Search Results (1,156)

Low-frequency seismic disturbances significantly limit the performance of precision engineering systems and active vibration isolation platforms. Model predictive control (MPC) is widely applied in such systems due to its ability to handle multi-variable dynamics and constraints. However, its performance strongly depends on model accuracy. To address this issue, this paper proposes a multilayer perceptron-enhanced model predictive control (MLP-MPC) framework for active vibration isolation. In the proposed approach, a multilayer perceptron (MLP) is trained offline to learn the mapping between the current system state and the free-response term in the MPC prediction equation. During online implementation, the trained MLP replaces the model-based free-response calculation while preserving the original quadratic programming structure of conventional MPC. The proposed method is evaluated on a single-degree-of-freedom active vibration isolation system under low-frequency sinusoidal excitation and measured seismic disturbances. The simulation results show that MLP-MPC achieves reduced running RMS tracking error and lower moving-window RMS error compared with conventional MPC and Proportional–Integral–Derivative (PID) control. The results suggest that integrating data-driven free-response estimation into predictive control provides a practical approach to enhancing the performance of low-frequency vibration suppression while maintaining computational feasibility. Full article

The cantilever pick-and-place arm of the high-speed placement machine is susceptible to micro-vibration and elastic deformation under high-acceleration motion, thereby degrading chip placement accuracy. To address this issue, this paper presents an analytical study on the natural frequency characteristics and structural optimization of slender variable-cross-section rods. First, based on the thin-walled shell theory, a displacement field model of the thin-walled cantilever rod is established. Second, combining the energy method and Hamilton’s principle, the undamped free vibration equation is derived. Using the Rayleigh–Ritz method with Chebyshev polynomials as the basis functions, an analytical calculation model for the natural frequency of the variable-section thin-walled rod is constructed. The model is validated against finite element simulations, and the relative errors of the low-order natural frequencies are controlled within 5%, confirming its favorable accuracy and robustness. Furthermore, the four-factor three-level orthogonal experiment is designed with the objective of maximizing natural frequency to conduct parameters sensitivity analysis. Accordingly, the optimal structural parameter combination ϕ₃ = 8 mm, L₁ = 10 mm, L₂ = 50 mm, and L₃ = 5 mm) is determined. Finally, the maximum dynamic deformation under high-acceleration motion decreases from 0.066 mm to 0.021 mm, a reduction of 68.2%, which effectively suppresses residual vibration and end displacement deviation. The analytical method proposed in this study provides a theoretical basis for the rapid dynamic performance evaluation of flexible components in high-speed precision equipment, and the optimization strategy can offer engineering references for the high-stiffness design of key components in chip placement machines. Full article

Bearing fault diagnosis is an important task for condition monitoring and predictive maintenance of rotating machinery. Nevertheless, many existing deep learning-based methods have difficulty in jointly modeling multi-scale fault characteristics, adaptively highlighting informative features, and maintaining robustness under noisy measurement conditions. To address these issues, this study presents MDCAD-Net, a multi-dilated convolution attention denoising network that integrates multi-scale temporal feature extraction, attention-based feature refinement, and explicit noise suppression within an end-to-end learning framework. Parallel dilated convolutions with different dilation rates are employed to capture short-duration transient impulses as well as long-range periodic patterns in vibration signals. Channel-wise feature recalibration using squeeze-and-excitation networks and spatial-temporal attention via a convolutional block attention module are combined to enhance informative representations. In addition, a denoising block with gated attention and residual connections is introduced to reduce noise interference while retaining fault-related signal components. Experiments conducted on the Case Western Reserve University bearing dataset show that the proposed method achieves a classification accuracy of 98.93% and yields competitive performance compared with several commonly used deep learning models. Ablation studies and feature visualization results further illustrate the contributions of the individual components and the separability of the learned feature representations under noisy conditions. The results indicate the potential of the proposed framework for practical bearing fault diagnosis under noisy operating conditions. Full article

