Vibration Patterns Research Articles

MIX DESIGN AND LABORATORY COMPACTION METHODS OF RCCP – A REVIEW

This article analyzes the difficulties in reproducing the actual circumstances of concrete compaction with rollers in the laboratory and mix design аfeatures of RCCP (Roller Compacted Concrete Pavement). While quick and straightforward, the Proctor compaction test may not adequately reflect the field compaction achieved with rollers. Gyratory compactors simulate the movement of the rollers, providing a more realistic situation with greater accuracy. However, they are expensive and require specialized knowledge. Due to the Vibratory hammer limited application and unrealistic vibration pattern compared to rollers, it is mostly used in laboratories for sample preparation rather than compaction. A vibrating table is effective for less rigid RCC mixture combinations and provides good compaction, although it does not perfectly simulate the action of a roller. The paper also underlines the need to create a link between density and moisture content to achieve maximum RCC performance.

A Study on the Attenuation Patterns of Underground Blasting Vibration and Their Impact on Nearby Tunnels

The natural caving method, as a new technique in underground mining, has been promoted and applied in several countries worldwide. The destruction of the bottom rock mass structure directly impacts the structural stability of underground engineering, resulting in damage and collapse of underground tunnels. Therefore, based on the principles of explosion theory and field monitoring data, a scaled three-dimensional numerical simulation model of underground blasting was constructed using LS-DYNA19.0 software to investigate the attenuation patterns of underground blasting vibrations and their impact on nearby tunnels. The results show that the relative error range between the simulated blasting vibration velocities based on the FEM-SPH (Finite Element Method–Smoothed Particle Hydrodynamics) algorithm and the measured values is between 7.75% and 9.85%, validating the feasibility of this method. Significant fluctuations in blasting vibration velocities occur when the blast center increases to within a range of 10–20 m. As the blast center distance exceeds 25 m, the vibration velocities are increasingly influenced by the surrounding stress. Additionally, greater stress results in higher blasting vibration velocities and stress wave intensities. Fitting the blasting vibration velocities of various measurement points using the Sadovsky formula yields fitting correlation coefficients ranging between 0.92 and 0.97, enabling the prediction of on-site blasting vibration velocities based on research findings. Changes in propagation paths lead to localized fluctuations in the numerical values of stress waves. These research findings are crucial for a deeper understanding of underground blasting vibration patterns and for enhancing blasting safety.

Longitudinal dynamic behavior study of a vibrating rod connected through an elastic nonlinear single degree freedom coupler

This research explores the efficacy of integrating nonlinear single-degree-of-freedom systems in the vibration control of rod coupling systems. By interlinking two rods with a nonlinear single-degree-of-freedom system as the intermediary, the study employs the Lagrange method (LM) to forecast nonlinear vibrational behaviors. The findings, substantiated by numerical analyses, affirm the precision of LM in gauging the amplitude responses when such a nonlinear system is utilized. The nonlinear dynamics, characterized by intricate vibrational patterns, peak jumping phenomena, and the migration of resonance zones, are induced by the nonlinear single-degree-of-freedom system. By fine-tuning the system’s parameters, significant alterations in the vibrational states of the rod coupling system are achievable. This suggests that the application of a nonlinear single-degree-of-freedom system is a viable strategy for modulating vibrations in rod systems. Furthermore, optimal parameterization of this system is proven to effectively dampen vibrations, showcasing its potential as a sophisticated mechanism for vibration suppression in coupled rod configurations.

Research on Damage Detection of Dual-Rotor Synchronous Excitation Mine Screen Beams Based on Strain Mode Difference Vibration Mode Analysis

The frame beam structure of the mine screen, subjected to various excitations, is a critical component of mining machinery. Its stress is intricate, the operational environment is severe, and damage can lead to catastrophic failures resulting in machinery destruction and fatalities. Based on the characterization of the vibration response of mine screen frame beams with varying degrees of damage at the same location and with the same degree of damage but at different locations, this paper develops a method of strain modal difference vibration pattern analysis and damage feature extraction for the detection of structural damage in beams. This method is based on the sensitivity of the sudden change in vibration strain modal difference to small deformations. This method solves the problem of using the conventional structural finite element analysis or experimental modal analysis methods to obtain the displacement mode, intrinsic frequency, and other characteristics, which make it difficult to effectively identify the actual engineering, with the damage conditions of the damage state and damage location of the mine screen frame beam problems. The feasibility and validity of the engineering application of the concept are demonstrated through instances.

