Journal of Vibroengineering
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Minimizing the radiated sound power from vibrating plates by using in-plane functionally graded materials
Full text linkThis paper presents a method for decreasing sound radiation from vibrating plates. The method uses Functionally Graded Materials (FGM) for building the plates instead of isotropic material. The graded pattern of material composition is characterized within the in-plane directions based on a two-dimensional trigonometric law. In the proposed method, the finite element method (FEM) is utilized for estimating the dynamic response of the plates. Then, the Lumped Parameter Model (LPM) is used for calculating sound radiation power. A genetic algorithm is applied as an optimization tool for determining the best distribution of the FGM. The efficacy of the proposed method is demonstrated by three design problems; minimizing the radiated sound from vibrating FGM plate at a particular excitation frequency, over a frequency band, and at a particular natural frequency. The design problems show that a considerable decrease of sound power can be accomplished with the optimal design of FGM plates in comparison with the isotropic plates
Amplitude and frequency estimator for aperiodic multi-frequency noisy vibration signals of a tram gearbox
Full text linkSinusoidal parameter estimation for determining frequency position and amplitude is challenging for noisy short vibration signals, e.g. from machines or human vibrations. In this paper, we propose the “Trimmed Window Discrete Fourier Transform” (TWDFT) estimator, which uses for every frequency a one-point discrete Fourier transform (DFT) to determine the corresponding spectral amplitude. To avoid leakage effects, it cuts the time interval so that it corresponds to an integer number of period durations. To evaluate the estimator performance, we compare it with relevant estimators such as the Cramer-Rao lower bound (CRLB) and the spectral spline interpolation applied on a noisy mono-frequent test signal with a fractional frequency. For the estimated parameters, the mean squared errors (MSE) are calculated and compared as a function of the signal-to-noise ratio (SNR). The advantages of the TWDFT estimator can be seen over the whole SNR range. The TWDFT estimates are better than the fast Fourier transform (FFT) starting at a SNR of –6 dB. At a SNR of 30 dB, the estimator meets the real value of the frequency and reaches similar results as the CRLB. The application of the TWDFT estimator as a short-time analysis on a vibration signal of a tram gearbox shows a significantly more differentiated time-frequency analysis compared to a short-time Fourier transform (STFT)
Parametric identification of technological thermophysics processes based on neural network approach
Full text linkIn this paper, the inverse problem of technological thermophysics under the influence of disturbing factors is under study. In the problem of identifying the process of nonstationary heat conduction, it is required to concretize its mathematical model by qualitatively and quantitatively expressing an unknown characteristic based on the results of experimental studies. It is necessary to determine the uncontrolled time-varying heat flux density on the surface of the heated product from the noisy temperature measurement results at a certain point inside the object. The problem is formulated in an extreme setting as a problem of optimal control of an object with distributed parameters, in which the quadratic value of the temperature discrepancy between experimental and model data is used as an optimality criterion. The preliminary parametrization of the desired control on a compact set of polynomial functions implements the reduction to the parametric optimization problem. Physically substantiated solutions to inverse heat conduction problems are found as a result of their sequential parametric optimization using an algorithmically accurate method based on optimal control theory. The proposed solution combines the advantages of an accurate analytical method, which allows taking into account the physical essence of the process of interest and artificial intelligence methods, which provide great opportunities to find an quasioptimal solution under conditions of uncertainty in the mathematical description of the process. The analytical method of sequential parameterization provides a search for solutions on a compact set of smooth functions, as a result of which there is a reduction to the problem of parametric optimization. Measurement errors lead to processing large amounts of data, which necessitates the use of artificial neural networks for parametric optimization of the identified characteristics. The attained results confirm the possibility of obtaining adequate solutions to the inverse problems of thermal conductivity with the intensity of the measurement noise in the range of 0-15 %. In the investigated class of solutions, with a suitable setting of the ranges of belonging of the parameters, the error in approximating the temperature state can be up to 2-5 %, and the error in restoring the unknown characteristic can be up to 7-10 %
Consideration on lateral vibration of automobiles in quasi-planar model with wheel separation and road deformation taken into account
Full text linkThis article considers lateral vibration of an automobile in a so-called quasi-planar model where both the loss of contact and road deformation are taken into account. The automobile with dependent suspension is modeled as a vibration system which has two masses and four degrees of freedom. The deformed road is modeled as an elastic beam which has uniform rectangular cross-section, is simply supported at the two ends and lies on the Kelvin's visco-elastic ground. The loss of contact and the change in dimensions of contact areas are considered. The differential equations of motion of the vehicle-road coupled system which contains a partial differential equation are transformed into a set of all ordinary differential equations by applying the Bubnov-Galerkin’s method. A procedure for numerically solving the transformed differential equations of motion is proposed. Some illustrating results coming from numerical consideration are also presented in the paper
Intelligent optimization for bending moment in uniaxial fatigue loading test of wind turbine blades
Full text linkWind turbine mainly relies on blades to capture wind energy and complete energy conversion. Wind turbine blade is one of the key components of wind turbine. In the full scale load test of wind turbine blade, the moment matching is the key part of the test and the premise of wind turbine blade certification. In order to solve the matching problem of the bending moment and the arrangement of counterweight in the fatigue loading test, an improved intelligent optimization algorithm was proposed to achieve the purpose of moment matching. The relationship between the excitation frequency of the rotating mass and the natural frequency of the blade was determined through the identification of the modal test parameters, and the calculation model of the section bending moment was constructed. Based on the optimization algorithm, the joint optimization of moment distribution and amplitude control was carried out with the mean square error as the fitness function. The correctness and feasibility of the balance weight optimization scheme for moment matching in uniaxial fatigue test were verified through the blade test
