109 resultados para synsedimentary faults


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The distribution network reliability can be increased if distributed generators (DGs) are allowed to operate in both grid-connected and islanded operations when the network has a high DG penetration level. However, the current utility regulations do not allow for the islanded operation. The arc faults are the one of the major issues preventing the islanded operation, since the arc will not extinguish if the DGs are not disconnected. In this paper, the effect of a converter interfaced DG on an arc fault is investigated by considering different control strategies for the converter. The foldback current control characteristic is proposed to a converter interfaced DG to achieve quick arc extinction and self-restoration without disconnecting the DG in the event of an arc fault. The results are validated through PSCAD/EMTDC simulations.

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In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

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The study reported here, constitutes a full review of the major geological events that have influenced the morphological development of the southeast Queensland region. Most importantly, it provides evidence that the region’s physiography continues to be geologically ‘active’ and although earthquakes are presently few and of low magnitude, many past events and tectonic regimes continue to be strongly influential over drainage, morphology and topography. Southeast Queensland is typified by highland terrain of metasedimentary and igneous rocks that are parallel and close to younger, lowland coastal terrain. The region is currently situated in a passive margin tectonic setting that is now under compressive stress, although in the past, the region was subject to alternating extensional and compressive regimes. As part of the investigation, the effects of many past geological events upon landscape morphology have been assessed at multiple scales using features such as the location and orientation of drainage channels, topography, faults, fractures, scarps, cleavage, volcanic centres and deposits, and recent earthquake activity. A number of hypotheses for local geological evolution are proposed and discussed. This study has also utilised a geographic information system (GIS) approach that successfully amalgamates the various types and scales of datasets used. A new method of stream ordination has been developed and is used to compare the orientation of channels of similar orders with rock fabric, in a topologically controlled approach that other ordering systems are unable to achieve. Stream pattern analysis has been performed and the results provide evidence that many drainage systems in southeast Queensland are controlled by known geological structures and by past geological events. The results conclude that drainage at a fine scale is controlled by cleavage, joints and faults, and at a broader scale, large river valleys, such as those of the Brisbane River and North Pine River, closely follow the location of faults. These rivers appear to have become entrenched by differential weathering along these planes of weakness. Significantly, stream pattern analysis has also identified some ‘anomalous’ drainage that suggests the orientations of these watercourses are geologically controlled, but by unknown causes. To the north of Brisbane, a ‘coastal drainage divide’ has been recognized and is described here. The divide crosses several lithological units of different age, continues parallel to the coast and prevents drainage from the highlands flowing directly to the coast for its entire length. Diversion of low order streams away from the divide may be evidence that a more recent process may be the driving force. Although there is no conclusive evidence for this at present, it is postulated that the divide may have been generated by uplift or doming associated with mid-Cenozoic volcanism or a blind thrust at depth. Also north of Brisbane, on the D’Aguilar Range, an elevated valley (the ‘Kilcoy Gap’) has been identified that may have once drained towards the coast and now displays reversed drainage that may have resulted from uplift along the coastal drainage divide and of the D’Aguilar blocks. An assessment of the distribution and intensity of recent earthquakes in the region indicates that activity may be associated with ancient faults. However, recent movement on these faults during these events would have been unlikely, given that earthquakes in the region are characteristically of low magnitude. There is, however, evidence that compressive stress is building and being released periodically and ancient faults may be a likely place for this stress to be released. The relationship between ancient fault systems and the Tweed Shield Volcano has also been discussed and it is suggested here that the volcanic activity was associated with renewed faulting on the Great Moreton Fault System during the Cenozoic. The geomorphology and drainage patterns of southeast Queensland have been compared with expected morphological characteristics found at passive and other tectonic settings, both in Australia and globally. Of note are the comparisons with the East Brazilian Highlands, the Gulf of Mexico and the Blue Ridge Escarpment, for example. In conclusion, the results of the study clearly show that, although the region is described as a passive margin, its complex, past geological history and present compressive stress regime provide a more intricate and varied landscape than would be expected along typical passive continental margins. The literature review provides background to the subject and discusses previous work and methods, whilst the findings are presented in three peer-reviewed, published papers. The methods, hypotheses, suggestions and evidence are discussed at length in the final chapter.

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This paper describes protection and control of a microgrid with converter interfaced micro sources. The proposed protection and control scheme consider both grid connected and autonomous operation of the microgrid. A protection scheme, capable of detecting faults effectively in both grid connected and islanded operations is proposed. The main challenge of the protection, due to current limiting state of the converters is overcome by using admittance relays. The relays operate according to the inverse time characteristic based on measured admittance of the line. The proposed scheme isolates the fault from both sides, while downstream side of the microgrid operates in islanding condition. Moreover faults can be detected in autonomous operation. In grid connected mode distributed generators (DG) supply the rated power while in absence of the grid, DGs share the entire power requirement proportional to rating based on output voltage angle droop control. The protection scheme ensures minimum load shedding with isolating the faulted network and DG control provides a smooth islanding and resynchronization operation. The efficacy of coordinated control and protection scheme has been validated through simulation for various operating conditions.