Dynamic Unbalance Identification in Steady-State Rotating Machinery: A Hybrid Methodology Integrating Physical and Data-Driven Techniques

Rotating machinery plays a strategic role in key industrial sectors, making its analysis a subject of great interest for both academia and industry. Effective maintenance planning for this equipment is essential for asset management and for meeting current industrial requirements. To address this demand, this work presents a novel unbalance identification approach based on a digital representation of a rotating machine's dynamic behavior in relation to the development of specific faults. A hybrid methodology is proposed, integrating Finite Element Modeling, a Kalman Filter for parameter estimation, and Referenced Moving Window Principal Component Analysis. This Principal Component Analysis extension enhances vibration pattern recognition, enabling accurate fault quantification directly from slight changes in the system's steady-state behavior. The methodology uniquely eliminates the need for phase angle measurements, facilitating continuous monitoring of unbalance progression in steady-state conditions. Two case studies demonstrate the methodology's potential: one utilizing synthetic data from a Floating Production Storage and Offloading centrifugal compressor unit, and the other based on real data from a hydroelectric turbine-generator. These studies illustrate the integration of computational modeling, data-driven analysis, and monitored vibration data, achieving robust and accurate unbalance identification. This approach provides valuable insights into current capabilities and opens promising pathways for future applications, particularly in the digital twin domain for rotating machinery.

A low-cost prosthetic arm with real-time haptic feedback and gesture control for enhanced user autonomy

In daily life, manipulating and feeling objects is essential for autonomy and engagement in various activities. However, individuals relying on prosthetic limbs often encounter barriers such as high costs, ineffective feedback, and limited design adaptability. Unlike conventional prosthetic limbs, which frequently struggle to integrate seamlessly and provide intuitive control, the robotic arm outlined in this study represents a leap in functionality and user experience. At the core of its design lies a specialized glove outfitted with a calibrated array of flex-sensing resistors capable of precisely detecting and interpreting the wearer's movements. These sensors input to the robotic arm, translating the user's gestures into motions that follow human hands. The fingertips are equipped with force-sensing resistors to discern the magnitude of force applied during gripping actions. This real-time sensory feedback is conveyed to the user through a haptic system integrated into the glove. By modulating the intensity and pattern of vibrations, users can gauge their grip strength and manipulate their grasp of the object accordingly. Comprehensive experiments were conducted across various scenarios to assess its performance, agility, strength, and sensory accuracy. Through refinement, the author aims to optimize functionality and reliability, enhancing practicality for users. This project has broader implications for the prosthetics community. By utilizing the scalability and cost-effectiveness of this model, the author envisions tailored solutions that empower individuals with limb differences to live more independently.

Finite element analysis on the human and guinea pig cochlear vibration patterns under bone conduction stimulations

To compare the vibrational patterns of human and guinea pig cochleae accurately, we developed and validated a novel finite element model of the guinea pig, leveraging it to analyze vibrational patterns in the cochlea. This approach is mirrored in our examination of the human cochlear model, providing granular insights into the nuances of human bone conduction hearing. The comparative analysis reveals that the guinea pig cochlea mirrors human cochlear vibrational patterns, thus serving as an efficient proxy for exploring human cochlear function. The human mastoid and the upper region of the guinea pig’s skull are recommended as the convenient and comparable sites for bone conduction stimulation. The cochlear vibration pattern encompasses a mix of rigid, rotational, and compressive motion. Significantly, the guinea pig model demonstrates robust agreement with existing experimental data and other studies, these findings are confirming the validity of the model. Our study delineates the distinct roles of the three vibration types across various frequency spectrums. At lower frequencies, rigid motion is the dominant mechanism, supplemented by rotational motion. However, at higher frequencies, the influence of rigid motion wanes, ceding prominence to rotational and compressive motions. This trend is consistently observed in both human and guinea pig models.

