902 resultados para POWER SPECTRUM ANALYSIS


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Fault tree analysis (FTA) is presented to model the reliability of a railway traction power system in this paper. First, the construction of fault tree is introduced to integrate components in traction power systems into a fault tree; then the binary decision diagram (BDD) method is used to evaluate fault trees qualitatively and quantitatively. The components contributing to the reliability of overall system are identified with their relative importance through sensitivity analysis. Finally, an AC traction power system is evaluated by the proposed methods.

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Spectrum sensing optimisation techniques maximise the efficiency of spectrum sensing while satisfying a number of constraints. Many optimisation models consider the possibility of the primary user changing activity state during the secondary user's transmission period. However, most ignore the possibility of activity change during the sensing period. The observed primary user signal during sensing can exhibit a duty cycle which has been shown to severely degrade detection performance. This paper shows that (a) the probability of state change during sensing cannot be neglected and (b) the true detection performance obtained when incorporating the duty cycle of the primary user signal can deviate significantly from the results expected with the assumption of no such duty cycle.

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Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

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Continuing monitoring of diesel engine performance is critical for early detection of fault developments in the engine before they materialize and become a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few non intrusive condition monitoring techniques that can be utilized for such tasks. In this experimental study, IAS analysis was employed to estimate the loading condition of a 4-stroke 4-cylinder diesel engine in a laboratory condition. It was shown that IAS analysis can provide useful information about engine speed variation caused by the changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectrum directly associated with the engine firing frequency (at twice the mean shaft revolution speed) can be utilized to estimate the engine loading condition regardless of whether the engine is operating at normal running conditions or in a simulated faulty injector case. The amplitude of this order component follows a clear exponential curve as the loading condition changes. A mathematical relationship was established for the estimation of the engine power output based on the amplitude of the major order component of the measured IAS spectrum.

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Continuing monitoring of diesel engine performance is critical for early detection of fault developments in the engine before they materialize and become a functional failure. Instantaneous crank angular speed (IAS) analysis is one of a few non intrusive condition monitoring techniques that can be utilized for such tasks. In this experimental study, IAS analysis was employed to estimate the loading condition of a 4-stroke 4-cylinder diesel engine in a laboratory condition. It was shown that IAS analysis can provide useful information about engine speed variation caused by the changing piston momentum and crankshaft acceleration during the engine combustion process. It was also found that the major order component of the IAS spectrum directly associated with the engine firing frequency (at twice the mean shaft revolution speed) can be utilized to estimate the engine loading condition regardless of whether the engine is operating at normal running conditions or in a simulated faulty injector case. The amplitude of this order component follows a clear exponential curve as the loading condition changes. A mathematical relationship was established for the estimation of the engine power output based on the amplitude of the major order component of the measured IAS spectrum.

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This paper focuses on the super/subsynchronous operation of the doubly fed induction generator (DFIG) system. The impact of a damping controller on the different modes of operation for the DFIG-based wind generation system is investigated. The coordinated tuning of the damping controller to enhance the damping of the oscillatory modes using bacteria foraging technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The robustness issue of the damping controller is also investigated.

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Load modelling plays an important role in power system dynamic stability assessment. One of the widely used methods in assessing load model impact on system dynamic response is parametric sensitivity analysis. A composite load model-based load sensitivity analysis framework is proposed. It enables comprehensive investigation into load modelling impacts on system stability considering the dynamic interactions between load and system dynamics. The effect of the location of individual as well as patches of composite loads in the vicinity on the sensitivity of the oscillatory modes is investigated. The impact of load composition on the overall sensitivity of the load is also investigated.

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The security of power transfer across a given transmission link is typically a steady state assessment. This paper develops tools to assess machine angle stability as affected by a combination of faults and uncertainty of wind power using probability analysis. The paper elaborates on the development of the theoretical assessment tool and demonstrates its efficacy using single machine infinite bus system.

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Knowledge of cable parameters has been well established but a better knowledge of the environment in which the cables are buried lags behind. Research in Queensland University of Technology has been aimed at obtaining and analysing actual daily field values of thermal resistivity and diffusivity of the soil around power cables. On-line monitoring systems have been developed and installed with a data logger system and buried spheres that use an improved technique to measure thermal resistivity and diffusivity over a short period. Results based on long term continuous field data are given. A probabilistic approach is developed to establish the correlation between the measured field thermal resistivity values and rainfall data from weather bureau records. This data from field studies can reduce the risk in cable rating decisions and provide a basis for reliable prediction of “hot spot” of an existing cable circuit

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Power system operation and planning are facing increasing uncertainties especially with the deregulation process and increasing demand for power. Probabilistic power system stability assessment and probabilistic power system planning have been identified by EPRI as one of the important trends in power system operations and planning. Probabilistic small signal stability assessment studies the impact of system parameter uncertainties on system small disturbance stability characteristics. Researches in this area have covered many uncertainties factors such as controller parameter uncertainties and generation uncertainties. One of the most important factors in power system stability assessment is load dynamics. In this paper, composite load model is used to consider the uncertainties from load parameter uncertainties impact on system small signal stability characteristics. The results provide useful insight into the significant stability impact brought to the system by load dynamics. They can be used to help system operators in system operation and planning analysis.

