Search Results (8,964)

This paper proposes an adaptive gain twisting sliding-mode control (AGTSMC) strategy for trapezoidal variable-stiffness joints (TVSJs) to achieve accurate trajectory tracking under both matched and mismatched uncertainties. The TVSJ employs a compact trapezoidal leaf spring with grooved bearing followers (GBFs), enabling wide-range stiffness modulation through low-friction rolling contact. To address the strong nonlinearities and unmodeled dynamics introduced by stiffness variation, a Lyapunov-based adaptive twisting controller is developed, where the gains are automatically adjusted without conservative overestimation. A second-order sliding-mode differentiator is integrated to estimate velocity and disturbance terms in finite time using only position measurements, effectively reducing chattering. The proposed controller guarantees finite-time stability of the closed-loop system despite bounded uncertainties and measurement noise. Extensive simulations and hardware-in-the-loop experiments on a TVSJ platform validate the method. Compared with conventional sliding mode controller (CSMC), terminal sliding mode controller (TSMC), and fixed-gain twisting control (TC), the AGTSMC achieves faster convergence, lower steady-state error, and improved vibration suppression across low, high, and variable stiffness modes. Experimental results confirm that the proposed approach enhances tracking accuracy and energy efficiency while maintaining robustness under large stiffness variations. Full article

The operational efficiency and precision of boom sprayers, as critical equipment for protecting field crops, are vital to global food security and agricultural sustainability. In precision agriculture systems, achieving uniform pesticide application fundamentally depends on maintaining stable boom posture during operation. However, severe boom vibration not only directly causes issues like missed spraying, double spraying, and pesticide drift but also represents a critical bottleneck constraining its functional realization in cutting-edge applications. Despite its importance, achieving absolute boom stability is a complex task. Its suspension system design faces a fundamental technical contradiction: effectively isolating high-frequency vehicle vibrations caused by ground surfaces while precisely following large-scale, low-frequency slope variations in the field. This paper systematically traces the evolutionary path of self-balancing boom technology in addressing this core contradiction. First, the paper conducts a dynamic analysis of the root causes of boom instability and the mechanism of its detrimental physical effects on spray quality. This serves as a foundation for the subsequent discussion on technical approaches for boom support and balancing systems. The paper also delves into the evolution of sensing technology, from “single-point height measurement” to “point cloud morphology perception,” and provides a detailed analysis of control strategies from classical PID to modern robust control and artificial intelligence methods. Furthermore, this paper explores the deep integration of this technology with precision agriculture applications, such as variable rate application and autonomous navigation. In conclusion, the paper summarizes the main challenges facing current technology and outlines future development trends, aiming to provide a comprehensive reference for research and development in this field. Full article

Switched reluctance motors (SRMs) are promising for applications such as air compressors due to their robust structure and fault tolerance, but suffer from high torque ripple and radial electromagnetic forces that cause vibration and noise. This paper proposes a game-theoretic multi-objective design optimization framework to enhance electromagnetic performance by simultaneously maximizing average torque and minimizing radial force. The optimization problem is transformed into a game model where objectives are treated as players with strategy spaces derived through fuzzy clustering and correlation analysis. Particle swarm optimization (PSO) is employed to solve the payoff functions under both novel cooperative and non-cooperative game scenarios of SRMs’ structural design. Finite element analysis (FEA) validates the optimized motor topology, showing that the cooperative game model achieves a balanced performance with high torque density and reduced vibration, meeting the requirements for air compressor drives. The proposed method effectively resolves the weight selection challenge in traditional multi-objective optimization and demonstrates strong engineering feasibility. Full article