Effect of ultrasound power on moisture status change of apple by contact ultrasound reinforced far-infrared radiation drying

To explore the effect of ultrasound power on internal water change of apple dried by contact ultrasound enhanced far-infrared radiation drying (CUFRD), the drying characteristics, microstructure, moisture migration, and molecular vibration patterns of apple slices subjected to this process at different ultrasound powers were investigated using low-field nuclear magnetic resonance (LF-NMR), Near-infrared (NIR) and two-dimensional(2D) correlation analysis. With the increase of contact ultrasound (CU) power, the drying times of apple were shortened by 8.69% to 17.39%, respectively. Scanning electron microscopy (SEM) observation indicated that higher CU power resulted in an increase in the number of microporous channels and pore diameter within apple’s internal tissue. The findings of LF-NMR clarified that free water content kept decreasing, while the content of semi-bound water initially increased and then reduced. Magnetic resonance imaging (MRI) images illustrated that higher CU power corresponded to a faster decrease in the redness value of the H+ density map of apple during drying. 2D correlation analysis revealed that the changes in the O-H bonds of apple were prioritized over the C-H bonds during drying process. NIR spectroscopy and LF-NMR heterogeneous correlation spectrograms demonstrated that at wavelengths of 950, 1450, and 1680 nm, the order of changes in water-related functional groups was quadruple-frequency O-H > combination of the first overtone of O-H stretching and OH-bending band > double-frequency C-H. Moreover, with increasing CU power, the vibration of hydrogen-containing functional groups intensified, leading to increased water activity. Thus, CU application could significantly enhance the CUFRD process of apple slices.

Processing the fine-grained features of tactile textures involves the primary somatosensory cortex

Abstract Dynamic tactile perception and discrimination of textures require the ability to encode and differentiate complex vibration patterns elicited at the level of the skin when sliding against a surface. Whether the primary somatosensory cortex (S1) can encode the fine-grained spectrotemporal features distinguishing textures remains debated. To address this question, EEG frequency-tagging was used to characterize responses to vibrotactile oddball contrasts between two textures. In a first session designed to identify the topographical distribution of responses originating from the hand and foot representations in S1, standard and deviant stimuli were pure sinusoidal vibrations differing in frequency and intensity. In a second session, standard and deviant stimuli were two different snippets of bandpass-filtered white noise matched in terms of intensity and average frequency content, but differing in terms of their complex spectrotemporal content. Using the S1 functional localizer, we showed that oddball responses to a spectrotemporal contrast follow the somatotopical organization of S1. Our results suggest that the encoding of fine-grained spectrotemporal features associated with different vibration patterns involves S1.

Design of lightweight aircraft trim panel with a high sound transmission loss

The trim panels of aircraft cabin are frequently made up of multilayer materials including a honeycomb, typically in the form of sandwich panels, which have the advantage of being lightweight and space-saving, but lack good acoustic insulation. It has been shown that, for 10% more mass, weights arranged in a fractal pattern in the honeycomb affect the vibratory pattern of a sandwich panel by creating multiple reflections of the bending waves on the inclusions. They thus generate a phenomenon of focusing vibratory waves providing localized modes while attenuating the structure's acoustic radiation. The objectives of this paper are to describe: first, the vibro-acoustic model of an overloaded homogenized bending panel (to mimic a trim panel with a fractal pattern); second, the physical phenomena associated to this concept; third, the impact on the modal behavior and the vibratory and acoustic responses.

Nonlinear vibration and parametric excitation of magneto‐thermo elastic embedded nanobeam using homotopy perturbation technique

AbstractThe present study focuses on the modeling and analyzing the nonlinear vibration patterns and parametric excitation of embedded Euler–Bernoulli nanobeams subjected to thermo‐magneto‐mechanical loads. The Euler–Bernoulli nanobeam is developed with external parametric excitation. The governing equation of motion is derived by utilizing nonlocal continuum theory and nonlinear von Karman beam theory. Subsequently, the homotopy perturbation technique is employed to determine the vibration frequencies. Finally, the modulation equation of Euler–Bernoulli nanobeams is derived for simply supported boundary condition. In order to validate our findings, we conduct a comparative analysis against existing literature, thereby underscoring the effectiveness and robustness of our proposed methodology. The influence of stress, magnetic potential, temperature, damping coefficient, Winkler coefficient, and nonlocal parameters are tested numerically on nonlinear frequency‐amplitude and parametric excitation–amplitude responses. The numerical examples indicate the significant impact of physical variables on the nonlinear frequency and parametric excitation. The primary objective of this study is to investigate the effects of external physical variables on the dynamic behavior of nanobeams, particularly in nonlinear regimes. This study provides insights into the design and control of nanostructures under complex load conditions, contributing to developing advanced materials and nanosystems.

Prediction of approaching trains based on H‐ranks of track vibration signals

AbstractThis paper introduces a method for forecasting the arrival of trains by analyzing track vibration signals. The proposed algorithms, based on H‐ranks of track vibration signals, can generate early alerts for approaching trains. These algorithms are robust to additive noise and environmental conditions. The theoretical foundation of the method involves the application of matrix operations to detect significant changes in vibration patterns, indicating an approaching train.

