274 resultados para Pumping machinery.


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Cyclostationary models for the diagnostic signals measured on faulty rotating machineries have proved to be successful in many laboratory tests and industrial applications. The squared envelope spectrum has been pointed out as the most efficient indicator for the assessment of second order cyclostationary symptoms of damages, which are typical, for instance, of rolling element bearing faults. In an attempt to foster the spread of rotating machinery diagnostics, the current trend in the field is to reach higher levels of automation of the condition monitoring systems. For this purpose, statistical tests for the presence of cyclostationarity have been proposed during the last years. The statistical thresholds proposed in the past for the identification of cyclostationary components have been obtained under the hypothesis of having a white noise signal when the component is healthy. This need, coupled with the non-white nature of the real signals implies the necessity of pre-whitening or filtering the signal in optimal narrow-bands, increasing the complexity of the algorithm and the risk of losing diagnostic information or introducing biases on the result. In this paper, the authors introduce an original analytical derivation of the statistical tests for cyclostationarity in the squared envelope spectrum, dropping the hypothesis of white noise from the beginning. The effect of first order and second order cyclostationary components on the distribution of the squared envelope spectrum will be quantified and the effectiveness of the newly proposed threshold verified, providing a sound theoretical basis and a practical starting point for efficient automated diagnostics of machine components such as rolling element bearings. The analytical results will be verified by means of numerical simulations and by using experimental vibration data of rolling element bearings.

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This paper merges the analysis of a case history and the simplified theoretical model related to a rather singular phenomenon that may happen in rotating machinery. Starting from the first, a small industrial steam turbine experienced a very strange behavior during megawatt load. When the unit was approaching the maximum allowed power, the temperature of the babbitt metal of the pads of the thrust bearing showed constant increase with an unrecoverable drift. Bearing inspection showed that pad trailing edge had the typical aspect of electrical pitting. This kind of damage was not reparable and bearing pads had to replaced. This problem occurred several times in sequence and was solved only by adding further ground brushes to the shaft-line. Failure analysis indicated electrodischarge machining as the root fault. A specific model, able to take into consideration the effect of electrical pitting and loading capacity decreasing as a consequence of the damage of the babbitt metal, is proposed in the paper and shows that the phenomenon causes the irretrievable failure of the thrust bearing.

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The transmission path from the excitation to the measured vibration on the surface of a mechanical system introduces a distortion both in amplitude and in phase. Moreover, in variable speed conditions, the amplification/attenuation and the phase shift, due to the transfer function of the mechanical system, varies in time. This phenomenon reduces the effectiveness of the traditionally tachometer based order tracking, compromising the results of a discrete-random separation performed by a synchronous averaging. In this paper, for the first time, the extent of the distortion is identified both in the time domain and in the order spectrum of the signal, highlighting the consequences for the diagnostics of rotating machinery. A particular focus is given to gears, providing some indications on how to take advantage of the quantification of the disturbance to better tune the techniques developed for the compensation of the distortion. The full theoretical analysis is presented and the results are applied to an experimental case.

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The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

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In the field of rolling element bearing diagnostics, envelope analysis has gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of this technique has been extended to cases in which small speed fluctuations occur, maintaining high effectiveness and efficiency. In order to make this algorithm suitable to all industrial applications, the constraint on speed has to be removed completely. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This chapter presents a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.

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This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.

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The Communities and Technologies 2013 conference received 46 submissions for full papers and 12 submissions for research in progress papers. From these submissions, 17 papers were selected to appear at the conference (29%). All submitted papers were subjected to double blind peer review by an independent international program committee of 51 experts.

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Incorporating a learner’s level of cognitive processing into Learning Analytics presents opportunities for obtaining rich data on the learning process. We propose a framework called COPA that provides a basis for mapping levels of cognitive operation into a learning analytics system. We utilise Bloom’s taxonomy, a theoretically respected conceptualisation of cognitive processing, and apply it in a flexible structure that can be implemented incrementally and with varying degree of complexity within an educational organisation. We outline how the framework is applied, and its key benefits and limitations. Finally, we apply COPA to a University undergraduate unit, and demonstrate its utility in identifying key missing elements in the structure of the course.

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How influential is the Australian Document Computing Symposium (ADCS)? What do ADCS articles speak about and who cites them? Who is the ADCS community and how has it evolved? This paper considers eighteen years of ADCS, investigating both the conference and its community. A content analysis of the proceedings uncovers the diversity of topics covered in ADCS and how these have changed over the years. Citation analysis reveals the impact of the papers. The number of authors and where they originate from reveal who has contributed to the conference. Finally, we generate co-author networks which reveal the collaborations within the community. These networks show how clusters of researchers form, the effect geographic location has on collaboration, and how these have evolved over time.