Enterprises in industries such as coking and metallurgy possess extensive industrial equipment requiring real-time monitoring and timely fault detection. Transmitting all monitoring data to servers or cloud platforms for processing presents challenges, including substantial data volumes, high latency, and significant bandwidth consumption, thereby compromising the monitoring system’s real-time performance and stability. This paper proposes a cloud–edge collaborative approach for edge feature extraction in equipment monitoring. A three-tier collaborative architecture is established: “edge pre-processing-cloud optimization-edge iteration”. At the edge, lightweight time-domain and frequency-domain feature extraction modules are employed based on equipment structure and failure mechanisms to rapidly pre-process and extract features from monitoring data (e.g., equipment vibration), substantially reducing uploaded data volume. The cloud node constructs a diagnostic feature library through threshold self-learning and data-driven model training, then disseminates optimized feature extraction parameters to the edge node via this threshold learning mechanism. The edge node dynamically iterates its feature extraction capabilities based on updated parameters, enhancing the capture accuracy of critical fault features under complex operating conditions. Verification and demonstration applications were conducted using an enterprise’s online equipment monitoring system as the experimental scenario. The results indicate that the proposed method reduces data transmission volume by 98.21% and required bandwidth by 98.25% compared to pure cloud-based solutions, while effectively enhancing the monitoring system’s real-time performance. This approach significantly improves equipment monitoring responsiveness, reduces demands on network bandwidth and data transmission, and provides an effective technical solution for equipment health management within industrial IoT environments. Full article

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is highly prevalent in patients with type 2 diabetes (T2D), and advanced fibrosis is the strongest predictor of liver-related morbidity and mortality. Therefore, early noninvasive risk stratification is critical. While the Fibrosis-4 (FIB-4) index and vibration-controlled transient elastography (VCTE) are widely used, the newer FibroScan-AST (FAST) score has shown promise in detecting at-risk metabolic-associated steatohepatitis (MASH) with significant fibrosis. Evidence comparing the FAST and FIB-4 indices in Middle Eastern T2D populations remains limited. We compared the diagnostic performances of these models for advanced fibrosis in Saudi patients with T2D and MASLD. Methods: We conducted a retrospective analysis of 273 patients diagnosed with T2D and MASLD. All patients underwent VCTE. To identify advanced fibrosis, we used liver stiffness measurement (LSM) as a surrogate marker for liver biopsy. We calculated the FAST and FIB-4 indices for each patient. To assess the diagnostic performance of these scores, we evaluated their sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUROC). Results: In this cohort study, 26.4% of participants had a high-risk FAST score (>0.35; median: 0.13). Patients with high-risk FAST scores (>0.35) were younger, had higher BMIs, elevated liver enzyme levels, and poorer glycemic control than those in the lower-risk groups. High-risk FAST scores were strongly correlated with elevated LSM, FIB-4, and controlled attenuation parameter values (p < 0.001). The FAST score demonstrated better performance than the FIB-4 index in detecting advanced fibrosis. It showed higher accuracy (85.4% vs. 77.3%), sensitivity (82.0% vs. 48.0%), and negative predictive value (95.5% vs. 87.8%) while maintaining a similar specificity. The AUROC values were 0.936 (95% CI: 0.901–0.971) for the FAST score compared to 0.711 (95% CI: 0.625–0.797) for the FIB-4 index. Conclusions: The FAST score demonstrated better diagnostic accuracy than the FIB-4 index and identified patients with poor metabolic control and obesity as being at the highest risk among Saudi patients with T2D and MASLD. These findings support the integration of other elastography-based tests into stepwise fibrosis screening pathways for diabetic populations, potentially improving the early detection of advanced fibrosis and patient outcomes. Full article