To address the polarization fading noise in coherent detection phase-sensitive optical time-domain reflectometry (Φ-OTDR) for distributed low-frequency vibration sensing, a Φ-OTDR sensing scheme integrating polarization diversity reception and the variational mode decomposition (VMD) algorithm is proposed. The mechanism of polarization fading induced by fiber birefringence and external perturbations is systematically analyzed. A signal–noise mathematical model for polarization diversity reception is established, and the adaptive decomposition capability of the VMD algorithm for non-stationary phase signals is elaborated. This scheme can accurately separate the additional noise introduced by polarization diversity reception from the target low-frequency vibration signals. Experimental results demonstrate that, compared with the single-path detection scheme, the proposed method eliminates the amplitude attenuation of beat frequency signals caused by polarization mismatch at the optical path level. Meanwhile, it effectively suppresses both the additional noise introduced by polarization diversity and the low-frequency phase drift resulting from unstable laser frequency. It achieves precise phase restoration of vibration signals excited at 50 Hz under three typical sensing distances of 5 km, 10 km, and 30 km. Additionally, it successfully restores low-frequency vibration signals as low as 0.6 Hz at the sensing distance of 30 km. Full article

This study investigates the hydrodynamic characteristics of single-layer heave plates with varying salient edges and triple-layer configurations with size mismatches under forced oscillation, utilizing 3D overset mesh numerical simulations. For single-layer plates, the 0° edge configuration maintains high hydrodynamic coefficients across all conditions, whereas the 135° edge peaks under specific parameters. Introducing horizontal gaps consistently degrades performance. For triple-layer plates, increasing the spacing ratio mitigates spatial flow interference, significantly enhancing hydrodynamic coefficients. Furthermore, introducing size differences creates a stepped mismatched configuration that effectively mitigates wake shielding and enhances fluid entrainment. Consequently, the coefficients increase steadily with the absolute size difference, reaching optimal heave suppression in the triple-layer arrangement with a large spacing and a ±20 m size mismatch. Finally, a highly accurate empirical formula (R² > 0.92) is proposed to predict the damping (C_d) and added mass (C_a) coefficients, effectively capturing the nonlinear coupling effects of spacing ratio and size difference. These findings provide practical theoretical guidance for optimizing vibration reduction systems in offshore platforms. Full article

The fuel consumption of power-split hybrid electric vehicles (PSHEVs) can be effectively reduced via mode transition that includes the engine process. However, factors such as engine torque ripple, system parameter uncertainties, and variations in torsional vibration characteristics can easily induce drivetrain vibration. These factors not only degrade ride comfort but also lead to a fundamental control challenge. The inherent trade-off between rapid response and stability is difficult to reconcile. In addition, the lack of adaptive mechanisms further limits consistent performance under varying conditions. To tackle these problems, a scenario-adaptive composite robust control (SACRC) strategy is proposed. The strategy consists of a UIO (unknown input observer)-based torque observation module, an adaptive VSS-LMS approach, and an H∞ controller with self-tuning parameters. Firstly, a six-degree-of-freedom dynamic model of the PSHEV transmission system is established with excitation sources, considering the characteristics of dual elastic elements. Secondly, a UIO-based torque observer is designed using a simplified dual-elastic-element model. By using engine speed and output shaft speed, the observer can accurately identify the torque transmitted by the torsional damper and drive shaft. Then, an adaptive VSS-LMS and H∞ controller with self-tuning parameters is constructed to ensure a balanced performance between fast torsional vibration suppression and control stability. Finally, simulation and experimental results demonstrate that the proposed strategy provides favorable adaptability to complex scenarios, and unifies the performance goals of rapidity, stability, and robustness. Full article

