981 resultados para phasor measurement unit (PMU)


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Near ground maneuvers, such as hover, approach and landing, are key elements of autonomy in unmanned aerial vehicles. Such maneuvers have been tackled conventionally by measuring or estimating the velocity and the height above the ground often using ultrasonic or laser range finders. Near ground maneuvers are naturally mastered by flying birds and insects as objects below may be of interest for food or shelter. These animals perform such maneuvers efficiently using only the available vision and vestibular sensory information. In this paper, the time-to-contact (Tau) theory, which conceptualizes the visual strategy with which many species are believed to approach objects, is presented as a solution for Unmanned Aerial Vehicles (UAV) relative ground distance control. The paper shows how such an approach can be visually guided without knowledge of height and velocity relative to the ground. A control scheme that implements the Tau strategy is developed employing only visual information from a monocular camera and an inertial measurement unit. To achieve reliable visual information at a high rate, a novel filtering system is proposed to complement the control system. The proposed system is implemented on-board an experimental quadrotor UAV and shown not only to successfully land and approach ground, but also to enable the user to choose the dynamic characteristics of the approach. The methods presented in this paper are applicable to both aerial and space autonomous vehicles.

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Near-ground maneuvers, such as hover, approach, and landing, are key elements of autonomy in unmanned aerial vehicles. Such maneuvers have been tackled conventionally by measuring or estimating the velocity and the height above the ground, often using ultrasonic or laser range finders. Near-ground maneuvers are naturally mastered by flying birds and insects because objects below may be of interest for food or shelter. These animals perform such maneuvers efficiently using only the available vision and vestibular sensory information. In this paper, the time-tocontact (tau) theory, which conceptualizes the visual strategy with which many species are believed to approach objects, is presented as a solution for relative ground distance control for unmanned aerial vehicles. The paper shows how such an approach can be visually guided without knowledge of height and velocity relative to the ground. A control scheme that implements the tau strategy is developed employing only visual information from a monocular camera and an inertial measurement unit. To achieve reliable visual information at a high rate, a novel filtering system is proposed to complement the control system. The proposed system is implemented onboard an experimental quadrotor unmannedaerial vehicle and is shown to not only successfully land and approach ground, but also to enable the user to choose the dynamic characteristics of the approach. The methods presented in this paper are applicable to both aerial and space autonomous vehicles.

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Traditionally, the control system of a modern teleoperated mobile robot consists of one or more two-dimensional joysticks placed on a control interface. While this simplistic interface allows an operator to remotely drive the platform, feedback is limited to visual information supplied by on-board cameras. Significant advances in the field of haptics have the potential to meaningfully enhance situational awareness of a remote robot. The focus of this research is the augmentation of Deakin University's OzBot trade MkIV mobile platform to include haptic control methodologies. Utilising the platform's inertial measurement unit, a remote operator has the ability to gain knowledge of the vehicle's operating performance and terrain while supplying a finer level of control to the drive motors. Our development of a generic multi-platform ActiveX allows the easy implementation of haptic force feedback to many computer based robot controllers. Furthermore, development of communication protocols has progressed with Joint Architecture for Unmanned Systems (JAUS) compliance in mind. The haptic force control algorithms are presented along with results highlighting the benefits of haptic operator feedback on the MklV OzBot trade chassis.

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Introduction: A systematic approach to managing the training of elite athletes is supported by accurate training load measurement. However, quantifying the training of elite Australian rowers is complex due to unique challenges: 1) the multi-centre, multi-state structure of the national program; 2) the variety of training undertaken, incorporating rowing-specific and non-specific modalities, with continuous and interval efforts that span the full intensity spectrum; and 3) the limitations of existing quantification methods for capturing total training loads undertaken from varied training. These challenges highlighted a need to create a consistent, location-independent framework for prescribing training in elite rowing, with a capacity to account for varied training. Methods: An in-house proprietary measure (the T2minute method) was developed at the National Rowing Centre of Excellence (NRCE), as a collaborative project between sport scientists and national squad coaches. The design phase was informed by assessments of the existing training measures, and built upon standardised intensity zones established at the Australian Institute of Sport. A common measurement unit was chosen: one T2minute equates to one minute of on-water single scull rowing at T2 intensity (∼60–72% VO2max). Each intensity zone was assigned a weighting factor according to the curvilinear relationship between power output, intensity, and blood lactate response. Each training mode was assigned a weighting factor based on whether coaches perceived it to be “harder” or “easier” than onwater rowing. With coaches’ feedback, the method was refined over a period of five months. The T2minute method was implemented as the core framework for prescribing training for elite Australian rowers throughout the 2009–2012 Olympic cycle. Results: The implementation of the T2minute method successfully established consistency with training prescription and monitoring practices within the NRCE high performance program. The national roll out this method has influenced rowing training methodology at elite and sub-elite levels in Australia. Since implementation, the method has undergone scientific validation. Further research is underway, utilising the method to explore complex relationships between rowers’ training and performance outcomes. Conclusion: The T2minute method is a novel approach that allows rowing coaches and sport scientists to utilise one consistent system to quantify load from varied training. Its implementation represents a considerable achievement in establishing a common framework for managing the training process within a complex organisational structure. This collaborative approach used to develop the T2minute method provides unique insight into the important considerations and practical challenges of applying training science to enhance elite sport performance.

