic flux densities were calculated, proving that EMF reconstruction can be achieved under the three support structures. Finally, with the CDM and position control law, a fault-tolerant control system was constructed, and the simulation of the magnetic bearing with a redundant structure was carried out. The simulation results reveal the mechanism of support reconstruction with three aspects of rotor displacement, the value and direction of currents that occur in each coil. The simulation results show that, in the 8-pole magnetic bearing, this study can achieve support reconstruction in the case of faults in up to two coils. Under the three working conditions of wireless no coil failure, the 8th coil fails and the 6–8th coils fail, the current distribution strategy was adjusted through the CDM. The instantaneous displacement disturbance during the support reconstruction process was less than 0.28 μm, and the EMF after reconstruction was basically consistent with the expected value. Full article

In this paper, we investigate the target-approaching control problem for a discrete-time first-order vehicle system where the target area is modeled as a static circular region. In the absence of absolute bearing or position information, we propose a simple local controller that relies solely on range measurements to the target obtained at two consecutive sampling instants. Specifically, if the measured distance decreases between two successive samples, the vehicle maintains a constant velocity; otherwise, it rotates its velocity vector by an angle of $\pi /2$ in the clockwise direction. This control strategy guarantees convergence to the target region, ensuring that the vehicle’s velocity direction remains unchanged in the best-case scenario and is adjusted at most three times in the worst case. The effectiveness of the proposed method is theoretically established and further validated through outdoor experiments with a mobile vehicle. Full article

The implantable capsule grouting pile is a novel pile foundation technology in which a capsule is affixed to the side of the implanted pile to facilitate grouting and achieve extrusion-based reinforcement. This technique is designed to improve the bearing capacity of implanted piles in coastal areas with deep, soft soil. This study conducted model tests involving multiple grouting positions across different foundation types to refine the construction process and validate the enhancement of bearing capacity. Systematic measurements and quantitative analyses were performed to evaluate the earth pressure distribution around the pile, the resistance characteristics of the pile end, the evolution of side friction resistance, and the overall bearing performance. Special attention was given to variations in the lateral friction resistance adjustment coefficient under different working conditions. Furthermore, an actual case analysis was conducted based on typical soft soil geological conditions. The results indicated that the post-grouting process formed a dense soil ring through the expansion and extrusion of the capsule, resulting in increased soil strength around the pile due to increased lateral earth pressure. Compared to conventional piles, the grouted piles exhibited a synergistic improvement characterized by reduced pile end resistance, enhanced side friction resistance, and improved overall bearing capacity. The ultimate bearing capacity of model piles at different grouting depths across different foundation types increased by 6.8–22.3% compared with that of ordinary piles. In silty clay and clayey silt foundations, the adjustment coefficient η_s of lateral friction resistance of post-grouting piles ranged from 1.097 to 1.318 and increased with grouting depth. The findings contribute to the development of green pile foundation technology in coastal areas. Full article

In this study, a novel shape memory alloy actuated bearing active preload system (SMA-BAPS) was proposed and experimentally demonstrated. SMA actuators placed in a single or antagonistic configuration were employed to drive the screw pair and thus fulfill one-way or bidirectional preload adjustment. Moreover, the self-locking screw pair was used to maintain the bearing preload without external energy input. To determine the parameters of screw pair and SMA actuators, a detailed design process was conducted based on analytical models of the proposed system. Finally, a screw pair with a lead of 3 mm and SMA actuators with a diameter of 0.5 mm and a length of 130 mm were adopted. Prototype tests were conducted to validate and evaluate the performance of the preload adjustment with the SMA-BAPS. The resistive torque and the natural frequency of spindles were recorded to represent the preload level of the bearing. Through the performance tests, the SMA-BAPS induced a maximum 47% variation in the resistive torque and a 20% variation in the spindle’s natural frequency. The response time of the SMA-BAPS was less than 5 s when the heating current of 5 A was applied on the SMA actuator. This design highlighted the compact size, quick response, as well as the bidirectional preload adjustment, representing its potential use in aerospace mechanisms and advanced motors. Full article

