Journal of Sound and Vibration最新文献

The dynamics of slender elastic structures under a generic number of moving loads is addressed in this paper. The problem is solved analytically, assuming the structures are representable via an Euler–Bernoulli beam, the moving loads are equally spaced forces traveling at constant velocity, and the (generic) number of such forces lying on the beam at any time is always the same. The obtained solution is based on a linear map, which transforms the system state at the time at which one of the forces crosses a beam end, to the system state at the time at which the subsequent force crosses the same end. The reiteration of the linear map provides the complete time response of the system. The solution technique described and employed in the paper allows the continuous-time problem to be turned into a discrete-time problem and can in principle also be adopted to study nonlinear dynamic problems. Moreover, it provides analytical expressions for the system state variables and makes it simple and straightforward the analytical detection of the velocities of the traveling forces that can produce a divergent dynamics. It is shown, among the rest, that such velocities (referred to here as divergence velocities) form a subset, yet infinite in dimension, of the set of critical velocities of the system, they correspond to specific external resonance conditions, and are determinable analytically, in closed form. Numerical examples are also reported and corroborate the analytical findings.

In this paper, we describe the development and testing of an active acoustic sensing (AAS) touch interface. The interface detects subtle changes in the vibrational characteristics of an elastic panel when a user applies a small force to the surface at different locations. The system consists of a panel with an affixed force exciter and vibration sensor to monitor the panel vibrations. An automated system was used to manipulate a stylus to apply a light force to the panel at an array of known locations and the vibrational response of the panel was recorded by the affixed sensor. We employed a rectangular grid of 414 points with 10 mm spacing on a 2 mm thick acrylic panel of dimensions 18 cm by 23 cm. Features of the recordings were employed as training data for a deep neural network. The results demonstrate the viability of the AAS interface, and they show the relative performance of the system as a function of the selected features. The demonstration platform achieved a classification accuracy of 100% and a mean distance error of 0.20 mm for regression. The best-performing feature sets were those that contained sufficient spectral resolution to discriminate subtle changes in the center frequencies and amplitudes of the panel’s modal resonances in response to small changes in touch location. The AAS touch interface is a practical and inexpensive means to provide accurate touch sensing for large surfaces, such as displays, televisions, and information kiosks.

An effective experimental identification of modal parameters of a rotating large umbrella truss structure has been developed which uses Digital Image Correlation (DIC) technique in a framework that integrates with Improved Empirical Wavelet Transform (IEWT) and Random Decrement Technique. In order to offset gravity effect in the ground experiment, an air-bearing-based supporting device is designed to allow a large umbrella truss structure to have a frictionless rotation about its mass center. Burg's algorithm is used to calculate the Standardized Autoregressive power spectrums, according to the full-field displacement of the rotating umbrella truss structure captured by DIC. Using the Standardized Autoregressive power spectrums, the natural frequencies of rotating umbrella truss structure are identified, while the corresponding damping ratios and mode shapes are determined via the nonlinear curve fitting method. Finally, vibratory modal analysis of the rotating large umbrella truss structure was performed at different rotating speeds. The presented technique is anticipated to provide an effective approach for identification of modal parameters of large space structures in practical applications.

This work presents a three dimensional, reduced order model of the dynamics of an acoustically compact aperture, subject to an arbitrary pressure forcing. It provides the time evolution of the velocity profile across the orifice section as function of the dynamical pressure excitation. The volume flow can be deduced therefrom, and can thus provide predictions of the fundamental frequency based orifice impedance. The representation of the nonlinear aperture flow proposed here establishes a direct mathematical relation to the fundamental equations of fluid mechanics. This offers a better understanding of the dominant physical mechanisms governing the system‘s dynamics and allows for good a priori estimates without supporting experiments. The model assumes that the viscosity induced rotational component of the fluid motion can be reduced to a discontinuity at the in-flow plane of the thin orifice, without significantly influencing the normal velocity profile. This seemingly unconventional assumption is solely targeting the acoustics problem and is validated with direct numerical simulations (DNS) of the aperture flow, using a compressible solver of the Navier–Stokes equations. Apart from the DNS, the model predictions are also validated against well established experimental results from the literature.

The localization of linearly moving sound sources using microphone arrays is particularly challenging as the transient nature of the signal leads to relatively short observation periods. Commonly, a moving focus approach is used and most methods operate at least partially in the time domain. In contrast, this manuscript presents an inverse source localization algorithm for uniformly moving single-frequency sources that acts entirely in the frequency domain. For this, a 2.5D approach is utilized and a transfer function between sources and a microphone grid is derived. By solving a least squares problem using the measured data at the microphone grid, the unknown source distribution in the moving frame can be determined. First, the measured time signals need to be transformed from the time into the frequency domain using a windowed discrete Fourier transform (DFT), which leads to an effect called spectral leakage that depends on the length of the time interval and the analysis window used.

To include the spectral leakage effect in the numerical model, the calculation of the transfer matrix is modified using the Fourier transform of the analysis window used in the DFT applied to the measurements. Currently, this approach is limited to single-frequency sources as this restriction allows for a simplification of the calculation and reduces the computational effort. The least squares problem is solved using a Tikhonov regularization employing an L-curve approach to determine a suitable regularization parameter. As moving sources are considered, utilizing the Doppler effect enhances the stability of the system by combining the transfer functions for multiple frequencies in the measured signals. The performance of the approach is validated using simulated data of a moving point source with or without a reflecting ground. Numerical experiments are performed to show the effect of the choice of frequencies in the receiver spectrum, the effect of the DFT, the frequency of the source, the distance between source and receiver, and the robustness with respect to noise.

