Showing papers in "Mechanical Systems and Signal Processing in 1995"

TL;DR: Comparison with the non-orthogonal wavelet transform for the same length of discrete data shows that the description of the signal in the 3-dimensional map of the wavelets transform is not sufficiently comprehensive due to limited scales.

TL;DR: In this paper, the basic formulation for the frequency response function based updating method and several possible solution strategies are discussed using simulated experimental data, and the basic algorithm is extended to deal with complex FRF data and the updating of a proportional damping matrix is attempted using experimentally-measured frequency response data.

TL;DR: In this article, a normalised bispectral measure is used in the analysis of vibration signals containing periodic components and noise, and practical considerations regarding the choice of sampling rate are considered.

TL;DR: In this article, the authors start from the element level and consider what criteria must be satisfied by the element mass and stiffness matrices, and thus what parameters there are which can be optimised in the updating.

TL;DR: In this article, a case study aimed at updating a medium-size finite element model using frequency response function (FRF) data was presented, where the numerical stability of the method and its applicability to true measured FRF data were investigated in the case of a plate-beam structure which was modeled using about 500 dof.

TL;DR: A normalised bispectral measure is used in the analysis of vibration signals containing periodic components and noise, showing that there is potential for using these measures for machine condition monitoring.

TL;DR: In this article, the authors apply model reduction methods to systems with local non-linearities, modeled using finite element analysis, and obtain the receptance of a discrete and a continuous system with cubic stiffening discrete springs, using the harmonic balance method.

TL;DR: By analysing a windowing signal with Fourier transform, the leakage-induced phase error is investigated, and the phase error distribution is indicated, and a practical approach to correct leakage in a discrete frequency signal to obtain accurate phase information is presented.

TL;DR: In this article, the mass, damping and stiffness parameters of a field foundation supporting unbalanced rotating machinery are identified using a single run-down measurement of the bearing characteristics and measurements of rotor and foundation motions at selected co-ordinates and speeds.

TL;DR: In this paper, a new scheme for detection and diagnosis of localised defects in rolling element bearings, using hypothesis test theory, is described, where the vibration of damaged bearings consists of two alternating zero-mean Gaussian components, with different variances, representing background noise and defect signature respectively.

TL;DR: In this article, the authors focus on the control issues that arise during automation of die and mould surface finishing using industrial robot held tools, with particular attention being devoted to the design and evaluation of force controllers to maintain the desired tool-workpiece interaction.

TL;DR: In this article, the authors investigated the characteristics of the inverse transfer function and frequency response function (FRF) error, and the indirect force determination error was analyzed statistically, and a regularisation process to reduce the error especially near the first kind of inverse pole frequencies was proposed.

TL;DR: It is shown that the recursive filtering can be used as an effective and reliable method of pre-conditioning the original vibration signals and is implemented and validated using computer simulation and experiments.

TL;DR: In this article, a sequel to the application of recursive filters to monitoring the vibrations of rotating machinery is presented. And the technique described in Part I (The Use of Non-stationary Recursive Filters) is further enhanced by using the angle domain.

TL;DR: In this paper, a number of approaches that estimate spectra, natural frequencies and dampings from the response to an unknown random input were compared with traditional frequency response function estimates using both a Monte Carlo simulation and real data.

TL;DR: In this paper, a uniform covering of the state plane can be obtained using a periodic kinematic signal (i.e. displacement, velocity and acceleration) with a user specified amplitude spectrum by making a proper choice for the associated phases.

TL;DR: In this article, various formulations for suspension design optimisation are discussed and implemented using grid and sequential quadratic programming optimisation methods, and the actual design of the test washing machine is verified for its optimality.

TL;DR: Feedforward neural networks are developed and implemented to classify a four-stage high pressure air compressor into one of the following conditions: baseline, suction or exhaust valve faults, and provide very accurate diagnosis for suction and discharge valve defects.

TL;DR: In this paper, a genetic algorithm is designed for the problem of finding the optimal location of the actuators for active noise control in an interior environment, and the algorithm is implemented and tested against a simple greedy approach.

TL;DR: In this paper, the effect of spherical wave fronts on conventional noise source identification methods which assume a planar wave front was studied. And the validity of these methods in identifying the location and strength of the noise source was tested by numerical simulations in terms of the various array parameters and also by experiments conducted in an anechoic room.

TL;DR: In this article, a modal-based method for the two tasks of structural dynamic model updating and identification of joint models in structural assemblies is introduced, and its theoretical and computational capabilities and shortcomings are discussed.

TL;DR: In this paper, a new and effective method has been developed to locate localised stiffness nonlinearity by correlating an analytical model with measured vibration test data, where the analytical model used is assumed to contain modeling errors and the measured data required are only those at one mode with incomplete co-ordinates.

TL;DR: A comparison between five speeds using the conventional detector and the new detector shows that the latter clearly outperforms the former, and can be used in several other applications e.g. gear default detection and axle fissure.

TL;DR: In this paper, it was shown that transient vibrations, like those generated by valve impacts in a reciprocating compressor, are best analysed in the time-domain, where they can be characterized in terms of timing and strength on a cycle-by-cycle basis, by filtering it with the inverse of the structural transfer function.

TL;DR: In this paper, the effect of laminations on the transverse vibrational modes of a stator was investigated and it was shown that the effect is much greater than on the in-plane vibrational mode.

TL;DR: In this article, a fault diagnosis and severity assessment (FDIA) scheme for a screw compressor has been established using feed-forward neural networks (FNNs), which consists of nonlinear model identification of the compressor and pattern classification of parameters of identified models corresponding to the various faulty conditions.

TL;DR: In this paper, an effective procedure for the early detection and objective diagnosis of faults in rolling element bearings is described, which involves the use of an inductive inference theory based classification program called "Snob", which objectively divides frequency spectra into classes representing different bearing conditions.

TL;DR: In this paper, a two-level Gauss-Newton approach is proposed which allows the simultaneous and efficient correction of design and updating models, which can be applied to modal or FRF test data.

TL;DR: In this paper, the problem of identifying a substructure belonging to a greater structure, assuming that the main part of the structure is known, has been addressed in the time domain.

TL;DR: It was found that by the sorting up operation of the symptom data and extraction of equal symptom readings, similar recognition and forecasting abilities can be obtained, as in statistical Weibull and Frechet characteristics.