Deep-sea mining systems are a critical pathway for acquiring key strategic resources such as nickel and cobalt. The core conveying component, the mining rigid pipe, is susceptible to transverse vibrations under complex wave excitation, which threaten system safety, necessitating the development of efficient and reliable vibration control solutions. This paper proposes an improved Triple-spring nonlinear energy sink (TS-NES). An integrated dynamic model coupling the mining rigid pipe and the TS-NES is established using the vector form intrinsic finite element method and solved via the central difference method. The effectiveness and superiority of the TS-NES are verified through displacement, time–frequency, energy, and phase analyses. Subsequently, a systematic parameter sensitivity study is conducted. The results indicate that under both single-frequency and multi-frequency wave excitations, the TS-NES exhibits broadband, high-efficiency vibration suppression performance superior to that of the conventional tuned mass damper (TMD). It can substantially and uniformly dissipate vibration energy and maintain an approximately 90° phase lag with the primary structure. Parameter studies reveal that installing the TS-NES in the upper section of the pipe yields significant vibration reduction. The device is insensitive to stiffness variations, and appropriately increasing its mass, damping, and inclination angle can further enhance the vibration suppression effect. Full article

Cardiovascular diseases are the primary causes of mortality worldwide, often characterized by subtle onset and acute progression. Traditional ECG electrodes may cause skin irritation, limiting routine monitoring and early risk assessment. Relying on the advantages of non-contact monitoring, millimeter-wave radar-based cardiac monitoring combined with deep learning has become a popular research direction recently. To overcome the poor generalization of methods trained from single-source datasets, this study designed seven experimental scenarios covering wakefulness and sleep. A novel deep learning network consisting of encoder and decoder structures named PMG-SATNet was proposed. The encoder comprises a parallel multi-scale feature extraction module and a global temporal relationship modeling module to capture fine-grained local patterns and long-range dependencies. The decoder employs a temporal convolutional network augmented with a spectral attention mechanism to emphasize clinically relevant ECG frequency bands and suppress respiration and body motion interference. After being validated on the self-built dataset, PMG-SATNet outperformed baseline models in terms of Pearson correlation coefficient and root mean square error, with an improvement of 3.3% and 3.8%, and 16.4% and 23.8%, respectively. The validation results imply that PMG-SATNet is capable of recovering ECG signals from millimeter-wave radar-derived chest vibrations with high fidelity and can potentially be implemented in real-life cardiac health monitoring. Full article

First-principles calculations based on density functional theory (DFT) are a powerful tool in data-oriented materials research. The choice of approximation for the exchange-correlation functional is crucial, as it strongly affects the accuracy of DFT calculations. This study compares the performance capabilities of three approximations on the energetics, mechanical and electronic properties, and crystal structure of NaAlP₂O₇, which is an insulator with a wide band gap that suppresses its electronic conductivity. Two of these approximations are based on Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation (GGA) and the other on the strongly constrained and appropriately normed (SCAN) meta-GGA. We explore these materials as a contribution to the development of new solid electrolytes (SEs) for sodium-ion batteries (NIBs), which have the potential to mitigate challenges related to lifecycle, safety, and low ionic conductivity. The performance of these batteries largely emanates from the extraordinary demand for high-performing energy storage technologies. This study revealed that PBEsol accurately predicted lattice parameters that closely aligned with experimental values. However, r2SCAN provided the most reliable predictions of the structural and electronic properties of the NaAlP₂O₇ solid electrolyte compared to PBE and PBEsol. Findings demonstrated that the material is structurally, mechanically, electronically, and thermodynamically stable, but exhibits vibrational instability, which may scatter ions and reduce ionic conductivity due to the presence of imaginary frequencies. Our results highlight the importance of selecting appropriate functionals for solid electrolyte DFT computations. The r2SCAN functional appears to be a promising choice for calculating NaAlP₂O₇ properties. Full article