Dynamic characteristics of a horizontal rectangular vessel partially or fully filled with a fluid

A theoretical framework is presented for free vibration of a flexible horizontal rectangular vessel, whether it is partially or fully filled with a fluid. The vibrational modal patterns of the vessel, whether dry or wet, are classified into symmetric and antisymmetric modes. The theoretical model conceptualizes the vessel as an unfolded plate with line supports simulating the vessel's corners. The motion of contained fluid is described using displacement potentials that adhere to the Laplace equation and fluid boundary conditions. Importantly, the proposed analytical approach accounts for the dynamic interaction between the vessel and the fluid, ensuring compatibility along their contacting surfaces. The Rayleigh-Ritz method is employed to formulate an eigenvalue problem, considering entire kinetic and strain energies of the fluid-filled vessel. The accuracy of the theoretical approach is checked by conducting finite element analyses. Remarkably, the natural frequencies obtained through commercial software align closely with the theoretical predictions for both dry and fluid-filled vessels. In instances of fully fluid-filled vessels, we can discern the presence of fluid contact at the vessel's upper plate by examining the natural frequencies and mode shapes. The proposed method offers applicability in dynamically analyzing water-filled spent fuel casks, enhancing safety during transportation.

A multiscale Gaussian expansion method for low-frequency multimodal damping analysis of variable stiffness acoustic black hole beams

To address the issues of slow convergence and poor accuracy in existing dynamics methods caused by non-uniform variable cross-sections and layered material stiffness variations in variable stiffness acoustic black hole structure (VSABH). A multiscale Gaussian expansion method (MSGEM) is proposed in this paper. The structural dimensions are taken into account, and the structural parameters of multiple shape functions are adaptively selected based on stiffness and cross-sectional variation parameters. This results in the formation of shape function groups of various scales, which in turn creates the matrix of multi-scale Gaussian function groups. The feature information of the displacement field is realized to be extracted from multiple scales, and the fitting error of MSGEM to the displacement field of VSABH beam is within 2.02%. The missing solution of eigenfrequency of Gaussian expansion method is avoided, and the modal vibration patterns are basically matched, which verifies the validity of MSGEM. Meanwhile, the advantages of low-frequency multimodal vibration reduction of VSABH beams are highlighted from several aspects, and the trend of the adjustment of the vibration reduction characteristics of VSABH beams by different parameters is clarified, which provides valuable design guidance for ABH metamaterials oriented to low-frequency vibration reduction.

Wind turbine foundation ring fatigue reliability analysis under wind-load using SCADA system

Under the action of wind load, the foundation ring of the fan will generate stress concentration and alternating stress, leading to fatigue failure. Based on the average wind speed obtained from the supervisory control and data acquisition (SCADA) system, the orthogonal expansion method of random pulsating wind field and the number theory point selection method are used to calculate and simulate the corresponding pulsating wind speed time series, and then calculate the wind speed time series and wind load time series. Based on the ABAQUS finite element software, a model of a 5 MW wind turbine is established. The modal analysis is used to obtain the modal vibration pattern and the intrinsic frequency to verify the reasonableness of the structural modeling. Subsequently, the wind load time series is applied to the wind turbine model to obtain the stress time series using instantaneous modal dynamic analysis (Modal dynamics). The stress time series at the location of maximum stress concentration in the foundation ring is extracted, and the stress time series with the same stress amplitude is obtained through conversion, which has Wiener characteristics. After obtaining the stress amplitude using the rainflow counting method, the fatigue reliability is calculated based on the structural fatigue reliability analysis method considering the threshold crossing duration of the random process. This research holds reference significance for the calculation of fatigue reliability under approximate working conditions.

Further Study of Music Visualization: Chladni's Figure

By applying the principle of standing waves, the various scales produced by a piano within music software can be transformed into Chladni figures. These figures, which visually represent the vibration patterns of a surface, can be captured using photographic equipment. By carefully selecting the most accurate patterns and organizing them into a comprehensive table, it is possible to create a visual representation of Chladni figures corresponding to each musical syllable. This method provides a unique way to visualize the acoustic characteristics of different musical notes.

