Showing papers in "Mechanical Systems and Signal Processing in 2005"

TL;DR: In this paper, an improved Hilbert-Huang transform (HHT) was proposed for rolling bearing fault detection. And the improved HHT's performance was compared with that of the wavelet-based scalogram through experimental case studies.

TL;DR: In this paper, a damage detection method based on principal component analysis (PCA) applied to vibration features identified during the monitoring of the structure is proposed for structural health monitoring under varying environmental and operational conditions.

TL;DR: In this article, the authors proposed a method for the fault diagnosis of roller bearings based on EMD and Hilbert spectrum analysis of wavelet coefficients of high scales, which can obtain the local Hilbert marginal spectrum from which the faults in a bearing can be diagnosed and fault patterns can be identified.

TL;DR: In this article, the authors propose a method to resample the signal against the angle by using the acceleration signal of a gearbox, where the gear tooth pairs produce contact shocks during rotation and these shocks are processed in order to retrieve the position of the gear against the time.

TL;DR: A local PCA-based damage detection method is applied for the structural health monitoring of a real bridge using vibration data measured in situ over a one-year period.

TL;DR: This paper proposes two robust separation techniques based on the short-time Fourier transform which are perfectly suited to handle convolutive mixtures of sources and they lead to fast and efficient implementation.

TL;DR: In this paper, a model-based method that predicts remaining useful life of a gear with a fatigue crack is presented, which consists of an embedded model to identify gear meshing stiffness from measured gear torsional vibration, an inverse method to estimate crack size from the estimated meshing stiffnesses, a gear dynamic model to simulate gear mesheming dynamics and determine the dynamic load on the cracked tooth, and a fast crack propagation model to forecast the remaining usable life based on the estimated crack size and dynamic load.

TL;DR: In this paper, a general-purpose data acquisition system and pure software implementation are presented for the measurement of instantaneous angular speed. But, the authors do not consider the use of hardware resources without incurring additional costs in the form of upgrades to the measurement system.

TL;DR: In this paper, a new time-frequency technique, known as basis pursuit, was developed for detecting inner race and outer race faults in a rolling bearing with inner and outer races.

TL;DR: In this paper, an advanced signal classifier for small reciprocating refrigerator compressors using noise and vibration signals was developed, and three classifiers, self-organising feature map, learning vector quantization and support vector machine (SVM), were applied in training and testing for feature extraction and the classification accuracies of the techniques are compared to determine the optimum fault classifier.

TL;DR: Genetic programming is used to detect faults in rotating machinery to examine the performance of two-class normal/fault recognition and the results are compared with a few other methods for fault detection.

TL;DR: The main idea of the proposed approach is that the feature vectors obtained by the FFT, wavelet transform, bispectrum, etc., are used as fault features, respectively, and the HMMs as the classifiers to recognise the faults of the speed-up and speed-down process in rotating machinery.

TL;DR: In this article, a technique for structure damage detection based on spatial wavelet analysis is presented, where both the positions and depths of multi-cracks can be estimated from spatial wavelets based method.

TL;DR: In this paper, the fundamental vibration mode of a cracked cantilever beam is analyzed and both the location and size of the crack are estimated by the sudden changes in the spatial variation of the analysed response, while the size of a crack is related to the fractal dimension measure.

TL;DR: A new method for triaxial sensor set selection based on maximizing the determinant of the target mode information matrix is presented, which maximizes a combination of target mode signal strength and linear independence critical to both test-analysis correlation and modal identification.

TL;DR: In this paper, a detailed analysis is presented to explain the cause of rubbing, its occurrence and phenomenon if the severity of rubbing becomes serious, and a comparison has also been conducted to investigate the effectiveness of monitoring the rubbing-caused impacts by using conventional scalograms and reassigned scalogram.

TL;DR: In this article, a simplified mathematical model of a gear system was developed to illustrate the feasibility of monitoring the instantaneous angular speed (IAS) as a means to monitor the condition of gears that are subjected to fluctuating load conditions.

TL;DR: This paper describes a large-scale evaluation of several different automatic bearing monitoring methods using 103 laboratory and industrial environment test signals and concludes that wavelets are especially well suited for this task.

TL;DR: In this article, a new method based on the Sherman-Morrison identity for the elimination of mass loading effects of transducers from measured frequency response functions (FRFs) is presented.

TL;DR: In this paper, an innovative sensitivity-based technique was introduced for the normalisation of operational mode shapes purely on a basis of output-only data The technique is based on the use of a controlled mass modification experiment and does not involve any analytical models Moreover, it allows to extend the applicability of many modal analysis based applications towards the domain of in-operation modal testing

TL;DR: In this paper, an indirect measurement of the cylinder pressure from diesel engines is demonstrated for a large two-stroke marine diesel engine and a small four-stroke diesel engine, which involves reconstructing the cylinder crank angle domain diagram from the acoustic emission generated during the combustion phase.

TL;DR: In this paper, the effects of cylinder imbalance on the individual harmonic components of the engine speed signal were investigated from a cylinder health diagnostics point of view. Butler et al. used a crankshaft vibration model to evaluate the effect of low power production in individual cylinders of a six-cylinder industrial diesel engine.

TL;DR: In this article, a cyclic Wiener filter is applied to the measured cylinder pressure in order to separate the noises of mechanical and thermal origins, and a blind source separation (BSS) method is applied on signals issued from accelerometers placed on one of the cylinders.

TL;DR: In this paper, a fatigue test is carried out on a gearbox to obtain the gearbox signals of running-in stage, normal wearing stage and ultimate wearing stage, and the results demonstrate their effectiveness in showing the gear box condition degradation and even the gear structural fault.

TL;DR: In this article, the authors proposed a blind source separation algorithm that exploits the spectral redundancy induced by the pure second-order cyclostationary (CS2) part and tries to reconstruct it by combining several filtered frequency-shifted versions of the signal.

TL;DR: In this paper, a method based on singular value decomposition (SVD) was proposed to eliminate noise from measured frequency response functions (FRFs) so as to improve the quality of the measured data.

TL;DR: In this paper, the authors presented a methodology to analyze the influence of the foundation or supporting structure on the rotor-bearings system performance, using the Finite Elements Method (FEM) to model the rotor.

TL;DR: In this paper, the response of a balanced rigid rotor supported by rolling element bearings is studied, where the contacts between the balls and races are considered as non-linear springs, whose stiffness is obtained by using Hertzian elastic contact deformation theory.

TL;DR: In this article, a framework for the development of a fault detection and classification algorithm based on the coefficients calculated from the discrete wavelet transform and using clustering is described, and results from testing are presented, verifying the analysis.

TL;DR: In this article, the authors presented the first step towards using multiple acoustic emission (AE) sensors to produce spatially located time series signals for a running engine, which is meant the decomposition of a multi-source signal by acquiring it with an array of sensors and using source location to reconstitute the individual time series attributable to some or all of these signals.