Journal of Sound and Vibration最新文献

A novel method for reducing the resonant peak of a flexible rotor at critical speeds based on control of the gradual variable stiffness of supports (GVSS) using shape memory alloy (SMA) springs is presented in this paper. The resonance peaks of a rotor structure can be attenuated through the design of GVSS law. Firstly, the impact of GVSS on the rotor's critical speeds was analyzed, and the mechanical mechanism of vibration reduction based on GVSS was identified. Secondly, a rotor system with a single critical speed was used for simulation analysis and it was founded that the starting time to change support stiffness and the change rate were two critical factors that affect vibration reduction. Then, a further simulation was undertaken on a test rig designed with dynamic similarity of an aeroengine rotor having multiple supports and multiple critical speeds. The range of the variable stiffness with SMA springs’ supports and the control strategy of GVSS were investigated. Afterwards, the test rig was manufactured and assembled for testing and validation. To achieve rapid temperature changes for variation of the support stiffness, an innovative design utilizing the carbon fiber heating tubes and the liquid nitrogen sprays for heating and cooling of shape memory alloy springs was carried out. The test results indicate that using gradually variable stiffness of supports with SMA Springs can effectively reduce the multiple resonance peaks of a rotor, with a maximum suppression rate of 52.3 %. This verifies the feasibility of the method. It also indicates the potential for further engineering applications.

The propagation of perturbations in fluids is governed by an acoustic wave equation. This paper, first, introduces an arbitrarily-forced wave equation which, properly adapted, gives rise to equations describing specific phenomena of signal perturbation propagation in fluids (like, for instance, the Lighthill and Ffowcs-Williams and Hawkings equations for radiation and scattering). Then, its solution is determined through a novel boundary integral formulation based on the free-space Green function, which is applicable to fluid domains bounded by solid or porous deformable surfaces. Different versions of the proposed boundary integral formulation can be derived, depending on the frame of reference in which they are expressed. The numerical investigation begins with the comparison of the results obtained by the presented formulation against analytical solutions concerning both a pulsating solid sphere and a deformable porous surface that encloses pulsating sources. Then, the equivalence of the formulations expressed in different frames is examined for a bending and twisting non-lifting wing translating at different Mach numbers. Finally, the aeroacoustic field generated by a helicopter rotor model in forward flight is examined to assess the effect of the body deformation on the radiated noise and the accuracy of the numerical simulations by comparison with experimental data. The results of the numerical investigation have provided a comprehensive validation of the deformable-boundary integral formulation presented for the analysis of wave propagation in fluids, and confirmed its capability to study problems of engineering interest.

Accurate identification and estimation of stochastic forces applied to in-service engineering structures play a vital role in structural safety assessments. This study devised an effective force power spectral density (PSD) identification method to address the challenge of identifying multipoint stationary stochastic forces in uncertain structures. Initially, a probability model was employed to characterize structural uncertainties. Subsequently, an integral relationship was established between the probability density function (PDF) of the random structural parameters and that of the stochastic force PSD. By employing a point-selection technique based on the generalized F-discrepancy and a smoothing method, the uncertainty problem was transformed into a finite number of stochastic force PSD identification problems for deterministic structures. Simultaneously, based on the inverse pseudo-excitation method, a matrix equilibration approach and an improved Tikhonov regularization method were used to address the problem of large identification errors near structural natural frequencies. In comparison to the traditional weighting matrix method, the proposed method further reduces the condition number of frequency response function matrices, thereby enhancing the accuracy of force PSD identification. Finally, numerical examples were presented to validate the effectiveness of the proposed method in solving the stochastic force identification problem.

This work presents an innovative type of acoustic metasurface structure based on the Helmholtz resonator in order to generate an acoustic metasurface with multifunctional effects, such as configurable asymmetrical focusing. With the aim to accomplish a flexible regulation of the complete phase of the sound waves, a new cell structure is constructed by incorporating the Helmholtz resonator height gradient change, resulting in the multifunctional design of an acoustic metasurface via simulation. The metasurface structure parameters, which include the aperture width and the Helmholtz cavity width, are adjusted to attain improved sound focusing and a higher transmission rate. According to the results, the metasurface has an asymmetric focusing influence on a greater frequency range of 2845∼3620 Hz, which is raised by 10.71% compared to the highly uniform symmetric cell structure. The transmission of the cell structure is also higher than 0.96. In the meantime, the sound waves can be actively controlled by adjusting the interlayer spacing and incident angle. This results in a specific adjustable range along the x-axis within 0.22 ∼ 0.87 m and the y-axis within -0.278 ∼ 0.278 m of the focusing location. The outcomes of this investigation may find use in ultrasonic treatment and ultrasonography.

A modeling and analytical method considering contact interface pressure characteristics is presented in this paper. Firstly, a high-fidelity model of a blade with a double friction damping structure is established by solid element, and a three-dimensional friction contact element is used to describe the nonlinear friction interface between the blade contact interfaces. Then, the static pressure distribution characteristics of the contact interface of the blade are obtained through the experimental device of the blade with double friction damping structure, and the accuracy of the pressure characteristics is verified. Based on the static pressure distribution, the time-varying dynamic pressure formula of blade contact interface is derived. The influence of the pressure distribution on the contact characteristics of the contact interface is analyzed and applied to the dynamic calculation of the rotating blade. The influence of different parameters on the blade dynamics is obtained. And the optimum mass ratio of the under-platform damper is obtained by simulating the operation condition of the aero engine blade acceleration process.