Aviation hydraulic systems operate under high pressure and large flow rates, which induce significant fluid pressure pulsations and hydraulic shocks in pipelines. These pulsations, exacerbated by complex external loads, can lead to excessive vibration stress, component damage, oil leakage, and compromised system safety. While existing methods—such as pump structure optimization, pipeline layout adjustment, and active control—can reduce pulsations to some extent, they are limited by cost, reliability, and adaptability, particularly under high-pressure and multi-excitation conditions. Passive control, using pressure pulsation damping devices, has proven to be more practical; however, conventional designs typically focus on low-load systems and have limited frequency adaptability. This paper proposes a multi-hole parallel pressure pulsation damping device that offers high vibration attenuation, broad adaptability, and easy installation. A combined simulation–experiment approach is employed to investigate its damping mechanism and performance. The results indicate that the damping device effectively reduces vibrations in the 200–500 Hz range, with minimal impact from changes in load pressure and rotational speed. Under a high pressure of 21 MPa and a speed of 1500 rpm, the maximum insertion loss can reach 15.82 dB, significantly reducing the pressure pulsation in the hydraulic pipeline. Full article

Background and Objectives: Elastodontic appliances made of medical-grade silicone are increasingly used in interceptive orthodontics, but prolonged intraoral exposure may affect their stability. This study evaluated structural changes in LM-Activator^TM 2 appliances after clinical use, using Fourier-transform infrared (FTIR) spectroscopy. Materials and Methods: Eight appliances (one unused control and seven worn for 3–24 months) were analyzed by FTIR-ATR in the 4000–650 cm⁻¹ range. Absorption bands characteristic of polydimethylsiloxane (PDMS) were quantified, and indices reflecting backbone crosslinking, side-group retention, hydrophilicity, and relative reduction in methyl-related spectral contributions were calculated. Results: The PDMS backbone remained chemically intact across all samples. However, progressive molecular reorganization was detected with wear duration. The Backbone Dominance Index increased significantly from control to 24 months, while side-group indices decreased, confirming apparent depletion of methyl-related FTIR bands. Hydrophilicity and crosslinking indices rose over time, particularly after 12 months, indicating increased surface polarity and network densification. Conclusions: LM-Activator^TM 2 appliances undergo gradual intraoral aging, marked by backbone crosslinking and apparent reduction in methyl-associated vibrational contributions inferred from FTIR ratio side-groups. These changes, while not compromising the polymer identity, may influence surface properties, biofilm retention, and long-term mechanical behavior. Periodic replacement is recommended to ensure optimal clinical performance. Full article

Accurate characterization of rail corrugation is essential for the operation and maintenance of urban rail transit. To enhance the representation capability for rail corrugation, this study proposes a sound–vibration feature fusion method based on Laplacian manifold learning. The method constructs a multidimensional feature space using real-world acoustic and vibration signals measured from metro vehicles, introduces a Laplacian manifold structure to capture local geometric relationships among samples, and incorporates inter-class separability into traditional intra-class compactness metrics. Based on this, a comprehensive feature evaluation index L_r is developed to achieve adaptive feature ranking. The final fusion indicator, LWVAF, is generated through weighted feature integration and used for rail corrugation characterization. Validation on in-service metro line data demonstrates that, after rail grinding, LWVAF exhibits a more pronounced reduction and higher sensitivity to changes compared with individual acoustic or vibration features, reliably reflecting improvements in rail corrugation. The results confirm that the proposed method maintains strong robustness and physical interpretability even under small-sample and weak-label conditions, offering a new approach for sound–vibration fusion analysis and corrugation evolution studies. Full article

The vibrations of the dynamical system play an important role in biological processes, electrical engineering, and mechanical structures. In this work, we focus on the behaviors of dynamical systems, such as periodical or damped oscillations and asymptotic behaviors. Theorems for explicitly integrability of the dynamical system are established. The effect of the physical parameters $0<a\le 1$, $d\ge 0$ is semi-analytically analyzed by means of the Optimal Parametric Iteration Method (OPIM). We pointed out some cases when the investigated system admits only one first integral or two first integrals. These cases are reduced to a second-order nonlinear differential equations, which are solved by OPIM. The OPIM solutions are highlighted qualitatively by figures and quantitatively by tables, respectively, and are in good agreement with corresponding numerical ones. The accuracy of the obtained results are emphasized by comparison with the iterative solutions, via the classical iterative method and new optimal iterative method, respectively. Other advantages of the applied method are pointed out. Full article

