Showing papers in "Mechanical Systems and Signal Processing in 2002"

TL;DR: In this paper, the authors compared 138 publications dealing with on-line and indirect tool wear monitoring in turning by means of artificial neural networks and compared the methods applied in these publications as well as the methodologies used to select certain methods, to carry out simulation experiments, to evaluate and to present results.

TL;DR: The performance of both types of classifiers in two-class fault/no-fault recognition examples are examined and the attempts to improve the overall generalisationperformance of both techniques through the use of genetic algorithm based feature selection process are examined.

TL;DR: In this paper, an effective demodulation method based on the use of a complex shifted Morlet wavelet family was proposed for detecting rolling element bearing defects, which can lead to the clear identification of the nature of the fault.

TL;DR: In this paper, a new approach of gear fault diagnosis based on continuous wavelet transform is presented, which is more suitable for extracting mechanical fault information than orthogonal wavelet transforms.

TL;DR: In this paper, a sensitivity-based method is proposed for the scaling of operational mode shapes on a basis of operational modal models only, where the excitation forces are unknown and not all modal parameters can still be estimated.

TL;DR: In this paper, a wavelet transform is applied to detect abrupt changes in the vibration signals obtained from operating bearing being monitored, which can be easily associated with the bearing defect characteristic frequencies for diagnosis.

TL;DR: In this article, a stiffness-based prognostic model for bearing systems based on vibration response analysis and damage mechanics is discussed, which can be used to effectively predict the failure lifetime and the remaining life of a bearing system.

TL;DR: In this article, a vibration waveform normalisation approach is presented, which enables the use of the pseudo-Wigner-Ville distribution to indicate deteriorating fault conditions under fluctuating load conditions.

TL;DR: In this paper, a mathematical model is developed to simulate data from typical BTT tests of rotating assemblies, and the simulator is then used in order to provide a qualitative analysis of several phenomena that can be associated with the synchronous vibrations of rotating assembly, including mistuning, coupling, excitation at multiple Engine Orders and simultaneous synchronous and asynchronous responses.

TL;DR: In this article, a frequency-domain maximum likelihood estimator is used to automate the modal identification process and a fuzzy clustering algorithm is used for mode selection and mode-tracking.

TL;DR: In this article, the authors developed a condition monitoring procedure for rolling element bearing which involves a combination of signal processing, signal analysis and artificial intelligence methods, based on power spectrum, bispectral and bicoherence vibration analyses.

TL;DR: An overview of the existing direct methods for the finite-element model (FEM) updating problem is presented and the recently developed ‘direct and partial modal’ approach for the partial eigenstructure assignment problem and the ‘eigenvalue embedding’ techniques for vibrating systems are reviewed.

TL;DR: This paper presents the application of wavelet analysis to identify events and changes in structural state in a bridge during and after its construction.

TL;DR: In this article, the measurement and modelling of linear systems in the presence of nonlinear distortions has been studied for a special class of periodic excitation signals, and enhanced properties of the best linear approximation and the stochastic non-linear distortions are obtained.

TL;DR: In this paper, the robustness is achieved by minimising some not-so-well-known condition numbers of the eigenvalues of the closed-loop second-order pencil.

TL;DR: In this article, an information maximisation based blind source separation algorithm (a type of ICA) was proposed for gear vibration measurements, where the individual gear and pinion vibrations cannot be separated using the blind separation algorithm, but the learning curve can be used to detect impulsive and random changes in the data.

TL;DR: Instead of directly inspecting complicated wavelet patterns in time–scale domains with limited human experience and availability, automated classification of the localised features related to gear faults, therefore, can be implemented.

TL;DR: In this paper, a reduced-order characteristic polynomial (ROCP) is defined in terms of the measured natural frequency, the partial modal properties predicted from a flawed FEM model and the model parameters to be updated or identified.

TL;DR: In this article, the authors present a technical overview of the design and analysis of active boundary controllers for distributed parameter (vibration and noise) systems, which are commonly applied to non-linear finite dimensional systems.

TL;DR: In this paper, the unbalance estimation was combined with the split frequency range for the foundation model and highlights the limitations observed during the estimation of foundation models and the state of unbalance.

TL;DR: In this paper, a rolling smooth tire with test laboratory facilities was used to measure the radial deformation of the tire and the acceleration signal of the tyre tread over one revolution, and the true contact length was estimated.

TL;DR: In this article, a comparison of traditional linear filters popular in the jet engine industry is made with the median filter and the subfilter weighted FIR median hybrid (SWFMH) filter results with simulated data with implanted faults.

TL;DR: In this article, an empirical model-based fault diagnosis system is developed for induction motors using recurrent dynamic neural networks and multiresolution signal processing methods, which is scalable to different power ratings and has been successfully demonstrated with data from 2.2, 373 and 597 kW induction motors.

TL;DR: In this paper, a discrete wavelet transform (DWT) is used to characterize the non-linear dynamic characteristics of the milling operation and the onset and progression of instability.

TL;DR: In this paper, a wavelet modulus maxima based approach for the identification of the shaft center orbits is proposed, which is based on wavelet modulation maxima and continuous wavelet transform.

TL;DR: In this article, robust estimation techniques are used to determine the most robust parameter set, which is optimum in that the residuals are as small as can be, for a range of bounded uncertainties on the model and measurements.

TL;DR: In this paper, a method for analysis of stochastic processes is presented which makes feasible the extraction of deterministic and random components of process dynamics directly from data, applied to time series from metal cutting.

TL;DR: The proposed solution to the partial eigenvalue assignment problem of an undamped gyroscopic distributed parameter system is readily applicable to stabilise or to combat the effects of excessive vibrations in a large structure.

TL;DR: In this paper, the applicability of the sensitivity-based method is extended to the domain of operational modal analysis (output-only measurements) by using a new method for the correct rescaling of operational mode shape estimates that neither requires forced vibration testing nor finite element modelling.

TL;DR: In this paper, a theoretical energy flow analysis is proposed to predict the energy exchanged among complex systems, via the entropy concept, leading to a theoretical analysis of energy transmission among oscillators.