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Development and implementation of a novel measure for quantifying training loads in rowing: The T2minute method. J Strength Cond Res 28(4): 1172–1180, 2014—The systematic management of training requires accurate training load measurement. However, quantifying the training of elite Australian rowers is challenging because of (a) the multicenter, multistate structure of the national program; (b) the variety of training undertaken; and (c) the limitations of existing methods for quantifying the loads accumulated from varied training formats. Therefore, the purpose of this project was to develop a new measure for quantifying training loads in rowing (the T2minute method). Sport scientists and senior coaches at the National Rowing Center of Excellence collaborated to develop the measure, which incorporates training duration, intensity, and mode to quantify a single index of training load. To account for training at different intensities, the method uses standardized intensity zones (T zones) established at the Australian Institute of Sport. Each zone was assigned a weighting factor according to the curvilinear relationship between power output and blood lactate response. Each training mode was assigned a weighting factor based on whether coaches perceived it to be “harder” or “easier” than on-water rowing. A common measurement unit, the T2minute, was defined to normalize sessions in different modes to a single index of load; one T2minute is equivalent to 1 minute of on-water single scull rowing at T2 intensity (approximately 60–72% V[Combining Dot Above]O2max). The T2minute method was successfully implemented to support national training strategies in Australian high performance rowing. By incorporating duration, intensity, and mode, the T2minute method extends the concepts that underpin current load measures, providing 1 consistent system to quantify loads from varied training formats.

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In this Thesis, the development of the dynamic model of multirotor unmanned aerial vehicle with vertical takeoff and landing characteristics, considering input nonlinearities and a full state robust backstepping controller are presented. The dynamic model is expressed using the Newton-Euler laws, aiming to obtain a better mathematical representation of the mechanical system for system analysis and control design, not only when it is hovering, but also when it is taking-off, or landing, or flying to perform a task. The input nonlinearities are the deadzone and saturation, where the gravitational effect and the inherent physical constrains of the rotors are related and addressed. The experimental multirotor aerial vehicle is equipped with an inertial measurement unit and a sonar sensor, which appropriately provides measurements of attitude and altitude. A real-time attitude estimation scheme based on the extended Kalman filter using quaternions was developed. Then, for robustness analysis, sensors were modeled as the ideal value with addition of an unknown bias and unknown white noise. The bounded robust attitude/altitude controller were derived based on globally uniformly practically asymptotically stable for real systems, that remains globally uniformly asymptotically stable if and only if their solutions are globally uniformly bounded, dealing with convergence and stability into a ball of the state space with non-null radius, under some assumptions. The Lyapunov analysis technique was used to prove the stability of the closed-loop system, compute bounds on control gains and guaranteeing desired bounds on attitude dynamics tracking errors in the presence of measurement disturbances. The controller laws were tested in numerical simulations and in an experimental hexarotor, developed at the UFRN Robotics Laboratory

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Phasor Measurement Units (PMUs) optimized allocation allows control, monitoring and accurate operation of electric power distribution systems, improving reliability and service quality. Good quality and considerable results are obtained for transmission systems using fault location techniques based on voltage measurements. Based on these techniques and performing PMUs optimized allocation it is possible to develop an electric power distribution system fault locator, which provides accurate results. The PMUs allocation problem presents combinatorial features related to devices number that can be allocated, and also probably places for allocation. Tabu search algorithm is the proposed technique to carry out PMUs allocation. This technique applied in a 141 buses real-life distribution urban feeder improved significantly the fault location results. © 2004 IEEE.