Incorporating sensors such as microelectromechanical system (MEMS)-based inertial measurement units (IMUs) and strain gauges into aircraft structures has the potential to complement ground vibration testing results and improve the tracking of structural modes and wing shape in flight, as well as structural health monitoring. This study evaluates the feasibility and accuracy of employing MEMS accelerometers and gyroscopes together with strain gauges to estimate the structural modes of an aircraft. For this purpose, a ground vibration test was carried out on a 1:3 scaled Diana 2 glider model from which the displacement, rotation, and strain modes were estimated. The estimated modal parameters were compared with traditional piezoelectric accelerometer results and Finite Element Method model predictions. The results showed that the modal frequencies, damping ratios, and mode shapes estimated using MEMS IMUs and strain gauges closely matched the reference accelerometer estimates. Furthermore, the combination of displacement, rotation, and strain mode shapes allowed for greater insight into the structural dynamics. The exploratory use of gyroscopes for aircraft GVT allowed the structural torsion to be captured directly, thereby potentially simplifying future GVT setups by eliminating the need for placing accelerometers in pairs across the structure. Full article

A machine learning (ML) methodology for the robust detection and severity characterization of incipient gear faults under variable speed and load is postulated. The methodology is trained using vibration signals from a single accelerometer mounted on the gearbox, simultaneously acquired with tachometer signals at a sample of working conditions (WCs) from the range of interest. A special parametric identification procedure of gearbox dynamics that may account for the continuous range of WCs is introduced through `clouds’ of advanced stochastic data-driven Functionally Pooled models, estimated from angularly resampled vibration signals. Each cloud represents the gearbox dynamics at a specific fault severity level, while the pseudo-static effects of the WCs on the dynamics are accounted for through data pooling. Fault detection and severity characterization are achieved by testing the consistency of a vibration signal with each model cloud within a hypothesis testing framework in which the unknown load is also estimated. The methodology is assessed through 18,300 experiments on a single-stage spur gearbox including four incipient single-tooth pinion faults, 61 speeds, and four load levels. The faults produce no significant changes in the time-domain signals, while their frequency-domain effects overlap with the variations caused by the WCs, rendering the diagnosis problem highly challenging. The comparison with a state-of-the-art deep Stacked Autoencoder (SAE) demonstrates the ML method’s superior performance, achieving 95.4% and 91.6% accuracy in fault detection and characterization, respectively. Full article

Under the premise of a certain damping layer volume, topological optimization design of its attach shape can enable a pipeline system to achieve optimal damping performance. This paper proposes a topology optimization method for vibration reduction in spatial pipelines with damping layers based on a finite element model. A parametric modeling approach is developed for the clamp-supported spatial pipeline with viscoelastic damping layer, and both clamp-support damping and damping layer material damping are considered. Using the progressive optimization method, an optimization model is established with the modal loss factor of the pipeline system as the objective function, the existence state of each damping layer element as the design variable, and the material volume as the constraint. Further, a case study is conducted. The correctness of the dynamic model is verified by hammer and frequency sweep tests. The optimization results indicate that retaining only 30% of the damping layer volume reduces weight by 70%, while vibration attenuation performance decreases by merely 2.46% compared to the fully coated configuration, demonstrating the effectiveness of the proposed topology optimization approach. Full article

