Showing papers in "Mechanical Systems and Signal Processing in 1996"

TL;DR: In this paper, a plate element model of a cantilevered box beam with varying rib stiffnesses is used to demonstrate efficiency and highlight practical difficulties of the proposed approaches for predictions of static responses, modal frequencies, modeshapes, and sensitivities of those quantities to design parameters.

TL;DR: This modeling technique for fault diagnosis was found to require much shorter lengths of vibration data than traditional pattern classification techniques used in the field of machine condition monitoring, and generally outperformed the radial basis functions and the traditional linear autoregressive models.

TL;DR: In this article, the authors introduce some of the basic concepts of chaos theory, then details a method for quantifying a fractal dimension from a time series, the correlation dimension.

TL;DR: In this paper, a new method of feature extraction and feature assessment using a wavelet packet transform for monitoring of machining processes is introduced, which is tested using two practical examples: chatter monitoring in turning and tool wear monitoring in drilling.

TL;DR: In this paper, the sensitivity method is applied to update finite element models of welded joints and the boundary condition of a cantilever plate, and the results show an improvement on the analytical natural frequencies.

TL;DR: In this article, the authors used the bary center of spectral lines in the main lobe to obtain the coordinate of the spectrum peak and obtained the accurate frequency, amplitude and phase of the rms spectrum peak.

TL;DR: A 100% reliability has been achieved for the detection of roller bearing defects via fuzzy reasoning and Bearing_Expert is very beneficial for factory automation and preventive maintenance.

TL;DR: Application of the method for the identification of the KUKA IR/361 industrial robot proves the validity of the proposed parameterisation approach, which allowed small condition numbers with few coefficients for each joint to be obtained and simplifies the optimisation problem significantly.

TL;DR: In this paper, the correlation dimension from chaotic time series data is determined by reconstruction of the attractor using the time delay method from the raw time series, followed by computation of the correlation dimensions from the phase space vectors.

TL;DR: The proposed network functioned successfully in clustering the data obtained from cutting tests performed within a reasonable range of cutting conditions and showed approximately 80 to 94% success rates in these tests.

TL;DR: In this paper, the deconvolution properties of cepstrum analysis are used to extract poles and zeros of transfer functions from response vibrations, which are then used for curve-fitting purpose.

TL;DR: In this paper, a model-based demodulation scheme is developed to exploit the information contained in wideband gear vibrations for better gear defect detection, which can include a large number of tooth meshing harmonics as modulation carrier.

TL;DR: In this article, the effect of out-of-band modes on the in-band FRF, during such development, is investigated. Butler et al. proposed a complete method to track changes in a frequency response function (FRF) which might be caused by a variety of reasons such as the development of local material damage.

TL;DR: In this paper, a direct procedure is developed to estimate the mass properties from the massline characteristic of experimental FRFs, where the non-linear problem is divided into a series of simpler linear problems and solved in subsequent steps.

TL;DR: In this article, the temperature-induced voltage generation of distributed piezoelectric sensors can be further divided into two major components: the pyroelectric effect and the thermal strain effect.

TL;DR: A new efficient neural network algorithm that has been previously developed by the present authors for multiple-index based regression is adapted to solve the trend analysis problem for a machine system.

TL;DR: In this paper, a Hilbert transform based on an analysing wavelet is proposed. But the Hilbert transform algorithm is not suitable for signal analysis, especially in extracting orthogonality modulated signals from a mechanical dynamic system.

TL;DR: In this paper, the authors expose the complete procedure of suppressing the chatter of a machine center without detailing each design step, and show that the spindle is the main weak component of the machine.

TL;DR: The design relations are formulated such that to allow on-line design and implementation and thus result in a self-tuning control algorithm that is implemented on an integrated digital signal processing and transputer system.

TL;DR: In this article, a neural network scheme is applied to perform one-step-ahead prediction of flank wear from cutting force signals obtained from a tool dynamometer, using an appropriate force ratio, the flank wear can be predicted within 8 percent of the actual wear for various turning conditions.

TL;DR: The methodology is evaluated with machining data from a simplified monitoring situation, and proves to be able to bridge the gap between academic enthusiasm and industrial needs for a practical and reliable sensor-based toolwear monitoring system.

TL;DR: In this paper, a frequency-domain technique to extract the normal modes from a measurement contaminated by noise for highly coupled structures is developed, which is applicable to either viscous or structural damping.

TL;DR: In this paper, it is shown using numerical methods, that the magnitude of singular values dramatically reflects the minimum of non-minimum phase structure of the system allowing clear interpretation of the magnitudes of the condition number.

TL;DR: In this article, the authors used a low-cost conventional tachometer to measure the induced speed variations induced by the gear tooth impacts caused by exciting the system sinusoidally.

TL;DR: In this article, a multi-input multi-output (MIMO) algorithm for modal parameter identification is developed based on linear prediction theory and its numerical efficiency compared to that of the well known Eigensystem realisation algorithm ERA.

TL;DR: In this article, the authors investigated the use of statistical and time-frequency analysis of the downstream pressure signature to characterise blade-to-blade variability of both average and residual pressure associated with a single row 36 blade axial compressor.

TL;DR: In this paper, higher-order spectral analysis is used to understand the role of phase coupling in non-linear interactions between two or more Fourier components. And the analytical approximations are useful in understanding the dependence of bispectra on the nonlinearities.

TL;DR: In this article, a short-circuit detector was developed to detect burn-through in weld joints and a square-law detector was combined with a non-linear modification of an autoregressive model with extra input.

TL;DR: In this article, the authors deal with the estimation of the order, the parameters, and the spectrum of a process modeled by a multivariate autoregressive time series, by minimization of a new criterion function.

TL;DR: In this paper, a linear quadratic Gaussian theory with loop transfer recovery has been used to design the compensator for the negative effect of tractor accelerations on a spray boom.