Geometrically non-linear free and forced vibration of a shallow arch
Full text linkThe purpose of this present work is to investigate the geometrical non-linearity in free and forced vibration of a shallow arch elastically restrained at the ends. The non-linear governing equilibrium equation of the shallow arch is obtained after the Euler Bernoulli theory and the Von Karman geometrical non-linearity assumptions. After applying the ends conditions, the eigenvalues problem of the generalized trancendant equation have been determined iteratively using the Newton-Raphson algorithm. The kinetic and total strain energy have been discretized into a series of a finite spatial functions which are a combination of linear modes and basic function contribution coefficients. Using Hamilton’s principle energy and spectral analysis, the problem is reduced into a set of non-linear algebraic equations that solved numerically using an approximate explicit method developed previously the so-called second formulation. Considering a multimode approach, the effect of initial rise and concentrated force on non-linear behaviour of system has been illustrated in the backbone curves giving the non-linear amplitude-frequency dependence. The corresponding non-linear deflections and curvatures have been plotted for various vibration amplitudes
Dynamic response analysis of cable-stayed bridge under random traffic flow and fleet
Full text linkThe vehicle-bridge coupling vibration (VBCV) theory is being applied in the safety evaluation of existing bridges, such as cable-stayed bridge. In order to study the dynamic performance and vibration response of urban long-span cable-stayed bridges under traffic flow, and provide reference for the design, construction and safety assessment of existing bridges, the urban cable-stayed bridge with single tower and double cable in service was taken as the research object. The dynamic response of bridges under vehicles with different number, distance, speed and weight was analyzed. And the VBCV of bridge under different vehicle density and speed was discussed. The traffic flow on the bridge was simulated by the cellular automaton (CA) model, a half car model with four degrees of freedom was established, and the bridge models were established by the ANSYS software. According to the displacement coordination and mechanical balance conditions, the two models were connected, and were solved by MATLAB software. The dynamic response of the vehicle-bridge system under the vehicle fleet and random traffic flow was investigated. The research results showed that the vertical displacement (VD) of the main span increased with the number of vehicles, conversely, the vertical vibration acceleration (VVA) decreased. As driving distance increased, the VD and VVA of main span decreased. The VD of main span was not sensitive to the vehicle speed, but the VVA increased with the vehicle speed. The VD and VVA of the main span increased with the vehicle weight, and the VD of main span was proportional to the traffic density. As the traffic density increased, the VVA increased first, then decreased
Research progress of cavity-based acoustic energy harvester
Full text linkThe acoustic energy collector uses the cavity acoustic mode to capture the acoustic signal in a certain frequency range at the mouth of the cavity, achieves fluid-solid coupling and amplifies the acoustic vibration excitation, and then through piezoelectric, magnetoelectric and friction power generation mechanisms, the acoustic energy is finally converted into electrical energy. The overview of the research progress of cavity-based acoustic energy harvesters has found that acoustic energy harvesters are usually composed of resonant cavity, diaphragm, and transducer materials, and the resonant cavity is the key to the design of acoustic energy harvester. Analyze the influence of cavity structure on sound pressure amplification to provide reference for the research and application of acoustic energy harvester. The piezoelectric type is the main energy conversion method, the magnetoelectric type is the auxiliary, and the friction power generation and the acoustic crystal resonance power generation have also become a new research direction, because of the widest application range of hybrid power generation, it has become a future development trend
An anomaly detection method for rotating machinery monitoring based on the most representative data
Full text linkWith the development of concepts of industry 4.0, condition monitoring techniques are changing. Large amounts of generated data require diagnostic procedures to be automated, which drives the need for new and better methods of autonomous interpretations of vibration condition monitoring data. However, if new methods are to be operational, they need to be verified under real industrial conditions and compared with well-established expert-based diagnostic techniques. This article introduces the novel algorithm of data preprocessing for the nearest-neighbor-based anomaly detection. This approach is validated on real industrial machinery in a series of case studies. The population of over-hung centrifugal fans, employed in the same industrial process, were monitored continuously according to the proposed methodology for an extended time period. Piezoceramic accelerometers were used to register time-domain vibration data. The data were processed to extract several signal features to serve as inputs to the anomaly detection algorithm. The novel solution is compared to the well-established condition monitoring approach. Presented data include not only the intact state of machinery but also a machine breakdown case and serious deterioration of the machine condition. The influence of maintenance work is also presented in the article. Authors show the data-driven approach to condition monitoring, which can be used as one of many predictive maintenance techniques
Experimental estimation of the damping ratio of metallic foam sandwich panels with sand intrusions
Full text linkThe interest to use steel foam sandwich structures is expanding in various industrial applications, and more attention is paid to improve the properties of these materials. However, liquid and solid intrusions can severely hamper their useful characteristics. This study aims to provide an experimental investigation on the potential of steel foam (hollow sphere) sandwich specimens to operate as passive dampers in flexural vibration and to preserve their capabilities when affected by the intrusion of external particles. The authors utilized two different experimental examinations, random noise (white noise) and impact (hammer) tests. The specimens consist of a hollow sphere foam core sandwiched between two mild steel sheets, bonded with a thermosetting epoxy resin. To simulate the intrusions of granular materials in operating conditions, the metallic foam cores of the samples were partially filled with different percentages of quartz sand particles. The two-phase specimens were then compared to the pristine (single-phase) ones. The resulting estimates of the vibrational damping ratio for single and double-phase metallic foam specimens were used to calibrate the respective Finite Element models, which proved to be suitable for replicating the damping characteristics of the specimens