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This paper studies receiver autonomous integrity monitoring (RAIM) algorithms and performance benefits of RTK solutions with multiple-constellations. The proposed method is generally known as Multi-constellation RAIM -McRAIM. The McRAIM algorithms take advantage of the ambiguity invariant character to assist fast identification of multiple satellite faults in the context of multiple constellations, and then detect faulty satellites in the follow-up ambiguity search and position estimation processes. The concept of Virtual Galileo Constellation (VGC) is used to generate useful data sets of dual-constellations for performance analysis. Experimental results from a 24-h data set demonstrate that with GPS&VGC constellations, McRAIM can significantly enhance the detection and exclusion probabilities of two simultaneous faulty satellites in RTK solutions.

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Islanded operation, protection, reclosing and arc extinguishing are some of the challenging issues related to the connection of converter interfaced distributed generators (DGs) into a distribution network. The isolation of upstream faults in grid connected mode and fault detection in islanded mode using overcurrent devices are difficult. In the event of an arc fault, all DGs must be disconnected in order to extinguish the arc. Otherwise, they will continue to feed the fault, thus sustaining the arc. However, the system reliability can be increased by maximising the DG connectivity to the system: therefore, the system protection scheme must ensure that only the faulted segment is removed from the feeder. This is true even in the case of a radial feeder as the DG can be connected at various points along the feeder. In this paper, a new relay scheme is proposed which, along with a novel current control strategy for converter interfaced DGs, can isolate permanent and temporary arc faults. The proposed protection and control scheme can even coordinate with reclosers. The results are validated through PSCAD/EMTDC simulation and MATLAB calculations.

