328 resultados para velocity estimation
Resumo:
A comprehensive one-dimensional meanline design approach for radial inflow turbines is described in the present work. An original code was developed in Python that takes a novel approach to the automatic selection of feasible machines based on pre-defined performance or geometry characteristics for a given application. It comprises a brute-force search algorithm that traverses the entire search space based on key non-dimensional parameters and rotational speed. In this study, an in-depth analysis and subsequent implementation of relevant loss models as well as selection criteria for radial inflow turbines is addressed. Comparison with previously published designs, as well as other available codes, showed good agreement. Sample (real and theoretical) test cases were trialed and results showed good agreement when compared to other available codes. The presented approach was found to be valid and the model was found to be a useful tool with regards to the preliminary design and performance estimation of radial inflow turbines, enabling its integration with other thermodynamic cycle analysis and three-dimensional blade design codes.
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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 safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an 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. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.
Resumo:
In recent years, some models have been proposed for the fault section estimation and state identification of unobserved protective relays (FSE-SIUPR) under the condition of incomplete state information of protective relays. In these models, the temporal alarm information from a faulted power system is not well explored although it is very helpful in compensating the incomplete state information of protective relays, quickly achieving definite fault diagnosis results and evaluating the operating status of protective relays and circuit breakers in complicated fault scenarios. In order to solve this problem, an integrated optimization mathematical model for the FSE-SIUPR, which takes full advantage of the temporal characteristics of alarm messages, is developed in the framework of the well-established temporal constraint network. With this model, the fault evolution procedure can be explained and some states of unobserved protective relays identified. The model is then solved by means of the Tabu search (TS) and finally verified by test results of fault scenarios in a practical power system.
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This paper details the progress to date, toward developing a small autonomous helicopter. We describe system architecture, avionics, visual state estimation, custom IMU design, aircraft modelling, as well as various linear and neuro/fuzzy control algorithms. Experimental results are presented for state estimation using fused stereo vision and IMU data, heading control, and attitude control. FAM attitude and velocity controllers have been shown to be effective in simulation.
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Population-representative data for dioxin and PCB congener concentrations are available for the Australian population based on measurements in age- and gender-specific serum pools.1 Such data provide a basis for characterizing the mean concentrations of these compounds in the population, but do not provide information on the inter-individual variation in serum concentrations that may exist in the population within an age- and gender-specific group. Such variation may occur due to inter-individual differences in long-term exposure levels or elimination rates. Reference values are estimates of upper percentiles (often the 95th percentile) of measured values in a defined population that can be used to evaluate data from individuals in the population in order to identify concentrations that are elevated, for example, from occupational exposures.2 The objective of this analysis is to estimate reference values corresponding to the 95th percentile (RV95s) for Australia on an age-specific basis for individual dioxin-like congeners based on measurements in serum pools from Toms and Mueller (2010).
Resumo:
A routine activity for a sports dietitian is to estimate energy and nutrient intake from an athlete's self-reported food intake. Decisions made by the dietitian when coding a food record are a source of variability in the data. The aim of the present study was to determine the variability in estimation of the daily energy and key nutrient intakes of elite athletes, when experienced coders analyzed the same food record using the same database and software package. Seven-day food records from a dietary survey of athletes in the 1996 Australian Olympic team were randomly selected to provide 13 sets of records, each set representing the self-reported food intake of an endurance, team, weight restricted, and sprint/power athlete. Each set was coded by 3-5 members of Sports Dietitians Australia, making a total of 52 athletes, 53 dietitians, and 1456 athlete-days of data. We estimated within- and between- athlete and dietitian variances for each dietary nutrient using mixed modeling, and we combined the variances to express variability as a coefficient of variation (typical variation as a percent of the mean). Variability in the mean of 7-day estimates of a nutrient was 2- to 3-fold less than that of a single day. The variability contributed by the coder was less than the true athlete variability for a 1-day record but was of similar magnitude for a 7-day record. The most variable nutrients (e.g., vitamin C, vitamin A, cholesterol) had approximately 3-fold more variability than least variable nutrients (e.g., energy, carbohydrate, magnesium). These athlete and coder variabilities need to be taken into account in dietary assessment of athletes for counseling and research.