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Small-scale pumps will be the heartbeat of many future micro/nanoscale platforms. However, the integration of small-scale pumps is presently hampered by limited flow rate with respect to the input power, and their rather complicated fabrication processes. These issues arise as many conventional pumping effects require intricate moving elements. Here, we demonstrate a system that we call the liquid metal enabled pump, for driving a range of liquids without mechanical moving parts, upon the application of modest electric field. This pump incorporates a droplet of liquid metal, which induces liquid flow at high flow rates, yet with exceptionally low power consumption by electrowetting/deelectrowetting at the metal surface. We present theory explaining this pumping mechanism and show that the operation is fundamentally different from other existing pumps. The presented liquid metal enabled pump is both efficient and simple, and thus has the potential to fundamentally advance the field of microfluidics.

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Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

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Whole System Design is increasingly being seen as one of the most cost effective ways to both increase the productivity and reduce the negative environmental impacts of an engineered system. A focus on design is critical, as the output from this stage of the project locks-in most of the economic and environmental performance of the designed system throughout its life, which can span from a few years to many decades. Indeed, it is now widely acknowledged that all designers – particularly engineers, architects and industrial designers – need to be able to understand and implement a whole system design approach. This book provides a clear design methodology, based on leading efforts in the field, and is supported by worked examples that demonstrate how advances in energy, materials and water productivity can be achieved through applying an integrated approach to sustainable engineering. Chapters 1–5 outline the approach and explain how it can be implemented to enhance the established Systems Engineering framework. Chapters 6–10 demonstrate, through detailed worked examples, the application of the approach to industrial pumping systems, passenger vehicles, electronics and computer systems, temperature control of buildings, and domestic water systems.

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In many cities around the world, surveillance by a pervasive net of CCTV cameras is a common phenomenon in an attempt to uphold safety and security across the urban environment. Video footage is being recorded and stored, sometimes live feeds are being watched in control rooms hidden from public access and view. In this study, we were inspired by Steve Mann’s original work on sousveillance (surveillance from below) to examine how a network of camera equipped urban screens could allow the residents of Oulu in Finland to collaborate on the safekeeping of their city. An agile, rapid prototyping process led to the design, implementation and ‘in the wild’ deployment of the UbiOpticon screen application. Live video streams captured by web cams integrated at the top of 12 distributed urban screens were broadcast and displayed in a matrix arrangement on all screens. The matrix also included live video streams of two roaming mobile phone cameras. In our field study we explored the reactions of passers-by and users of this screen application that seeks to inverse Bentham’s original panopticon by allowing the watched to be watchers at the same time. In addition to the original goal of participatory sousveillance, the system’s live video feature sparked fun and novel user-led apprlopriations.

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Falling prices have led to an ongoing spread of public displays in urban areas. Still, they mostly show passive content such as commercials and digital signage. At the same time, technological advances have enabled the creation of interactive displays potentially increasing their attractiveness for the audience, e.g. through providing a platform for civic discourse. This poses considerable challenges, since displays need to communicate the opportunity to engage, motivate the audience to do so, and be easy to use. In this paper we present Vote With Your Feet, a hyperlocal public polling tool for urban screens allowing users to express their opinions. Similar to vox populi interviews on TV or polls on news websites, the tool is meant to reflect the mindset of the community on topics such as current affairs, cultural identity and local matters. It is novel in that it focuses on a situated civic discourse and provides a tangible user interface, tackling the mentioned challenges. It shows one Yes/No question at a time and enables users to vote by stepping on one of two tangible buttons on the ground. This user interface was introduced to attract people’s attention and to lower participation barriers. Our field study showed that Vote With Your Feet is perceived as inviting and that it can spark discussions among co-located people.

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Adult neural stem cells (NSCs) play important roles in learning and memory and are negatively impacted by neurological disease. It is known that biochemical and genetic factors regulate self-renewal and differentiation, and it has recently been suggested that mechanical and solid-state cues, such as extracellular matrix (ECM) stiffness, can also regulate the functions of NSCs and other stem cell types. However, relatively little is known of the molecular mechanisms through which stem cells transduce mechanical inputs into fate decisions, the extent to which mechanical inputs instruct fate decisions versus select for or against lineage-committed blast populations, or the in vivo relevance of mechanotransductive signaling molecules in native stem cell niches. Here we demonstrate that ECM-derived mechanical signals act through Rho GTPases to activate the cellular contractility machinery in a key early window during differentiation to regulate NSC lineage commitment. Furthermore, culturing NSCs on increasingly stiff ECMs enhances RhoA and Cdc42 activation, increases NSC stiffness, and suppresses neurogenesis. Likewise, inhibiting RhoA and Cdc42 or downstream regulators of cellular contractility rescues NSCs from stiff matrix- and Rho GTPase-induced neurosuppression. Importantly, Rho GTPase expression and ECM stiffness do not alter proliferation or apoptosis rates indicating that an instructive rather than selective mechanism modulates lineage distributions. Finally, in the adult brain, RhoA activation in hippocampal progenitors suppresses neurogenesis, analogous to its effect in vitro. These results establish Rho GTPase-based mechanotransduction and cellular stiffness as biophysical regulators of NSC fate in vitro and RhoA as an important regulatory protein in the hippocampal stem cell niche.