680 resultados para Train Critical Speed


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This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

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Rolling Element Bearings (REBs) are vital components in rotating machineries for providing rotating motion. In slow speed rotating machines, bearings are normally subjected to heavy static loads and a catastrophic failure can cause enormous disruption to production and human safety. Due to its low operating speed the impact energy generated by the rotating elements on the defective components is not sufficient to produce a detectable vibration response. This is further aggravated by the inability of general measuring instruments to detect and process the weak signals at the initiation of the defect accurately. Furthermore, the weak signals are often corrupted by background noise. This is a serious problem faced by maintenance engineers today and the inability to detect an incipient failure of the machine can significantly increases the risk of functional failure and costly downtime. This paper presents the application of noise removal techniques for enhancing the detection capability for slow speed REB condition monitoring. Blind deconvolution (BD) and adaptive line enhancer (ALE) are compared to evaluate their performance in enhancing the source signal with consequential removal of background noise. In the experimental study, incipient defects were seeded on a number of roller bearings and the signals were acquired using acoustic emission (AE) sensor. Kurtosis and modified peak ratio (mPR) were used to determine the detectability of signal corrupted by noise.

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The transplantation of autologous bone graft as a treatment for large bone defects has the limitation of harvesting co-morbidity and limited availability. This drives the orthopaedic research community to develop bone graft substitutes. Routinely, supra-physiological doses of bone morphogenetic proteins (BMPs) are applied perpetuating concerns over undesired side effects and cost of BMPs. We therefore aimed to design a composite scaffold that allows maintenance of protein bioactivity and enhances growth factor retention at the implantation site. Critical-sized defects in sheep tibiae were treated with the autograft and with two dosages of rhBMP-7, 3.5 mg and 1.75 mg, embedded in a slowly degradable medical grade poly(ε-caprolactone) (PCL) scaffold with β-tricalcium phosphate microparticles (mPCL-TCP). Specimens were characterised by biomechanical testing, microcomputed tomography and histology. Bridging was observed within 3 months for the autograft and both rhBMP-7 treatments. No significant difference was observed between the low and high rhBMP-7 dosages or between any of the rhBMP-7 groups and autograft implantation. Scaffolds alone did not induce comparable levels of bone formation compared to the autograft and rhBMP-7 groups. In summary, the mPCL-TCP scaffold with the lower rhBMP-7 dose led to equivalent results to autograft transplantation or the high BMP dosage. Our data suggest a promising clinical future for BMP application in scaffold-based bone tissue engineering, lowering and optimising the amount of required BMP.

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Improved public awareness of the environment and available technologies will continue to highlight the importance of sustainable housing in the coming years. Despite this potential, the majority of new housing development in Australia is still “project homes” with few tangible sustainability measures. Stakeholders tend to have different perceptions and priorities on sustainability. To promote the uptake of sustainable housing products, a study of the critical issues affecting the implementation of sustainable housing is necessary. This research investigates multiple factors that may influence key stakeholders’ decision-making towards sustainable housing adoption. Drawing insights from combined questionnaire and interview studies, 12 critical factors and their interrelationships are identified based on professional views in the Australian housing industry. The mutual influences, or driving force and dependency, of these factors are further investigated via Interpretive Structural Modelling (ISM) to distinguish those requiring prominent and immediate attention. A hierarchical model is developed to help key stakeholders prioritise actions when implementing sustainable housing.

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The dynamics describing the motion response of a marine structure in waves can be represented within a linear framework by the Cummins Equation. This equation contains a convolution term that represents the component of the radiation forces associated with fluid memory effects. Several methods have been proposed in the literature for the identification of parametric models to approximate and replace this convolution term. This replacement can facilitate the model implementation in simulators and the analysis of motion control designs. Some of the reported identification methods consider the problem in the time domain while other methods consider the problem in the frequency domain. This paper compares the application of these identification methods. The comparison is based not only on the quality of the estimated models, but also on the ease of implementation, ease of use, and the flexibility of the identification method to incorporate prior information related to the model being identified. To illustrate the main points arising from the comparison, a particular example based on the coupled vertical motion of a modern containership vessel is presented.

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Robust facial expression recognition (FER) under occluded face conditions is challenging. It requires robust algorithms of feature extraction and investigations into the effects of different types of occlusion on the recognition performance to gain insight. Previous FER studies in this area have been limited. They have spanned recovery strategies for loss of local texture information and testing limited to only a few types of occlusion and predominantly a matched train-test strategy. This paper proposes a robust approach that employs a Monte Carlo algorithm to extract a set of Gabor based part-face templates from gallery images and converts these templates into template match distance features. The resulting feature vectors are robust to occlusion because occluded parts are covered by some but not all of the random templates. The method is evaluated using facial images with occluded regions around the eyes and the mouth, randomly placed occlusion patches of different sizes, and near-realistic occlusion of eyes with clear and solid glasses. Both matched and mis-matched train and test strategies are adopted to analyze the effects of such occlusion. Overall recognition performance and the performance for each facial expression are investigated. Experimental results on the Cohn-Kanade and JAFFE databases demonstrate the high robustness and fast processing speed of our approach, and provide useful insight into the effects of occlusion on FER. The results on the parameter sensitivity demonstrate a certain level of robustness of the approach to changes in the orientation and scale of Gabor filters, the size of templates, and occlusions ratios. Performance comparisons with previous approaches show that the proposed method is more robust to occlusion with lower reductions in accuracy from occlusion of eyes or mouth.