To investigate the impact of radial internal clearance of rolling bearings on the dynamic response of a flexible rotor system in a turbo-shaft engine, a dynamic similarity model of the power turbine rotor was established. Experimental research was then conducted. Four rolling bearings supporting the rotor were examined, with dynamic response tests carried out under varying radial internal clearances. The influence of the radial internal clearance on the dynamic characteristics of the rotor system was studied using the controlled variable method. The amplitude, orbit, and asynchronous vibration were analyzed through time-domain signal comparison, waterfall diagrams, and spectral analysis. The experimental results demonstrate that: (1) Adjusting the radial internal clearance of the bearings can significantly reduce the dynamic response of the flexible rotor system, with a maximum observed displacement response reduction of 88%. (2) The efficiency of vibration reduction is closely related to the axial location of the bearing. (3) Optimal radial internal clearance is not necessarily achieved at the maximum or minimum values. (4) The "locked-up" frequency phenomenon, which increases the resonance opportunities of the rotor system, can be mitigated by adjusting the radial internal clearance of different bearings. This research is of great significance and engineering value for understanding, diagnosing, and preventing excessive vibration in flexible rotor systems.

In this study a Chebyshev spectral method is introduced to analyse the vibroacoustic characteristics of plates with arbitrary shape. This approach involves a unique expansion of the governing equations for plate displacements using Chebyshev polynomials, coupled with Gauss-Chebyshev-Lobatto sampling. A significant advancement in computational efficiency is the use of a tensor product configuration. To manage irregular shapes, the elements of the inner product matrix corresponding to the open regions were set to zero. For precise shape representation, a substantial number of Chebyshev-Gauss-Lobatto points, surpassing the polynomial truncation count, are carefully selected. the elastic boundary conditions of the plate were simulated by applying artificial spring techniques at different points. The prediction accuracy of the vibroacoustic phenomena, including those of the mean square velocity and sound power, were rigorously confirmed through comprehensive comparisons with results from previous studies and those obtained using the finite element method. Furthermore, the accuracy and versatility of the method are demonstrated through a variety of numerical examples encompassing plates with geometries shaped like rectangules, triangules, clouds, and pigs geometries, and different boundary conditions.

Gear monitoring and fault diagnosis are vital for preventing accidents and minimizing economic losses in transportation and industrial systems. Traditional methods use vibration sensors and a two-stage analysis approach: preprocessing data to remove noise and extract relevant components, and generating a condition indicator to detect behavioral anomalies in the gears over time.

Time synchronous averaging is a notable tool for monitoring gears at constant speeds. Such a tool filters sensor signals and extracts rotation-related components by using statistical measurements as condition indicators. However, it has limitations in scenarios with time-varying sampling rates and fluctuating speeds, where statistical measures may not fully capture changes in system parameters.

This article proposes a novel methodology for monitoring gears in multivariate rotordynamical systems under fluctuating speed conditions. The method integrates time synchronous averaging, system identification algorithms, and statistical tools. It generates a time-synchronous average signal considering speed fluctuations, computes a state–space model of gear behavior in healthy states, extracts residual data from a data-driven model, and generates a condition indicator based on the Cauchy–Schwarz divergence.

The proposed methodology was evaluated using experimental data from three rotor dynamical setups under different operational conditions. Validation showed its effectiveness, especially under high-load conditions with significant speed fluctuations.

Recently, many forms of audio industrial applications, such as sound monitoring and source localization, have begun exploiting smart multi-modal devices equipped with a microphone array. Regrettably, model-based methods are often difficult to employ for such devices due to their high computational complexity, as well as the difficulty of appropriately selecting the user-determined parameters. As an alternative, one may use deep network-based methods, but these are often difficult to generalize, nor can they generate the desired beamforming map directly. In this paper, a computationally efficient acoustic beamforming algorithm is proposed, which may be unrolled to form a model-based deep learning network for real-time imaging, here termed the DAMAS-FISTA-Net. By exploiting the natural structure of an acoustic beamformer, the proposed network inherits the physical knowledge of the acoustic system, and thus learns the underlying physical properties of the propagation. As a result, all the network parameters may be learned end-to-end, guided by a model-based prior using back-propagation. Notably, the proposed network enables an excellent interpretability and the ability of being able to process the raw data directly. Extensive numerical experiments using both simulated and real-world data illustrate the preferable performance of the DAMAS-FISTA-Net as compared to alternative approaches.

In this study, an analysis method is proposed to explain the dynamic mode decomposition (DMD) mode of wall fluctuating pressure from the perspective of hydrodynamics and acoustics. According to the phase velocity, the wavenumber–frequency spectrum is divided into hydrodynamic, acoustic, and subconvective regions. Multiple DMD modes of the pressure field are calculated to obtain the wavenumber–frequency spectrum of the reconstructed pressure, which is characterized by the fact that the energy is concentrated at different wavenumber positions of the same frequency. This behavioral feature enables the DMD mode to be identified as a hydrodynamic, acoustic, and hybrid property according to the wavenumber position where the energy spot appears. This method can realize the classification and contribution analysis of the hydrodynamic and acoustic properties of the wall pressure DMD mode, and establish the mapping relationship between the acoustic mode and the eddy current characteristics through the eigenvalues. The coherent structure of the trace acoustic energy radiation in the incompressible fluid is observed from the statistical perspective, which increases understanding of the flow noise. The zero-pressure gradient wall flow experiment of Abraham is numerically analyzed using the aforementioned method. The results indicate that most of the DMD modes are identified as hydrodynamic, and only the nineteenth-order DMD mode is identified as acoustic. The frequency of the acoustic mode is 23.9 Hz, which has obvious wave-packet characteristics, whereas the hydrodynamic mode exhibits nonradiative convection characteristics, and its eddy current structure is closer to the wall transfer.