940 resultados para Diagnostic,


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- This paper presents a validation proposal for development of diagnostic and prognostic algorithms for SF6 puffer circuit-breakers reproduced from actual site waveforms. The re-ignition/restriking rates are duplicated in given circuits and the cumulative energy dissipated in interrupters by the restriking currents. The targeted objective is to provide a simulated database for diagnosis of re-ignition/restrikes relating to the phase to earth voltage and the number of re-ignition/restrikes as well as estimating the remaining life of SF6 circuit-breakers. The model-based diagnosis of a tool will be useful in monitoring re-ignition/restrikes as well as predicting a nozzle’s lifetime. This will help ATP users with practical study cases and component data compilation for shunt reactor switching and capacitor switching. This method can be easily applied with different data for the different dielectric curves of circuit breakers and networks. This paper presents modelling details and some of the available cases, required project support, the validation proposal, the specific plan for implementation and the propsed main contributions.

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Durability issues of reinforced concrete construction cost millions of dollars in repair or demolition. Identification of the causes of degradation and a prediction of service life based on experience, judgement and local knowledge has limitations in addressing all the associated issues. The objective of this CRC CI research project is to develop a tool that will assist in the interpretation of the symptoms of degradation of concrete structures, estimate residual capacity and recommend cost effective solutions. This report is a documentation of the research undertaken in connection with this project. The primary focus of this research is centred on the case studies provided by Queensland Department of Main Roads (QDMR) and Brisbane City Council (BCC). These organisations are endowed with the responsibility of managing a huge volume of bridge infrastructure in the state of Queensland, Australia. The main issue to be addressed in managing these structures is the deterioration of bridge stock leading to a reduction in service life. Other issues such as political backlash, public inconvenience, approach land acquisitions are crucial but are not within the scope of this project. It is to be noted that deterioration is accentuated by aggressive environments such as salt water, acidic or sodic soils. Carse, 2005, has noted that the road authorities need to invest their first dollars in understanding their local concretes and optimising the durability performance of structures and then look at potential remedial strategies.

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Dasheen mosaic potyvirus (DsMV) is an important virus affecting taro. The virus has been found wherever taro is grown and infects both the edible and ornamental aroids, causing yield losses of up to 60%. The presence of DsMV, and other viruses,prevents the international movement of taro germplasm between countries. This has a significant negative impact on taro production in many countries due to the inability to access improved taro lines produced in breeding programs. To overcome this problem, sensitive and reliable virus diagnostic tests need to be developed to enable the indexing of taro germplasm. The aim of this study was to generate an antiserum against a recombinant DsMV coat protein (CP) and to develop a serological-based diagnostic test that would detect Pacific Island isolates of the virus. The CP-coding region of 16 DsMV isolates from Papua New Guinea, Samoa, Solomon Islands, French Polynesia, New Caledonia and Vietnam were amplified,cloned and sequenced. The size of the CP-coding region ranged from 939 to 1038 nucleotides and encoded putative proteins ranged from 313 to 346 amino acids, with the molecular mass ranging from 34 to 38 kDa. Analysis ofthe amino acid sequences revealed the presence of several amino acid motifs typically found in potyviruses,including DAG, WCIE/DN, RQ and AFDF. When the amino acid sequences were compared with each other and the DsMV sequences on the database, the maximum variability was21.9%. When the core region ofthe CP was analysed, the maximum variability dropped to 6% indicating most variability was present in the N terminus. Within seven PNG isolates ofDsMV, the maximum variability was 16.9% and 3.9% over the entire CP-coding region and core region, respectively. The sequence ofPNG isolate P1 was most similar to all other sequences. Phylogenetic analysis indicated that almost all isolates grouped according to their provenance. Further, the seven PNG isolates were grouped according to the region within PNG from which they were obtained. Due to the extensive variability over the entire CP-coding region, the core region ofthe CP ofPNG isolate Pl was cloned into a protein expression vector and expressed as a recombinant protein. The protein was purified by chromatography and SDS-PAGE and used as an antigen to generate antiserum in a rabbit. In western blots, the antiserum reacted with bands of approximately 45-47 kDa in extracts from purified DsMV and from known DsMV -infected plants from PNG; no bands were observed using healthy plant extracts. The antiserum was subsequently incorporated into an indirect ELISA. This procedure was found to be very sensitive and detected DsMV in sap diluted at least 1:1,000. Using both western blot and ELISA formats,the antiserum was able to detect a wide range ofDsMV isolates including those from Australia, New Zealand, Fiji, French Polynesia, New Caledonia, Papua New Guinea, Samoa, Solomon Islands and Vanuatu. These plants were verified to be infected with DsMV by RT-PCR. In specificity tests, the antiserum was also found to react with sap from plants infected with SCMV, PRSV-P, PRSV-W, but not with PVY or CMV -infected plants.

