Showing papers in "Mechanical Systems and Signal Processing in 2010"

TL;DR: The paper addresses two complex case studies of modal and structural identification of monuments in Portugal: the Clock Tower of Mogadouro and the Church of Jeronimos Monastery, in Lisbon.

TL;DR: In this paper, a combination between relevance vector machine (RVM) and logistic regression (LR) is proposed to assess the failure degradation and prediction from incipient failure until final failure occurred.

TL;DR: A novel approach for optimal sensor and/or actuator placement for structural health monitoring (SHM) applications by implementing an appropriate statistical model of the wave propagation and feature extraction process within a detection theory framework.

TL;DR: In this paper, a technique based on the dual-tree complex wavelet transform (DTCWT) is proposed to enhance the desired features related to some special type of machine fault.

TL;DR: In this article, the authors developed an ANN approach utilizing both failure and suspension condition monitoring histories, which can be used for remaining useful life prediction of other equipments, and validated using vibration monitoring data collected from pump bearings in the field.

TL;DR: In this article, the quality of modal damping ratios estimates based on ambient and free vibration tests using both numerical simulations and data collected on large Civil Engineering structures where both tests were performed.

TL;DR: In this article, a modified ensemble empirical mode decomposition (MEEMD) method is proposed to reduce the computational cost of the original EEMD method as well as improving its performance.

TL;DR: In this paper, a new hybrid method based on optimal Morlet wavelet filter and autocorrelation enhancement is presented to diagnose rolling element bearing faults in the early stage of bearing failures.

TL;DR: A detailed comparison with the classical spectral analysis based on correlation techniques shows that the proposed procedures are more robust than those of Schoukens et al.

TL;DR: Wang et al. as discussed by the authors proposed a new method for bearing performance degradation assessment based on lifting wavelet packet decomposition and fuzzy c-means, which can reflect effectively performance degradation of bearing.

TL;DR: In this paper, a parameter independent yet simple to implement fault detection technique is presented, where the Teager energy operator is tailored to extract both the amplitude and frequency modulations of the vibration signals measured from mechanical systems.

TL;DR: In this article, the authors present a literature review on the field of automated modal identification and tracking procedures for structural health assessment, and some case studies are also reported in order to validate the approach.

TL;DR: In this article, the authors proposed an alternative way of bearing condition monitoring based on the instantaneous angular speed measurement by the help of a large experimental investigation on two different applications, they prove that localized faults like pitting in bearing generate small angular speed fluctuations which are measurable with optical or magnetic encoders.

TL;DR: The main idea in this study is to employ the linear ARMA model and the nonlinear GARCH model to explain the wear and fault condition of machine, respectively.

TL;DR: In this article, an experimental assessment of several vibration based statistical time series methods for Structural Health Monitoring (SHM) is presented via their application to a lightweight aluminum truss structure.

TL;DR: In this paper, the operational transfer path analysis (OTPA) method is extended with the singular value decomposition (SVD) method to reduce the influence of noise in practical applications.

TL;DR: In this article, a Gaussian process with RBF kernels was used for regression to learn the relationship between time of flight differences and damage location using data generated by artificially stimulated acoustic emission.

TL;DR: In this paper, a 20-cylinder diesel engine with crankshaft torsional modes in the low frequency range is modeled with a phenomenological model and an automated diagnosis based on an artificially intelligent system is proposed.

TL;DR: In this article, the effect of the cylinder's surface temperature on both the direct and inverse dynamics of the damper is studied, and the neural network model is shown to be reasonably robust against significant temperature variation.

TL;DR: In this paper, the authors used Autoregressive (AR) models to fit the acceleration time histories obtained from two experimental structures: a 3-storey bookshelf structure and the ASCE Phase II Experimental SHM Benchmark Structure, in undamaged and limited number of damaged states.

TL;DR: In this paper, an adaptive regularization approach for solving the nonlinear model updating inverse problem is presented, which aims at limiting the local change in damaged structural elements in each iteration and forcing the variation of other undamaged elements close to zero.

TL;DR: Limits to transmissibility based transfer path analysis methods are identified and described and the potential dangers of applying such methods without taking these into account are pointed out.

TL;DR: In this article, a step-by-step approach is presented to optimise the signal processing both for offline and online applications based on the characteristics of the signal for in-cylinder pressure analysis.

TL;DR: In this paper, a new method named frequency-spatial domain decomposition (FSDD) was proposed for modal identification in civil engineering structures, with theoretical background, formulation and algorithm.

TL;DR: In this paper, a method to adjust design parameter means and their related covariance matrix from multiple sets of experimental modal data is presented. But this method is restricted to a single set of test data.

TL;DR: In this article, an OMAX approach was used to solve the problem of identifying the true behavior of a finite element (FE) model updating problem, where an artificial force is used in operational conditions and a structural model is identified that takes both the forced and the ambient excitation into account.

TL;DR: In this paper, a vibration-based fault diagnostic method is developed to identify the vital components of a diesel engine that have abnormal clearance by inspecting the timing of impacts created by the components that had abnormal clearance during operation.

TL;DR: Results show that, despite the changes of temperature, the IDDM provides a correct identification of damage location even for cases where the evolution of modal frequencies belies the actual damaged state of the structure.

TL;DR: It is shown that the proposed method can be used for nonlinear systems and for parametric identification of the system dynamics in a generalized output error framework and illustrated on simulations and real measurements examples.