The Bearing–Angle algorithm effectively improves the observability of vision-based motion estimation for moving targets by combining the dimensional information of target detection frames. However, the robustness of this algorithm will be significantly reduced when the observation error increases due to sudden changes in the target motion state. To address this shortcoming, this paper proposes a visual target motion estimation algorithm called the Dynamic Bearing–Angle, which aims to improve the accuracy and robustness of target motion analysis in dynamic scenarios such as unmanned aerial vehicle (UAV). The algorithm innovatively introduces a dual robustness mechanism of dynamic noise intensity adaptation and outlier suppression based on M-estimation. By adjusting the noise covariance matrix in real time and assigning low weights to the outlier observations using the Huber weight function, the Dynamic Bearing–Angle algorithm is able to effectively cope with non-Gaussian noise and sudden target maneuvers. We validate the performance of the proposed algorithm with numerical simulations and real sensor data, and the results show that the Dynamic Bearing–Angle maintains good robustness and accuracy under different noise intensities. Full article

This paper reviews the applications and performance advantages of ultra-high-performance concrete (UHPC), engineered cementitious composite (ECC), and recycled aggregate concrete (RAC) in composite flexural members. UHPC is characterized by its ultra-high strength, high toughness, excellent durability, and microcrack self-healing capability, albeit with high costs and complex production processes. ECC demonstrates superior tensile, flexural, and compressive strength and durability, yet it exhibits a lower elastic modulus and greater drying shrinkage strain. RAC, as an eco-friendly concrete, offers cost-effectiveness and environmental benefits, although it poses certain performance challenges. The focus of this review is on how to enhance the load-bearing capacity of composite beams or slabs by modifying the interface roughness, adjusting the thickness of the ECC or UHPC layer, and altering the cross-sectional form. The integration of diverse concrete materials improves the performance of beam and slab elements while managing costs. For instance, increasing the thickness of the UHPC or ECC layer typically enhances the load-bearing capacity of composite beams or plates by approximately 10% to 40%. Increasing the roughness of the interface can significantly improve the interfacial bond strength and further augment the ultimate load-bearing capacity of composite components. Moreover, the optimized design of material mix proportions and cross-sectional shapes can also contribute to enhancing the load-bearing capacity, crack resistance, and ductility of composite components. Nevertheless, challenges persist in engineering applications, such as the scarcity of long-term monitoring data on durability, fatigue performance, and creep effects. Additionally, existing design codes inadequately address the nonlinear behavior of multi-material composite structures, necessitating further refinement of design theories. Full article

Background/Objectives: Worldwide, men experience a higher incidence of pancreatic cancer (PC) than women. Methods: To increase understanding of the underlying reasons for this sex-related difference, we analysed general and sex-related risk factors for PC in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (women/men No. = 293,682/136,728; 717/577 PC-cases). Results: Cox proportional hazards models showed a 1.31-fold higher risk of developing PC for men compared to women (HR, 95% CI 1.15–1.49) after adjustment for age, smoking history, BMI, diabetes, and alcohol consumption. Associations of PC with established risk factors did not differ between men and women, with the exception of a greater risk of PC among women with greater attained body height, meat consumption and cigarettes smoked (1.12 (1.05–1.19) per 5 cm, 1.18 (1.02–1.36) per 100 g/d, 1.42 (1.27–1.59) per 10/d; respectively). Among child-bearing women, long cumulative duration of breastfeeding was inversely associated with risk of PC (HR 0.74, 95% CI 0.61–0.89) for >5.7 months of breastfeeding (median) relative to ≤5.7 months and among HRT users, cumulative duration of HRT use was inversely associated with PC risk (HR 0.71, 95% CI 0.53–0.95, >2.4 versus ≤2.4 years). Further reproductive and hormonal factors, such as age at menarche, number of full-term pregnancies, age at menopause, or use of oral contraceptives, were not significantly associated with PC risk. Conclusions: Pooled analyses of large cohort studies are needed to confirm these results, and detailed data on the type and intensity of HRT are required to better evaluate its effect. Full article