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The Mount Isa Basin is a new concept used to describe the area of Palaeo- to Mesoproterozoic rocks south of the Murphy Inlier and inappropriately described presently as the Mount Isa Inlier. The new basin concept presented in this thesis allows for the characterisation of basin-wide structural deformation, correlation of mineralisation with particular lithostratigraphic and seismic stratigraphic packages, and the recognition of areas with petroleum exploration potential. The northern depositional margin of the Mount Isa Basin is the metamorphic, intrusive and volcanic complex here referred to as the Murphy Inlier (not the "Murphy Tectonic Ridge"). The eastern, southern and western boundaries of the basin are obscured by younger basins (Carpentaria, Eromanga and Georgina Basins). The Murphy Inlier rocks comprise the seismic basement to the Mount Isa Basin sequence. Evidence for the continuity of the Mount Isa Basin with the McArthur Basin to the northwest and the Willyama Block (Basin) at Broken Hill to the south is presented. These areas combined with several other areas of similar age are believed to have comprised the Carpentarian Superbasin (new term). The application of seismic exploration within Authority to Prospect (ATP) 423P at the northern margin of the basin was critical to the recognition and definition of the Mount Isa Basin. The Mount Isa Basin is structurally analogous to the Palaeozoic Arkoma Basin of Illinois and Arkansas in southern USA but, as with all basins it contains unique characteristics, a function of its individual development history. The Mount Isa Basin evolved in a manner similar to many well described, Phanerozoic plate tectonic driven basins. A full Wilson Cycle is recognised and a plate tectonic model proposed. The northern Mount Isa Basin is defined as the Proterozoic basin area northwest of the Mount Gordon Fault. Deposition in the northern Mount Isa Basin began with a rift sequence of volcaniclastic sediments followed by a passive margin drift phase comprising mostly carbonate rocks. Following the rift and drift phases, major north-south compression produced east-west thrusting in the south of the basin inverting the older sequences. This compression produced an asymmetric epi- or intra-cratonic clastic dominated peripheral foreland basin provenanced in the south and thinning markedly to a stable platform area (the Murphy Inlier) in the north. The fmal major deformation comprised east-west compression producing north-south aligned faults that are particularly prominent at Mount Isa. Potential field studies of the northern Mount Isa Basin, principally using magnetic data (and to a lesser extent gravity data, satellite images and aerial photographs) exhibit remarkable correlation with the reflection seismic data. The potential field data contributed significantly to the unravelling of the northern Mount Isa Basin architecture and deformation. Structurally, the Mount Isa Basin consists of three distinct regions. From the north to the south they are the Bowthorn Block, the Riversleigh Fold Zone and the Cloncurry Orogen (new names). The Bowthom Block, which is located between the Elizabeth Creek Thrust Zone and the Murphy Inlier, consists of an asymmetric wedge of volcanic, carbonate and clastic rocks. It ranges from over 10 000 m stratigraphic thickness in the south to less than 2000 min the north. The Bowthorn Block is relatively undeformed: however, it contains a series of reverse faults trending east-west that are interpreted from seismic data to be down-to-the-north normal faults that have been reactivated as thrusts. The Riversleigh Fold Zone is a folded and faulted region south of the Bowthorn Block, comprising much of the area formerly referred to as the Lawn Hill Platform. The Cloncurry Orogen consists of the area and sequences equivalent to the former Mount Isa Orogen. The name Cloncurry Orogen clearly distinguishes this area from the wider concept of the Mount Isa Basin. The South Nicholson Group and its probable correlatives, the Pilpah Sandstone and Quamby Conglomerate, comprise a later phase of now largely eroded deposits within the Mount Isa Basin. The name South Nicholson Basin is now outmoded as this terminology only applied to the South Nicholson Group unlike the original broader definition in Brown et al. (1968). Cored slimhole stratigraphic and mineral wells drilled by Amoco, Esso, Elf Aquitaine and Carpentaria Exploration prior to 1986, penetrated much of the stratigraphy and intersected both minor oil and gas shows plus excellent potential source rocks. The raw data were reinterpreted and augmented with seismic stratigraphy and source rock data from resampled mineral and petroleum stratigraphic exploration wells for this study. Since 1986, Comalco Aluminium Limited, as operator of a joint venture with Monument Resources Australia Limited and Bridge Oil Limited, recorded approximately 1000 km of reflection seismic data within the basin and drilled one conventional stratigraphic petroleum well, Beamesbrook-1. This work was the first reflection seismic and first conventional petroleum test of the northern Mount Isa Basin. When incorporated into the newly developed foreland basin and maturity models, a grass roots petroleum exploration play was recognised and this led to the present thesis. The Mount Isa Basin was seen to contain excellent source rocks coupled with potential reservoirs and all of the other essential aspects of a conventional petroleum exploration play. This play, although high risk, was commensurate with the enormous and totally untested petroleum potential of the basin. The basin was assessed for hydrocarbons in 1992 with three conventional exploration wells, Desert Creek-1, Argyle Creek-1 and Egilabria-1. These wells also tested and confrrmed the proposed basin model. No commercially viable oil or gas was encountered although evidence of its former existence was found. In addition to the petroleum exploration, indeed as a consequence of it, the association of the extensive base metal and other mineralisation in the Mount Isa Basin with hydrocarbons could not be overlooked. A comprehensive analysis of the available data suggests a link between the migration and possible generation or destruction of hydrocarbons and metal bearing fluids. Consequently, base metal exploration based on hydrocarbon exploration concepts is probably. the most effective technique in such basins. The metal-hydrocarbon-sedimentary basin-plate tectonic association (analogous to Phanerozoic models) is a compelling outcome of this work on the Palaeo- to Mesoproterozoic Mount lsa Basin. Petroleum within the Bowthom Block was apparently destroyed by hot brines that produced many ore deposits elsewhere in the basin.

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Because of the greenhouse gas emissions implications of the market dominating electric hot water systems, governments in Australia have implemented policies and programs to encourage the uptake of solar water heaters (SWHs) in the residential market as part of climate change adaptation and mitigation strategies. The cost-benefit analysis that usually accompanies all government policy and program design could be simplistically reduced to the ratio of expected greenhouse gas reductions of SWH to the cost of a SWH. The national Register of Solar Water Heaters specifies how many renewable energy certificates (RECs) are allocated to complying SWHs according to their expected performance, and hence greenhouse gas reductions, in different climates. Neither REC allocations nor rebates are tied to actual performance of systems. This paper examines the performance of instantaneous gas-boosted solar water heaters installed in new residences in a housing estate in south-east Queensland in the period 2007 – 2010. The evidence indicates systemic failures in installation practices, resulting in zero solar performance or dramatic underperformance (estimated average 43% solar contribution). The paper will detail the faults identified, and how these faults were eventually diagnosed and corrected. The impacts of these system failures on end-use consumers are discussed before concluding with a brief overview of areas where further research is required in order to more fully understand whole of supply chain implications.

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This paper discusses diesel engine condition monitoring (CM) using acoustic emissions (AE) as well as some of the commonly encountered diesel engine problems. Also discussed are some of the underlying combustion related faults and the methods used in past studies to simulate diesel engine faults. The initial test involved an experimental simulation of two common combustion related diesel engine faults, namely diesel knock and misfire. These simulated faults represent the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank angle encoder and top-dead centre (TDC) signals. Using these signals, it was possible to characterise the effect of different combustion conditions and hence, various diesel engine in-cylinder pressure profiles.