Indoor speech propagation causes minute vibrations in surrounding objects, enabling remote speech recovery through passive eavesdropping. Unlike traditional methods that rely on acoustic waves, passive eavesdropping uses object vibrations, making it difficult to defend against, even in soundproof environments. However, weak vibration signals and noise interference make speech recovery challenging. Existing studies mainly focus on deep learning for signal reconstruction, requiring large datasets and high computational power, which complicates real-time, on-device deployment. To address this, we propose a lightweight passive speech recovery system based on millimeter-wave radar. Without prior knowledge of object locations or numbers, the system can adaptively fuse multi-source signals for real-time speech reconstruction. To counteract the noise characteristics of millimeter-wave radar and the weak amplitude of vibration signals, we designed a set of low-complexity noise suppression and signal enhancement algorithms, ensuring efficient operation on edge devices. Experimental results demonstrate that in single-target scenarios, the proposed system achieved a Mel Cepstral Distortion (MCD) of 3.923 and a Word Error Rate (WER) of 12.9%. In multi-target scenarios, the SNR improved by 3.65 dB, MCD decreased by an average of 1.52, and WER decreased by an average of 15.83%, making the method effective and practical in complex acoustic environments. Full article

Rolling bearings operate under complex contact conditions, and their tribological and dynamic behaviors are highly sensitive to their lubrication performance. Based on previous studies on surface texturing, three types of representative textures (wholly distributed dimples, locally distributed dimples, and grooves) with optimized parameters were fabricated on the shaft washers using the laser marking method. This was done to investigate the synergistic effect of surface textures and polytetrafluoroethylene (PTFE) nano-additives on the tribological and friction-induced vibration performance of cylindrical roller thrust bearings under starved lubrication. Lubricating oils containing various mass fractions (0.5 wt%, 1.0 wt%, and 3.0 wt%) of PTFE nano-additives were prepared and employed. The coefficients of friction (COFs), wear losses, worn morphologies, and time/frequency-domain vibration responses were analyzed. The results show that the appropriate integration of surface textures and solid lubricant additives can establish a highly effective synergy for rolling bearings under starved lubrication. PTFE nano-additives significantly improved the tribological performance of the smooth bearings and those with dimples (both wholly distributed and locally distributed), with the optimal performance observed at a mass fraction of 3.0 wt%. In contrast, the tribological performance of the groove-textured bearings noticeably deteriorated with the addition of PTFE nano-particles, especially at higher mass fractions. The bearing with wholly distributed dimples exhibited the best overall tribological performance at a mass fraction of 3.0 wt%, achieving a 61.8% reduction in the average COF, a 99.6% reduction in wear loss, and significantly suppressed vibration amplitudes. Full article

Flexible circular shafts are critical components for power transmission in engineering systems. However, they are susceptible to complex three-dimensional coupled vibrations under multidirectional excitations, which can compromise operational stability and lead to structural fatigue. To address this issue, this paper presents an active control method for the three-dimensional vibration of a piezoelectrically driven flexible circular shaft via a fuzzy adaptive PID algorithm. The study begins by establishing a dynamic model of the system based on the Euler–Bernoulli beam theory and Lagrange equation. This model forms the foundation for the design of a fuzzy adaptive PID controller. The accuracy of the developed model is then validated through simulations and experiments. Subsequently, active vibration control (AVC) experiments are carried out to evaluate the vibration attenuation effectiveness of various control strategies (including a conventional PID controller as the benchmark for comparison) under different types of excitations applied at the shaft root. The results demonstrate that the proposed active control method has superior control performance, and exhibits excellent vibration suppression performance, especially under bidirectional excitation at the natural frequency, where the vibration suppression ratios in the two orthogonal directions reach 93.03% and 92.09%, respectively. Full article