No matter how the chicken's body shakes, its head can always remain relatively motionless, leading to the intuitive impression that the S-configuration of the chicken neck possesses an unparalleled vibration isolation capability. However, this viewpoint has not been rigorously substantiated. To unravel the vibration isolation mechanism inherent in the chicken neck, this study introduces a multi-modular S-configurational model inspired by its biological structure. Utilizing Newton's law and Lagrange's equations, both the static and dynamic models for the S-configurational model are formulated. Furthermore, we incorporate actuators into the model and develop a bionic attitude control method. Surprisingly, numerical simulations reveal that the S-configuration of the chicken neck does not exhibit any passive vibration isolation function, challenging the intuitive impression. Instead, the motionless of a chicken head results from active control implemented by the corresponding chicken neck. This study may contribute to a better understanding of the vibration attenuation function of the neck of birds.

This paper addresses the computation of frequency-dependent dispersion curves (i.e., $k\left(\omega \right)$) and wave modes within the framework of the Wave Finite Element Method (WFEM) and in the context of high-dimensional periodic unit cell models. Numerous applications, ranging from phononics to vibroacoustics, now rely on dispersion analyses or wave expansion over a subset of eigensolutions – complex wavenumbers and Bloch waves – resulting from the resolution of an eigenvalue problem with a $T$-palindromic quadratic structure ($T$-PQEP). To exploit the structure of finite element models, various structure-preserving linearizations such as the Zhong-Williams and the $(S+S^{-1})$-transform have already been developed to achieve partial wave resolution of large $T$-PQEP, primarily targeting the dominating (least decaying) waves. In this paper we derive an alternative linearization of the $T$-PQEP for the $k\left(\omega \right)$ problem, which leads to enhanced targeting of the eigenvalues around the unit circle and reduces the inaccuracies induced by root multiplicity. A specific form of the problem is then proposed as an optimal compromise between ease of implementation, numerical stability, convergence and accuracy enhancement. The performance of our proposed linearization is compared against existing ones across various iterative eigensolvers, since the generalized eigenvalue problems involve complex non-hermitian matrices, which are not extensively included in eigensolvers. Results indicate that the proposed linearization should be favored for the WFEM, as it provides numerical enhancements in dispersion and wave vectors computation for large eigenvalue problems, as well as for further wave expansion applications.

The presence of sound sources that rotate can cause interference with stationary acoustic imaging, especially if the intensity of the rotating sound source is strong. Vice versa, stationary sound sources can also interfere with rotational acoustic imaging. Current algorithms for separating and locating rotating and stationary sound sources have problems such as weak separation capabilities, complex calculations, and limited array layouts. To address these challenges more effectively, a frequency-domain hybrid deconvolution method based on modal composition beamforming is proposed to separate and localize rotating and stationary sound sources. This algorithm operates within the frequency domain and is not restricted by array layout or the tonal single-frequency nature of sound sources. First, the point spread function and cross-point spread function matrices of the array are derived based on the modal transfer function. Then, a system of linear equations is constructed to separate rotating and stationary sound sources. Finally, the sound source separation and localization problems are solved through Gaussian Seidel and sparse-constrained deconvolution, respectively. Compared with the virtual rotating array method combined with matrix completion, simulation and experimental results demonstrate that this method can accurately locate and separate rotating and stationary sound sources, even when there is a substantial difference in intensity between rotating and stationary sound sources.

The presence of massive and directional vehicles moving on a railroad bridge causes temporal fluctuations in the fundamental frequencies of both bridge and vehicle systems, making traditional structural inspections difficult to employ effectively. Thus, this paper proposes an image-to-image Generative Adversarial Network (GAN) that estimates temporal frequency variation for the vehicle-bridge interaction system. To address the challenges associated with conventional approaches, eigenvalue analysis, numerical substitution, and Fourier series approximations are examined using a simple degree of freedom and a more complex model. Thus, the GAN model is proposed to overcome those limitations. In the framework, based on the properties of a real bridge and vehicle model, the modified Stockwell transform of bridge acceleration from the dynamic simulation is used as input data with the paired data from the numerical substitution approach. Then, the model is validated through quantitative measures and laboratory scale experiments. Results showed that the model has strong performances across the various scenarios, demonstrating the potential for bridge condition assessment under operational conditions.

Experimental modal analysis is commonly used to identify models for the vibratory behavior of structures. This is done by conducting a set of experiments to obtain the structure’s governing equations and information in the form of eigenfrequencies, mode shapes, and damping. However, linearity of the test structure is assumed within this identification procedure. Hence, as it stands, experimental modal analysis is not readily applicable to build models when nonlinearities are present through, for example, friction, (electro-) magnetic fields, or large deformations. To identify governing equations for such systems, a robust and systematic identification procedure is proposed in this article. The identification routine is formulated in the frequency domain, and a noise reduction scheme and a simplification routine are employed to obtain sparse and robust models. The identification procedure is implemented in an automated script (FrID), which is applied to forced response measurements stemming from structures with magnets, clamps, and bolted joints as well as systems with multiple active modes and internal resonances. The identified governing equations accurately fit the experimentally obtained frequency response measurements and can also be utilized to extrapolate the response for different forcing amplitudes. Moreover, nonlinear modes of the underlying conservative system can be computed from the identified governing equations.