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This paper focuses on the super/sub-synchronous operation of the doubly fed induction generator (DFIG) system. The impact of a damping controller on the different modes of operation for the DFIG based wind generation system is investigated. The co-ordinated tuning of the damping controller to enhance the damping of the oscillatory modes using bacteria foraging (BF) technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The robustness issue of the damping controller is also investigated

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Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature.

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Pedagogical styles, methods, models, practices or strategies are valued for what they claim they can achieve. In recent times curriculum documents and governments have called for a range of teaching approaches to meet the variety of learner differences and allow students to make more independent decision making in physical education (Hardy and Mawer, 1999). One well known system of categorizing teaching styles is the Mosston and Ashworth’s Spectrum of Teaching Styles (2002). In Queensland, prior to 2005, no research had been conducted on the teaching styles used by teachers of Physical Education. However, many teachers self-reported that they employed a variety of teaching styles depending on the aims and content of the material to be taught (Cothran, et al., 2005). This research, for the first time, collected teacher’s self-reported use of teaching styles and through observations verify the styles that were being used to teach Senior Physical Education in Queensland. More specifically the aims of the research were to determine: a) What teaching styles teachers of Senior Physical Education in Queensland believe they use? i) Were they using a range of teaching styles? ii) Were teachers of Senior Physical Education in Queensland using teaching styles that the Queensland Senior Physical Education Syllabus (2004) required? b) If Mosston and Ashworth’s (2002) Spectrum of Teaching Styles were used to categorise styles observed during the teaching of Senior Physical Education did the styles being used provide opportunities for evaluating as described by the Queensland Senior Physical Education Syllabus (2004)? The research was conducted in two phases. Part A involved use of a questionnaire to determine the teaching styles Queensland teachers of Senior Physical Education reported using and how often they reported using them. The questionnaire was administered to 110 teachers throughout Queensland. The sample was determined from 346 schools teaching Senior Physical Education (in 2006) across the state of Queensland, Australia. 286 questionnaires were sent to 77 non-randomised schools. There were 66 male and 44 female respondents in the sample. A wide range of teaching styles were reportedly used by teachers of Senior Physical Education with Practice Style-Style B, Command Style-Style A and Divergent Discovery Style-Style H, the most reportedly used. The Self-Teaching Style-Style K was reportedly used the least by teachers involved in this study. From the respondents a group of teachers were identified to form the participants for Part B. Part B of the study involved observation of a group of volunteer participants (from those who had completed the questionnaire) who displayed many of the ‘typical’ characteristics, and a cross-section of backgrounds, of teachers of Senior Physical Education in Queensland. In the case of this study, the criteria used to select the group of teachers to be observed teaching were, teaching experience (number of years: 0-4, 5-10 and 11 years and over), gender, geographical location of schools (focused on Brisbane and near area for travel/access purposes), profile of the students at schools (girls, boys or co-educational), nature of school (Government or Private) and the physical activities being taught in a school (activities to reflect all the areas of physical activity outlined within the syllabus). A total of 27 questionnaire respondents from Part A indicated that they were willing to be observed teaching practical lessons. The respondents who volunteered to be involved in Part B of the study came from different regions across the state of Queensland and was not confined to the Brisbane metropolitan area or large cities. From the group of people who volunteered for Part B four came from outside Brisbane and 23 from the Brisbane area. The final observation group of nine participants included eight teachers from the Brisbane area and one from a rural area. The characteristics of the final group included three females and six males from private and public schools with a range of teaching experience in years and a range of physical activities. Four year 12 and five year 11 teachers and their classes were videoed on three occasions as they progressed through an eight – nine week unit of work. This resulted in 24 hours 48 minutes and 20 seconds (or 4465 observations) of video teaching data which was subsequently coded by several researchers (99% interobserver reliability) to determine the teaching styles employed by the participants. This research indicated that, based on Mosston and Ashworth’s (2002) Spectrum of Teaching Styles, teachers of Senior Physical Education in Queensland used predominantly one style to teach 27 observed lessons. This is in sharp contrast to the variety of styles 110 teachers self- reportedly used and in spite of the Queensland Senior Physical Education Syllabus (2004) suggesting a range of specific styles be used. These results are discussed in the context of the Queensland Senior Physical Education Syllabus (2004), teacher knowledge of teaching styles and high-stakes curriculum and external pressures such as national testing and the publication of data from schools in tabloid newspapers. The data and findings in this research provide a rationale for improving teacher knowledge regarding teaching styles and the need for a clear definition of terminology in syllabus documents. Careful examination of the effects that the publishing of school data may have on teaching styles is advised. This research not only collected teacher’s perceptions of the teaching styles they believed they used it also verified these claims through direct observations of the teachers while teaching. These findings are relevant to syllabus writers, teacher educators, policy makers within education and teachers.