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This paper presents a novel control strategy for velocity tracking of Permanent Magnet Synchronous Machines (PMSM). The model of the machine is considered within the port-Hamiltonian framework and a control is designed using concepts of immersion and invariance (I&I) recently developed in the literature. The proposed controller ensures internal stability and output regulation, and it forces integral action on non-passive outputs.

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Phospholipids are the key structural component of cell membranes, and recent advances in electrospray ionization mass spectrometry provide for the fast and efficient analysis of these compounds in biological extracts.1-3 The application of electrospray ionization tandem mass spectrometry (ESI-MS/MS) to phospholipid analysis has demonstrated several key advantages over the more traditional chromatographic methods, including speed and greater structural information.4 For example, the ESI-MS/MS spectrum of a typical phospholipidsparticularly in negative ion modesreadily identifies the carbon chain length and the degree of unsaturation of each of the fatty acids esterified to the parent molecule.5 A critical limitation of conventional ESI-MS/MS analysis, however, is the inability to uniquely identify the position of double bonds within the fatty acid chains. This is especially problematic given the importance of double bond position in determining the biological function of lipid classes.6 Previous attempts to identify double bond position in intact phospholipids using mass spectrometry employ either MS3 or offline chemical derivatization.7-11 The former method requires specialized instrumentation and is rarely applied, while the latter methods suffer from complications inherent in sample handling prior to analysis. In this communication we outline a novel on-line approach for the identification of double bond position in intact phospholipids. In our method, the double bond(s) present in unsaturated phospholipids are cleaved by ozonolysis within the ion source of a conventional ESI mass spectrometer to give two chemically induced fragment ions that may be used to unambiguously assign the position of the double bond. This is achieved by using oxygen as the electrospray nebulizing gas in combination with high electrospray voltages to initiate the formation of an ozoneproducing.

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The backlash against feminist criminology is intertwined with broader resistance to feminism and other progressive social movements. Carol Smart noted in 1979 that changes in women's social or economic status have long been perceived as threats to the patriarchal gender order and are therefore "viewed with considerable misgiving, whilst any reinforcement of the value of women's traditional, domestic role has been perceived as a stand against further social decline and disorder" (Smart, 1979, p. 50). The contemporary backlash exists at the nexus of economic and ideological retrenchment seeking to enforce the hegemony of neoliberal conceptions of justice as formal equality. Critical criminology is linked to the backlash against feminism in two key ways. First, critical criminology is an important location for the study of antifeminism and its implications. Second, criminologists who study women or gender have frequently been attacked by antifeminist scholars and commentators.

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In spite of the extensive usage of continuous welded rails, a number of rail joints still exist in the track. Although a number of them exist as part of turnouts in the yards where the speed is not of concern, the Insultated Rail Joints (IRJs) that exist in ballasted tracks remain a source of significant impact loading. A portion of the dynamic load generated at the rail joints due to wheel passage is transmitted to the support system which leads to permanent settlements of the ballast layer with subsequent vertical misalignment of the sleepers around the rail joints. The vertical misalignment of the adjacent sleepers forms a source of high frequency dynamic load raisers causing significant maintenance work including localised grinding of railhead around the joint, re-alignment of the sleepers and/or ballast tamping or track component renewals/repairs. These localised maintenance activities often require manual inspections and disruptions to the train traffic loading to significant costs to the rail industry. Whilst a number of studies have modelled the effect of joints as dips, none have specifically attended to the effect of vertical misalignment of the sleepers on the dynamic response of rail joints. This paper presents a coupled finite element track model and rigid body track-vehicle interaction model through which the effects of vertical of sleepers on the increase in dynamic loads around the IRJ are studied. The finite element track model is employed to determine the generated dip from elastic deformations as well as the vertical displacement of sleepers around the joint. These data (dip and vertical misalignments) are then imported into the rigid body vehicle-track interaction model to calculate the dynamic loads.

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In the developing digital economy, the notion of traditional attack on enterprises of national significance or interest has transcended into different modes of electronic attack, surpassing accepted traditional forms of physical attack upon a target. The terrorist attacks that took place in the United States on September 11, 2001 demonstrated the physical devastation that could occur if any nation were the target of a large-scale terrorist attack. Therefore, there is a need to protect criticalnational infrastructure and critical information infrastructure. In particular,this protection is crucial for the proper functioning of a modern society and for a government to fulfill one of its most important prerogatives – namely, the protection of its people. Computer networks have many benefits that governments, corporations, and individuals alike take advantage of in order to promote and perform their duties and roles. Today, there is almost complete dependence on private sector telecommunication infrastructures and the associated computer hardware and software systems.1 These infrastructures and systems even support government and defense activity.2 This Article discusses possible attacks on critical information infrastructures and the government reactions to these attacks.

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This paper presents the modeling and motion-sensorless direct torque and flux control of a novel dual-airgap axial-flux permanent-magnet machine optimized for use in flywheel energy storage system (FESS) applications. Independent closed-loop torque and stator flux regulation are performed in the stator flux ( x-y) reference frame via two PI controllers. This facilitates fast torque dynamics, which is critical as far as energy charging/discharging in the FESS is concerned. As FESS applications demand high-speed operation, a new field-weakening algorithm is proposed in this paper. Flux weakening is achieved autonomously once the y-axis voltage exceeds the available inverter voltage. An inherently speed sensorless stator flux observer immune to stator resistance variations and dc-offset effects is also proposed for accurate flux and speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a machine prototype.