Showing papers in "Journal of Sound and Vibration in 2016"

TL;DR: A feature learning model for condition monitoring based on convolutional neural networks is proposed to autonomously learn useful features for bearing fault detection from the data itself and significantly outperforms the classical feature-engineering based approach which uses manually engineered features and a random forest classifier.

TL;DR: In this paper, a network-based model of the offshore structure subject to external wave force and actuator faults is presented, and an event-triggering mechanism is proposed such that during the control implementation, only requisite sampled data is transmitted over networks.

TL;DR: Experimental results validate the effectiveness of the methodology and demonstrate that proposed algorithm can be applied to recognize the different categories and severities of rolling bearings.

TL;DR: In this article, the authors presented a semi-analytical model to analyze an Euler-Bernoulli beam with embedded ABH feature and its full coupling with the damping layers coated over its surface.

TL;DR: In this article, a new vehicle suspension structure called ISD suspension, including the inerter, spring and damper has been created, which can effectively improve the damping performance of the suspension system, especially at the offset frequency of the vehicle body.

TL;DR: In this article, a multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role.

TL;DR: Based on sparse representation theories, a new approach for fault diagnosis of rolling element bearing is proposed in this article, where the over-complete dictionary is constructed by the unit impulse response function of damped second-order system, whose natural frequencies and relative damping ratios are directly identified from the fault signal by correlation filtering method.

TL;DR: Four kernel-based algorithms for damage detection under varying operational and environmental conditions, namely based on one-class support vector machine, support vector data description, kernel principal components analysis and greedy kernel principal component analysis are presented.

TL;DR: In this article, a review of the recent advances in computational methods for nonlinear normal modes (NNMs) is presented, and different algorithms for the computation of undamped and damped NNMs are discussed.

TL;DR: In this paper, a negative stiffness magnetic spring (NSMS) is employed to reduce the resonance frequency of the linear isolator, and the effect of the geometric parameters of the magnets on the stiffness characteristic of the NSMS is analyzed.

TL;DR: In this article, the influence of external load, the external excitation, the internal system parameters and the equilibrium positions on the dynamic responses of nonlinear tristable energy harvesters by using the harmonic balance method was investigated.

TL;DR: The growing area of harvesting energy by aerodynamically induced flutter in a fluid stream is reviewed in this article, where various approaches were found to understand, demonstrate and [sometimes] optimise harvester performance based on Movement-Induced or Extraneously Induced Excitation.

TL;DR: The main advantages of the proposed generalized stepwise demodulation transform for bearing condition monitoring under variable speed conditions include: (a) it can simultaneously improve energy concentration level of signals of interest and remove interferences in the TFR, (b) it is resampling-free and hence can avoid the resamplings related errors, and (c) it yields instantaneous frequencies for fault and shaft rotation and thus can carry out both fault detection and diagnosis tasks.

TL;DR: In this article, a nonlinear vibration model for fault severity assessment of rolling element bearings is established, and the inner race defect size parameter is introduced into the dynamic model, and vibration response signals are analyzed quantitatively to observe the relationship between vibration responses and fault sizes.

TL;DR: In this paper, an intelligent neural network based controller is designed to control the optimal voltage applied on the piezoelectric patches of a flexible cantilever plate to mitigate the vibration response.

TL;DR: In this article, the authors studied the low frequency wave propagation behavior of sandwich beams containing periodically embedded internal resonators and obtained a closed form expression for the propagation constant using a phased array approach and verified using finite element simulations.

TL;DR: In this article, a control-based continuation is adapted to follow the locus where system response and excitation are in quadrature, extracting the backbone curve of the underlying conservative system.

TL;DR: In this article, a human-structure interaction system for vibration in the vertical direction is considered, where the pedestrian vertical force is represented as a general time-dependent force, and the pedestrian is in turn modelled as moving force, moving mass, and moving spring-mass-damper.

TL;DR: Considering the sparsity of force in the time domain or in other basis space, a general sparse regularization method based on minimizing l 1 -norm of the coefficient vector of basis functions was developed in this article.

TL;DR: In this paper, a hierarchical Bayesian model updating framework is proposed for model calibration, response prediction and damage identification of a footbridge under changing environmental/ambient conditions, which is applied for model calibrations and response prediction.

TL;DR: In this paper, a new realization of a membrane-type acoustic metamaterial (MAM) with adjustable sound transmission properties is presented, which distinguishes itself from other realizations by a stacked arrangement of two MAMs which is inflated using pressurized air.

TL;DR: In this article, an online tacholess order tracking method is proposed for bearing fault detection under rotating speed variation conditions, which is based on extracting the instantaneous tachometer information from the collected vibration signal itself continuously, and resampling the original signal with equal angle increment.

TL;DR: Based on the Stewart platform configuration, the 6-DOF isolator is constructed by 6 X-shape structures as legs, which can realize very good and tunable vibration isolation performance in all 6 directions with a passive manner.

TL;DR: A highly accurate methodology for rolling element bearing fault diagnosis which is based on relatively simple procedures is suggested, as the simplicity of the individual processes ensures easy application and the possibility for automation of the entire process.

TL;DR: Wang et al. as discussed by the authors proposed a double-dictionary matching pursuit (DDMP) for fault extent evaluation of rolling bearing based on the Lempel-Ziv complexity (LZC) index.

TL;DR: In this article, the spectral structures of vibration signals of epicyclic gearboxes were derived by algebraic equations and the spectral structure of these models were deduced using Fourier series analysis, where all possible vibration transfer paths from gear meshing points to a fixed transducer and the effects of angular shifts of planet gears were considered.

TL;DR: In this article, a Stewart platform with piezoelectric actuators is presented for micro-vibration isolation, where the direct feedback of integrated forces is combined with the FxLMS based adaptive feedback to dampen vibration of inherent modes.

TL;DR: In this article, an innovative active seat suspension system for vehicles is presented, which is built with two low cost actuators each of which has one rotary motor and one gear reducer.

TL;DR: In this article, the von Karman nonlinear strain-displacement relationships are used and geometric imperfections are taken into account for nonlinear vibrations of viscoelastic thin rectangular plates subjected to normal harmonic excitation.

TL;DR: In this article, a new TSA-based angular resampling (TSAAR) method is proposed for fault diagnosis under speed fluctuation condition via sound signal analysis, which can accurately estimate the phase information of the fault-induced impulses using neither complicated time-frequency analysis techniques nor external speed sensors, and hence it provides a simple, flexible and data-driven approach that realizes variable-speed motor bearing fault diagnosis.