Free Vibration of Carbon Nanotube Reinforced Functionally Graded Shells

The main objective of this research is to investigate the vibration patterns of cylindrical panels composed of epoxy composites containing functionally graded Multiwall Carbon Nanotube (FG MWCNT). The research specifically addresses the issue of resonance failure, which is common in lightweight polymer composite structures that are subjected to dynamic forces. Curved components used in aircraft, automobiles, and marine vehicles, i.e. curved panels, conical shells, open shells and circular cylindrical shells, are particularly susceptible to this type of failure. The ANSYS software was used to consider three different types of uniaxial reinforcement distribution for modelling cylindrical panels made of FG-MWCNT epoxy composites. The extended rule of mixture of a micromechanical model is employed to determine the distribution of carbon nanotubes transversely the thickness of the structure, utilizing effective parameters. The research examines the impact of various geometrical considerations, such as the volume fraction of carbon nanotubes (CNTs),length to thickness ratio and boundary conditions on the analysis of vibration of the shell structure. The outcomes obtained from the suggested Finite Element Method (FEM) are obtainable to validate the performance and usefulness of the model.

Thermoelastic damping properties in hemi-ellipsoidal shells with variable thickness

Thermoelastic damping (TED) is a fundamental dissipation mechanism that inevitably exists in shell resonators with high quality factors. Based on the thermal energy method, this paper demonstrates an effective method for the TED characterization of the hemi-ellipsoidal shells with variable thickness which manifest lower TED compared with the hemispherical shells. The equation of motion of the hemi-ellipsoidal shell under clamped-free boundary conditions is established by Hamilton's principle and the assumed mode method, and the natural frequencies and mode shape functions of the hemi-ellipsoidal shell with variable thickness are obtained by solving the eigenvalue problem. The temperature field is acquired by solving the heat conduction equation along the radial direction, and an analytical model for the TED of the hemi-ellipsoidal shell with variable thickness is presented by calculating the maximum elastic potential energy and the work lost per cycle of vibration due to irreversible heat conduction. Analysis on TED at the vibration patterns of meridional wave number m = 1 and the circumferential wave number n = 2 or 3 where the shell resonators typically operate is carried out. The analytically calculated TED results are compared with those of the finite element method (FEM) to verify the feasibility and correctness of the present method. The influences of the geometrical parameters on the TED characteristics of the hemi-ellipsoidal shells with variable thickness are analyzed in detail. A meaningful discovery is that compared with the hemispherical shell, the hemi-ellipsoidal shell with variable thickness has a smaller TED when its semiminor axis is shorter than the semimajor axis, which is particularly significant for optimizing the design of the shell resonators with high quality factors.

Infrared Spectra Prediction for Functional Group Region Utilizing a Machine Learning Approach with Structural Neighboring Mechanism.

Infrared (IR) spectroscopy is a pivotal technique in chemical research for elucidating molecular structures and dynamics through vibrational and rotational transitions. However, the intricate molecular fingerprints characterized by unique vibrational and rotational patterns present substantial analytical challenges. Here, we present a machine learning approach employing a structural neighboring mechanism tailored to enhance the prediction and interpretation of infrared spectra. Our model distinguishes itself by honing in on chemical information proximal to functional groups, thereby significantly bolstering the accuracy, robustness, and interpretability of spectral predictions. This method not only demystifies the correlations between infrared spectral features and molecular structures but also offers a scalable and efficient paradigm for dissecting complex molecular interactions.

Segmentalized amplitude normalization in feature extraction technique for diagnostics enhancement of bearing deterioration under varying speeds

This research investigated the feasibility of applying hardware order-tracking (HOT) and segmentalized amplitude normalization (SAN) to enhance the diagnosis of multiple bearing defects at different levels under varying rotation speeds. The vibration of operating bearings may present an energy variation phenomenon due to different levels of bearing defects, while the fluctuation of vibration amplitude may be attributable to changes in rotation speeds. These two factors inevitably interfere with each other when diagnosing bearing defects at multiple levels and classes under varying rotation speeds. In this paper, the research focuses on conducting an in-depth analysis of signal signatures, followed by providing a physical insight into feature extraction. Consequently, it enables the application of simple machine learning methods to accurately diagnose various bearing defects, even when dealing with significantly different patterns in training and testing data due to varying rotation speeds. To verify the effectiveness of the proposed SAN method for cases involving varying rotation speeds, the training and testing sets used datasets (vibration measurements) corresponding to different rotation speed profiles. The experimental and analytical results revealed that the proposed SAN method can normalize datasets with disparate vibration patterns, and alleviate the coupling of vibration energy variation and shaft rotation speed. This enhancement resulted in approximately 18.6% increase in the accuracy of bearing diagnosis for cases involving varying rotation speeds.