Analysis of the influence of pre-loading in the rating life calculation of tapered roller bearings applied to lightweight front-axle differentials

For intricate automotive systems that enclose several components, such as gearboxes, an important aspect of the design is defining the correct assembly parameters. A proper assembly can ensure optimized operating conditions and therefore the components can achieve a longer life. In the case of the support bearings applied to front-axle lightweight differentials, the assembly preload is a major aspect for an adequate performance of the system. During the design phase it is imperative to define reference values to this preload, so the application would endure its requirements. However, with the assistance of computer simulations, it is possible to determine an optimum condition of operation, i.e. optimum pre-load, which would increase the system reliability. This paper presents a study on the influence of preload on the rating life of tapered roller bearings applied to light-weight front axle differentials, evaluating how preload affects several key parameters such as rating life and displacement of components, taking into account the flexibility of the surrounding differential housing. Copyright © 2012 SAE International.

Active control in rotating machinery using magnetic actuators with linear matrix inequalities (LMI) approach

The recent years have seen the appearance of innovative system for acoustic and vibration attenuation, most of them integrating new actuator technologies. In this sense, the study of algorithms for active vibrations control in rotating machinery became an area of enormous interest, mainly due to countless demands of an optimal performance of mechanical systems in aircraft, aerospace and automotive structures. In this way, this paper presents an approach that is numerically verified for active vibration control in a rotor using Active Magnetic Bearings (AMB). The control design in a discrete state-space formulation is carried out through feedback technique and Linear Matrix Inequalities (LMI) approach. LMI is useful for system with uncertainties. The AMB uses electromagnetic forces to support a rotor without mechanical contact. By monitoring the position of the shaft and changing the dynamics of the system accordingly, the AMB keeps the rotor in a desired position. This unique feature has broadened for the applications of AMB and now they can be considered not only as a main support bearing in a machine but also as dampers for vibration control and force actuators. © 2009 Society for Experimental Mechanics Inc.

Análise da abrangência de modelo modificado para mancais curtos com deformação.

Este trabalho apresenta uma discussão sobre o estudo dos efeitos térmicos e elásticos decorrentes da pressão de sustentação presentes nos mancais. Para tanto, propõe-se um modelo matemático baseado nas equações para mancais curtos considerando a região de cavitação e utilizando o princípio da continuidade de massa. Com isto, deduzem-se as equações para o mancal a partir das equações de Reynolds e da energia, aplicando uma solução modificada para a solução de Ocvirk, sendo as equações resolvidas numericamente pelo Método das Diferenças Finitas. Somado o tratamento de mecânica dos fluidos, o trabalho discute dois modelos térmicos de previsão de temperatura média do fluido e sua influência no campo de pressão, apresentando gráficos representativos do campo de pressão e de temperatura, assim como as diferenças e implicações das diferenças. Para o cálculo de deformação da estrutura, utiliza-se um Modelo de Elementos Finitos para uma dada geometria, fazendo-se uma avaliação da variação do campo de pressão e o quanto essa diferença afeta as demais propriedades do fluido. Por fim, com o modelo completo, calcula-se o quanto esse modelamento para mancais curtos se aproxima de soluções para mancais finitos, com base em resultados da literatura, chegando a desvios quase oito vezes menores que os previstos pela literatura. Além disso, pode-se estabelecer a abrangência do modelo, ou seja, prever as condições em que suas propriedades são válidas e podem ser utilizadas para estudos iniciais.

Reliable Fault Diagnosis for Low-Speed Bearings Using Individually Trained Support Vector Machines With Kernel Discriminative Feature Analysis

This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm

In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed rolling element bearing failures. The scheme consists of fault feature calculation, discriminative fault feature analysis, and fault classification. The proposed approach first computes wavelet-based fault features, including the respective relative wavelet packet node energy and entropy, by applying a wavelet packet transform to an incoming acoustic emission signal. The most discriminative fault features are then filtered from the originally produced feature vector by using discriminative fault feature analysis based on a binary bat algorithm (BBA). Finally, the proposed approach employs one-against-all multiclass support vector machines to identify multiple low-speed rolling element bearing defects. This study compares the proposed BBA-based dimensionality reduction scheme with four other dimensionality reduction methodologies in terms of classification performance. Experimental results show that the proposed methodology is superior to other dimensionality reduction approaches, yielding an average classification accuracy of 94.9%, 95.8%, and 98.4% under bearing rotational speeds at 20 revolutions-per-minute (RPM), 80 RPM, and 140 RPM, respectively.

Variable impedance bearings for large rotating machinery

This thesis describes an investigation which was carried out under the Interdisciplinary Higher Degres (IHD) Scheme of The University of Aston in Birmingham. The investigation, which involved joint collaboration between the IHD scheme, the Department of Mechanical Engineering, and G.E.C. Turbine Generators Limited, was concerned with hydrostatic bearing characteristics and of how hydrostatic bearings could be used to enable turbine generator rotor support impedances to be controlled to give an improved rotor dynamic response. Turbine generator rotor critical speeds are determined not only by the mass and flexibility of the rotor itself, which are relatively easily predicted, but also by the dynamic characteristics of the bearing oil film, pedestal, and foundations. It is because of the difficulty in accurately predicting the rotor support characteristics that the designer has a problem in ensuring that a rotor's normal running speed is not close to one of its critical speeds. The consequence of this situation is that some rotors do have critical speeds close to their normal running speed and the resulting high levels of vibration cause noise, high rotor stresses, and a shortening of bearing life. A combined theoretical and experimental investigation of the effects of mounting the normal rotor journal bearing in a hydrostatic bearing was carried out. The purpose of the work was to show that by changing the oil flow resistance offered by capillaries connecting accumulators to the hydrostatic bearing, the overall rotor support characteristics could be tuned to enable rotor critical speeds to be moved at will. Testing of a combined journal and hydrostatic bearing has confirmed the theory of its operation and a theoretical study of a full size machine showed that its critical speed could be moved by over 350 rpm and that its rotor vibration at running speed could be reduced by 80%.