Resumo:
In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.
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This study evaluated effects of defensive pressure on running velocity in footballers during the approach to kick a stationary football. Approach velocity and ball speed/accuracy data were recorded from eight football youth academy participants (15.25, SD=0.46 yrs). Participants were required to run to a football to cross it to a receiver to score against a goal-keeper. Defensive pressure was manipulated across three counterbalanced conditions: defender-absent (DA); defender-far (DF) and defender-near (DN). Pass accuracy (percentages of a total of 32 trials with 95% confidence limits in parenthesis) did not significantly reduce under changing defensive pressure: DA, 78% (55–100%); DF, 78% (61–96%); DN, 59% (40–79%). Ball speed (m·s−1) significantly reduced as defensive pressure was included and increased: DA, 23.10 (22.38–23.83); DF, 20.40 (19.69–21.11); DN, 19.22 (18.51–19.93). When defensive pressure was introduced, average running velocity of attackers did not change significantly: DA versus DF (m·s−1), 5.40 (5.30–5.51) versus 5.41 (5.34–5.48). Scaling defender starting positions closer to the start position of the attacker (DN) significantly increased average running velocity relative to the DA and DF conditions, 5.60 (5.50–5.71). In the final approach footfalls, all conditions significantly differed: DA, 5.69 (5.35–6.03); DF, 6 .22 (5.93–6.50); DN, 6.52 (6.23–6.80). Data suggested that approach velocity is constrained by both presence and initial distance of the defender during task performance. Implications are that the expression of kicking behaviour is specific to a performance context and some movement regulation features will not emerge unless a defender is present as a task constraint in practice.
Resumo:
Bus travel time estimation and prediction are two important modelling approaches which could facilitate transit users in using and transit providers in managing the public transport network. Bus travel time estimation could assist transit operators in understanding and improving the reliability of their systems and attracting more public transport users. On the other hand, bus travel time prediction is an important component of a traveller information system which could reduce the anxiety and stress for the travellers. This paper provides an insight into the characteristic of bus in traffic and the factors that influence bus travel time. A critical overview of the state-of-the-art in bus travel time estimation and prediction is provided and the needs for research in this important area are highlighted. The possibility of using Vehicle Identification Data (VID) for studying the relationship between bus and cars travel time is also explored.
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This paper deals with causal effect estimation strategies in highly heterogeneous empirical settings such as entrepreneurship. We argue that the clearer used of modern tools developed to deal with the estimation of causal effects in combination with our analysis of different sources of heterogeneity in entrepreneurship can lead to entrepreneurship with higher internal validity. We specifically lend support from the counterfactual logic and modern research of estimation strategies for causal effect estimation.
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This report is the second deliverable of the Real Time and Predictive Traveller Information project and the first deliverable of the Freeway Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Freeway Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for Freeway traffic. The objective of this report is to review the literature pertaining to travel time estimation and prediction models for freeway traffic.
Resumo:
This report is the fourth deliverable of the Real Time and Predictive Traveller Information project and the first deliverable of the Arterial Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Arterial Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for arterial traffic. The objective of this report is to review the literature pertaining to travel time estimation and prediction models for arterial traffic.
Resumo:
This report is the eight deliverable of the Real Time and Predictive Traveller Information project and the third deliverable of the Arterial Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Arterial Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for arterial traffic. Brisbane arterial network is highly equipped with Bluetooth MAC Scanners, which can provide travel time information. Literature is limited with the knowledge on the Bluetooth protocol based data acquisition process and accuracy and reliability of the analysis performed using the data. This report expands the body of knowledge surrounding the use of data from Bluetooth MAC Scanner (BMS) as a complementary traffic data source. A multi layer simulation model named Traffic and Communication Simulation (TCS) is developed. TCS is utilised to model the theoretical properties of the BMS data and analyse the accuracy and reliability of travel time estimation using the BMS data.
Resumo:
Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.