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Background: Patterns of diagnosis and management for men diagnosed with prostate cancer in Queensland, Australia, have not yet been systematically documented and so assumptions of equity are untested. This longitudinal study investigates the association between prostate cancer diagnostic and treatment outcomes and key area-level characteristics and individual-level demographic, clinical and psychosocial factors.---------- Methods/Design: A total of 1064 men diagnosed with prostate cancer between February 2005 and July 2007 were recruited through hospital-based urology outpatient clinics and private practices in the centres of Brisbane, Townsville and Mackay (82% of those referred). Additional clinical and diagnostic information for all 6609 men diagnosed with prostate cancer in Queensland during the study period was obtained via the population-based Queensland Cancer Registry. Respondent data are collected using telephone and self-administered questionnaires at pre-treatment and at 2 months, 6 months, 12 months, 24 months, 36 months, 48 months and 60 months post-treatment. Assessments include demographics, medical history, patterns of care, disease and treatment characteristics together with outcomes associated with prostate cancer, as well as information about quality of life and psychological adjustment. Complementary detailed treatment information is abstracted from participants’ medical records held in hospitals and private treatment facilities and collated with health service utilisation data obtained from Medicare Australia. Information about the characteristics of geographical areas is being obtained from data custodians such as the Australian Bureau of Statistics. Geo-coding and spatial technology will be used to calculate road travel distances from patients’ residences to treatment centres. Analyses will be conducted using standard statistical methods along with multilevel regression models including individual and area-level components.---------- Conclusions: Information about the diagnostic and treatment patterns of men diagnosed with prostate cancer is crucial for rational planning and development of health delivery and supportive care services to ensure equitable access to health services, regardless of geographical location and individual characteristics. This study is a secondary outcome of the randomised controlled trial registered with the Australian New Zealand Clinical Trials Registry (ACTRN12607000233426)

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This paper presents an overview of the CRC for Infrastructure and Engineering Asset Management (CIEAM)’s rotating machine health monitoring project and the status of the research progress. The project focuses on the development of a comprehensive diagnostic tool for condition monitoring and systematic analysis of rotating machinery. Particularly attention focuses on the machine health monitoring of diesel engines, compressors and pumps by using acoustic emission and vibration-based monitoring techniques. The paper also provides a brief summary of the work done by the three main research collaborating partners in the project, namely, Queensland University of Technology (QUT), Curtin University of Technology (CUT) and the University of Western Australia (UWA). Preliminary test and analysis results from this work are also reported in the paper

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Circuit breaker restrikes are unwanted occurrence, which can ultimately lead to breaker. Before 2008, there was little evidence in the literature of monitoring techniques based on restrike measurement and interpretation produced during switching of capacitor banks and shunt reactor banks. In 2008 a non-intrusive radiometric restrike measurement method, as well a restrike hardware detection algorithm was developed. The limitations of the radiometric measurement method are a band limited frequency response as well as limitations in amplitude determination. Current detection methods and algorithms required the use of wide bandwidth current transformers and voltage dividers. A novel non-intrusive restrike diagnostic algorithm using ATP (Alternative Transient Program) and wavelet transforms is proposed. Wavelet transforms are the most common use in signal processing, which is divided into two tests, i.e. restrike detection and energy level based on deteriorated waveforms in different types of restrike. A ‘db5’ wavelet was selected in the tests as it gave a 97% correct diagnostic rate evaluated using a database of diagnostic signatures. This was also tested using restrike waveforms simulated under different network parameters which gave a 92% correct diagnostic responses. The diagnostic technique and methodology developed in this research can be applied to any power monitoring system with slight modification for restrike detection.

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The CIGRE WGs A3.20 and A3.24 identify the requirements of simulation tools to predict various stresses during the development and operational phases of medium voltage vacuum circuit breaker (VCB) testing. This paper reviews the modelling methodology [13], VCB models and tools to identify future research. It will include the application of the VCB model for the impending failure of a VCB using electro-magnetic-transient-program with diagnostic and prognostic algorithm development. The methodology developed for a VCB degradation model is to modify the dielectric equation to cover a restriking period of more than 1 millimetre.

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The topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems.

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In fault detection and diagnostics, limitations coming from the sensor network architecture are one of the main challenges in evaluating a system’s health status. Usually the design of the sensor network architecture is not solely based on diagnostic purposes, other factors like controls, financial constraints, and practical limitations are also involved. As a result, it quite common to have one sensor (or one set of sensors) monitoring the behaviour of two or more components. This can significantly extend the complexity of diagnostic problems. In this paper a systematic approach is presented to deal with such complexities. It is shown how the problem can be formulated as a Bayesian network based diagnostic mechanism with latent variables. The developed approach is also applied to the problem of fault diagnosis in HVAC systems, an application area with considerable modeling and measurement constraints.

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Thirty-four elementary school teachers and 32 education students from Canada rated their reactions towards vignettes describing children who met attention-deficit/hyperactivity disorder (ADHD) symptom criteria that included or did not include the label “ADHD.” “ADHD”-labeled vignettes elicited greater perceptions of the child's impairment as well as more negative emotions and less confidence in the participants, although it also increased participants' willingness to implement treatment interventions. Ratings were similar to vignettes of boys versus girls; however, important differences in ratings between teachers and education students emerged and are discussed. Finally, we investigated the degree to which teachers' professional backgrounds influenced bias based on the label “ADHD.” Training specific to ADHD consistently predicted label bias, whereas teachers' experience working with children with ADHD did not.