Reliable multi-sensor bearing fault diagnosis is challenged by temporal leakage caused by window-level random splitting, limited modeling of cross-sensor dependencies, and inadequate integration of raw temporal dynamics with time-frequency representations. To address these issues, this study proposes a leakage-resistant multi-sensor diagnosis framework that combines a partition-before-windowing evaluation protocol with adaptive time-frequency graph learning and reliability-aware fusion. Continuous vibration records are first divided into disjoint temporal regions with guard intervals and overlap auditing to suppress time-neighbor leakage. The model then extracts complementary features from a raw-signal branch and a dual-resolution log-STFT branch, while adaptive graph learning captures sample-dependent inter-sensor couplings and sensor reliability weighting highlights informative channels. A cross-gated fusion module further integrates temporal and graph-domain representations in a sample-adaptive manner for final classification. Experiments on a reconstructed nine-class benchmark derived from the HUSTbearing dataset show that the proposed method achieves a Macro-Accuracy of 0.973, a Macro-Recall of 0.964, and a Macro-F1 of 0.954, outperforming representative raw-signal and STFT-based baselines under the same leakage-resistant protocol. These results demonstrate that jointly modeling multi-scale time-frequency structure, dynamic sensor relationships, and reliable evaluation yields an effective and interpretable solution for intelligent bearing fault diagnosis under complex operating conditions. Full article

The overall swing dynamics of rigid slender payloads lifted in a vertical orientation deviate significantly from the ideal point-mass pendulum model, leading to severe performance degradation of feedforward control strategies designed based on this simplified model. This paper focuses on the bridge crane system and establishes a double-pendulum dynamic model that accounts for the payload’s mass distribution effect. To compensate for the theoretical error of the linearized model, a data-driven payload swing frequency correction strategy is proposed. Based on this corrected model, a dual-mode Zero Vibration Derivative (Corrected-Dual-ZVD) input shaping feedforward controller is designed. Simulations under eight typical operating conditions were conducted using the Matlab/Simulink control system simulation software. The results show that compared to the controller designed based on the traditional single-pendulum model, the proposed Corrected-Dual-ZVD controller, based on the corrected double-pendulum model, can significantly reduce the maximum residual swing angle of the payload. The average swing angle suppression rate reaches 68.9% across seven valid operating conditions, and it can reach 98.9% under the extreme condition of high speed and short rope length. When model parameters are subjected to ±10% disturbances, the proposed method demonstrates good robustness. Full article

To address severe mine pressure disasters induced by the coupling of mining-induced dynamic stress and impact disturbance during close-distance coal seam mining, this paper takes the No. 8 and No. 9 close-distance coal seams in the 119 mining area of a coal mine in Ningxia, China, as the engineering background. Theoretical analysis and FLAC^3D numerical simulation methods were adopted to systematically study the evolution of overburden structure, the manifestation law of mine pressure caused by mining disturbance, and the dynamic response mechanism of roadway surrounding rock under impact load. The findings demonstrate: ① Based on key block theory and elasticity mechanics theory, the stress transfer mechanism of the complete bearing type overburden rock in close-range coal seams was clarified. The calculation model of floor plastic zone depth and additional stress was derived, and the influence mechanism of the bearing state of interlayer rock strata on the stability of underlying coal seam roadways was revealed. ② Comparative numerical simulations of mining schemes revealed that both schemes formed a “goaf pressure relief-workface-coal pillar” load-bearing configuration with “upward subsidence and downward bulging” basin-shaped settlement. Scheme A exhibited significantly increased stress peaks and interlayer plastic zones due to repeated mining-induced stress, substantially elevating the risk of strong mine pressure manifestation and surrounding rock instability. ③ Under 8 MPa cosine impact load with a vibration frequency of 50 Hz (peak particle vibration velocity of 9.57 m/s), compared with the unsupported roadway, the bolt–cable collaborative support system reduced the peak displacement of surrounding rock by over 35% and decreased the shock wave propagation velocity by more than 40%, effectively suppressing the expansion of plastic zones and the transfer of impact energy, while significantly enhancing the impact resistance of the roadway. This study not only provides a systematic theoretical basis for close-distance coal seam mining and rock burst prevention but also offers scientific guidance and technical reference for surrounding rock control and dynamic disaster prevention of roadways in similar close-distance coal seam mining projects, which is of important engineering value for ensuring the safe and efficient mining of underground coal resources. Full article