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This paper presents techniques which can be viewed as pre-processing step towards diagnosis of faults in a small size multi-cylinder diesel engine. Preliminary analysis of the acoustic emission (AE) signals is outlined, including time-frequency analysis, selection of optimum frequency band. Some results of applying mean field independent component analysis (MFICA) to separate the AE root mean square (RMS) signals are also outlined. The results on separation of RMS signals show this technique has the potential of increasing the probability to successfully identify the AE events associated with the various mechanical events.

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A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

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The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation and can also improve productivity and enhance system’s safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. Although a variety of prognostic methodologies have been reported recently, their application in industry is still relatively new and mostly focused on the prediction of specific component degradations. Furthermore, they required significant and sufficient number of fault indicators to accurately prognose the component faults. Hence, sufficient usage of health indicators in prognostics for the effective interpretation of machine degradation process is still required. Major challenges for accurate longterm prediction of remaining useful life (RUL) still remain to be addressed. Therefore, continuous development and improvement of a machine health management system and accurate long-term prediction of machine remnant life is required in real industry application. This thesis presents an integrated diagnostics and prognostics framework based on health state probability estimation for accurate and long-term prediction of machine remnant life. In the proposed model, prior empirical (historical) knowledge is embedded in the integrated diagnostics and prognostics system for classification of impending faults in machine system and accurate probability estimation of discrete degradation stages (health states). The methodology assumes that machine degradation consists of a series of degraded states (health states) which effectively represent the dynamic and stochastic process of machine failure. The estimation of discrete health state probability for the prediction of machine remnant life is performed using the ability of classification algorithms. To employ the appropriate classifier for health state probability estimation in the proposed model, comparative intelligent diagnostic tests were conducted using five different classifiers applied to the progressive fault data of three different faults in a high pressure liquefied natural gas (HP-LNG) pump. As a result of this comparison study, SVMs were employed in heath state probability estimation for the prediction of machine failure in this research. The proposed prognostic methodology has been successfully tested and validated using a number of case studies from simulation tests to real industry applications. The results from two actual failure case studies using simulations and experiments indicate that accurate estimation of health states is achievable and the proposed method provides accurate long-term prediction of machine remnant life. In addition, the results of experimental tests show that the proposed model has the capability of providing early warning of abnormal machine operating conditions by identifying the transitional states of machine fault conditions. Finally, the proposed prognostic model is validated through two industrial case studies. The optimal number of health states which can minimise the model training error without significant decrease of prediction accuracy was also examined through several health states of bearing failure. The results were very encouraging and show that the proposed prognostic model based on health state probability estimation has the potential to be used as a generic and scalable asset health estimation tool in industrial machinery.

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This paper discusses diesel engine condition monitoring (CM) using acoustic emissions (AE)as well as some of the commonly encountered diesel engine problems. Also discussed are some of the underlying combustion related faults and the methods used in past studies to simulate diesel engine faults. The initial test involved an experimental simulation of two common combustion related diesel engine faults, namely diesel knock and misfire. These simulated faults represent the first step towards a comprehensive investigation and analysis into the characteristics of acoustic emission signals arising from combustion related diesel engine faults. Data corresponding to different engine running conditions was captured using in-cylinder pressure, vibration and acoustic emission transducers along with both crank angle encoder and top-dead centre (TDC) signals. Using these signals, it was possible to characterise the effect of different combustion conditions and hence, various diesel engine in-cylinder pressure profiles.

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The design of the Kyoto Protocol renders it incapable of effectively responding to the problem of anthropogenic climate change. Therefore, this article explores the opportunity to construct a new, principled legal approach to respond to climate change that is premised on nationally derived legal responses. To do so, this article considers the theoretical foundation of the international legal response to climate change – Hardin's "The Tragedy of the Commons‟ – and the systemic design faults of the Kyoto Protocol. This article also suggests four principles – a judicious mix of legal instruments, flexibility, intrinsic legal coherence, and quantifiable and achievable targets for the reduction of greenhouse gas intensity – that are necessary to guide the creation of a nationally derived legal response to climate change. This approach is intended to provide the catalyst for new bilateral and multilateral arrangements that can, with the passing of time, generate sufficient momentum to drive the creation of a new and effective cooperative international legal framework to mitigate anthropogenic climate change.

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This paper proposes a novel approach for identifying risks in executable business processes and detecting them at run time. The approach considers risks in all phases of the business process management lifecycle, and is realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of faults to occur. Both historical and current execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a process automation suite to prompt the results to the user who may take remedial actions. The proposed architecture has been implemented in the YAWL system and its performance has been evaluated in practice.