Permanent magnet synchronous generators (PMSGs) are suitable for offshore applications due to their high efficiency and power density. Inter-turn short circuits (ITSCs) stand as one of the most critical faults in these machines due to their rapid evolution in phase or ground short circuits. It is therefore necessary to detect ITSCs at an early stage. In the literature, ITSC detection is often based on current signal processing methods. One of the challenges that these methods face is the presence of imperfections in the stator coils, which also affects the three-phase symmetry. Moreover, when the stator coils are connected in parallel, this type of fault becomes important, as circulating currents will flow between the parallel windings. This, in turn, increases the thermal stress on the insulation and the permanent magnets, while also exacerbating the vibrations of the generator. In this study, a finite-element analysis (FEA) model has been developed to simulate a dual-rotor PMSG under conditions of coil asymmetry. To further investigate the impact of this asymmetry, mathematical modeling has been conducted. For fault detection, negative-sequence current (NSC) analysis and torque monitoring have been used to distinguish coil asymmetry from ITSCs. While both methods demonstrate potential for fault identification, NSC induced small amplitudes and the torque analysis was unable to detect ITSCs under low-severity conditions, thereby underscoring the importance of developing advanced strategies for early-stage ITSC detection. The innovative aspect of this work is that, despite these limitations, the combined use of NSC phase-angle tracking and torque harmonic analysis provides, for the first time in a core-less PMSG with parallel-connected coils, a practical way to distinguish ITSC from coil asymmetry, even though both faults produce almost identical signatures in conventional current-based indices. Full article

Octachlorinated metal phthalocyanines (MPcCl₈, M = Co, Zn, VO) represent an underexplored class of functional materials with promising potential for chemiresistive sensing applications. This work is the first to determine the structure of single crystals of CoPcCl₈, revealing a triclinic (P-1) packing motif with cofacial molecular stacks and an interplanar distance of 3.381 Å. Powder XRD, vibrational spectroscopy, and elemental analysis confirm phase purity and isostructurality between CoPcCl₈ and ZnPcCl₈, while VOPcCl₈ adopts a tetragonal arrangement similar to its tetrachlorinated analogue. Thin films were fabricated via physical vapor deposition (PVD) and spin-coating (SC), with SC yielding highly crystalline films and PVD resulting in poorly crystalline or amorphous layers. Electrical measurements demonstrate that SC films exhibit n-type semiconducting behavior with conductivities 2–3 orders of magnitude higher than PVD films. Density functional theory (DFT) calculations corroborate the experimental findings, predicting band gaps of 1.19 eV (Co), 1.11 eV (Zn), and 0.78 eV (VO), with Fermi levels positioned near the conduction band, which is consistent with n-type character. Chemiresistive sensing tests reveal that SC-deposited MPcCl₈ films respond reversibly and selectively to ammonia (NH₃) and hydrogen sulfide (H₂S) at room temperature. ZnPcCl₈ shows the highest NH₃ response (45.3% to 10 ppm), while CoPcCl₈ exhibits superior sensitivity to H₂S (LOD = 0.3 ppm). These results suggest that the films of octachlorinated phthalocyanines produced by the SC method are highly sensitive materials for gas sensors designed to detect toxic and corrosive gases. Full article

Aluminum alloy 2024 (AA2024) is widely used in the aerospace sector, where a fine, uniform, and equiaxed grain structure is crucial for achieving enhanced mechanical properties. This study examines the effect of dynamic solidification, assisted by mechanical vibrations and conformal cooling, on the microstructural evolution and mechanical properties of permanent mold-cast AA2024. Mechanical vibrations were applied during solidification in the frequency range of 15–45 Hz and acceleration of 0.5–1.5 g. Process parameters, including pouring temperature, die temperature, vibration frequency, and acceleration, were optimized using an L9 orthogonal array based on the Taguchi method. Analysis of variance (ANOVA) was performed to determine the significance of the aforementioned process parameters. In addition, the alloy’s microstructure was observed through a microscope, which revealed a transition from dendritic to non-dendritic microstructure due to dynamic solidification. The average grain size of the alloy was significantly reduced by 40.9%. Moreover, the values of hardness and Ultimate Tensile Strength (UTS) of the alloy were improved by 13.5% and 10.6%, respectively. Optimal results were obtained at a pouring temperature of 750 °C, die temperature of 150 °C, frequency of 45 Hz, and acceleration of 1.0 g. Moreover, uncertainty analysis for all three responses was also performed. Full article