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Pós-graduação em Engenharia Mecânica - FEIS

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Pós-graduação em Ciências Cartográficas - FCT

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Healthcare, Human Computer Interfaces (HCI), Security and Biometry are the most promising application scenario directly involved in the Body Area Networks (BANs) evolution. Both wearable devices and sensors directly integrated in garments envision a word in which each of us is supervised by an invisible assistant monitoring our health and daily-life activities. New opportunities are enabled because improvements in sensors miniaturization and transmission efficiency of the wireless protocols, that achieved the integration of high computational power aboard independent, energy-autonomous, small form factor devices. Application’s purposes are various: (I) data collection to achieve off-line knowledge discovery; (II) user notification of his/her activities or in case a danger occurs; (III) biofeedback rehabilitation; (IV) remote alarm activation in case the subject need assistance; (V) introduction of a more natural interaction with the surrounding computerized environment; (VI) users identification by physiological or behavioral characteristics. Telemedicine and mHealth [1] are two of the leading concepts directly related to healthcare. The capability to borne unobtrusiveness objects supports users’ autonomy. A new sense of freedom is shown to the user, not only supported by a psychological help but a real safety improvement. Furthermore, medical community aims the introduction of new devices to innovate patient treatments. In particular, the extension of the ambulatory analysis in the real life scenario by proving continuous acquisition. The wide diffusion of emerging wellness portable equipment extended the usability of wearable devices also for fitness and training by monitoring user performance on the working task. The learning of the right execution techniques related to work, sport, music can be supported by an electronic trainer furnishing the adequate aid. HCIs made real the concept of Ubiquitous, Pervasive Computing and Calm Technology introduced in the 1988 by Marc Weiser and John Seeley Brown. They promotes the creation of pervasive environments, enhancing the human experience. Context aware, adaptive and proactive environments serve and help people by becoming sensitive and reactive to their presence, since electronics is ubiquitous and deployed everywhere. In this thesis we pay attention to the integration of all the aspects involved in a BAN development. Starting from the choice of sensors we design the node, configure the radio network, implement real-time data analysis and provide a feedback to the user. We present algorithms to be implemented in wearable assistant for posture and gait analysis and to provide assistance on different walking conditions, preventing falls. Our aim, expressed by the idea to contribute at the development of a non proprietary solutions, driven us to integrate commercial and standard solutions in our devices. We use sensors available on the market and avoided to design specialized sensors in ASIC technologies. We employ standard radio protocol and open source projects when it was achieved. The specific contributions of the PhD research activities are presented and discussed in the following. • We have designed and build several wireless sensor node providing both sensing and actuator capability making the focus on the flexibility, small form factor and low power consumption. The key idea was to develop a simple and general purpose architecture for rapid analysis, prototyping and deployment of BAN solutions. Two different sensing units are integrated: kinematic (3D accelerometer and 3D gyroscopes) and kinetic (foot-floor contact pressure forces). Two kind of feedbacks were implemented: audio and vibrotactile. • Since the system built is a suitable platform for testing and measuring the features and the constraints of a sensor network (radio communication, network protocols, power consumption and autonomy), we made a comparison between Bluetooth and ZigBee performance in terms of throughput and energy efficiency. Test in the field evaluate the usability in the fall detection scenario. • To prove the flexibility of the architecture designed, we have implemented a wearable system for human posture rehabilitation. The application was developed in conjunction with biomedical engineers who provided the audio-algorithms to furnish a biofeedback to the user about his/her stability. • We explored off-line gait analysis of collected data, developing an algorithm to detect foot inclination in the sagittal plane, during walk. • In collaboration with the Wearable Lab – ETH, Zurich, we developed an algorithm to monitor the user during several walking condition where the user carry a load. The remainder of the thesis is organized as follows. Chapter I gives an overview about Body Area Networks (BANs), illustrating the relevant features of this technology and the key challenges still open. It concludes with a short list of the real solutions and prototypes proposed by academic research and manufacturers. The domain of the posture and gait analysis, the methodologies, and the technologies used to provide real-time feedback on detected events, are illustrated in Chapter II. The Chapter III and IV, respectively, shown BANs developed with the purpose to detect fall and monitor the gait taking advantage by two inertial measurement unit and baropodometric insoles. Chapter V reports an audio-biofeedback system to improve balance on the information provided by the use centre of mass. A walking assistant based on the KNN classifier to detect walking alteration on load carriage, is described in Chapter VI.

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Tracking activities during daily life and assessing movement parameters is essential for complementing the information gathered in confined environments such as clinical and physical activity laboratories for the assessment of mobility. Inertial measurement units (IMUs) are used as to monitor the motion of human movement for prolonged periods of time and without space limitations. The focus in this study was to provide a robust, low-cost and an unobtrusive solution for evaluating human motion using a single IMU. First part of the study focused on monitoring and classification of the daily life activities. A simple method that analyses the variations in signal was developed to distinguish two types of activity intervals: active and inactive. Neural classifier was used to classify active intervals; the angle with respect to gravity was used to classify inactive intervals. Second part of the study focused on extraction of gait parameters using a single inertial measurement unit (IMU) attached to the pelvis. Two complementary methods were proposed for gait parameters estimation. First method was a wavelet based method developed for the estimation of gait events. Second method was developed for estimating step and stride length during level walking using the estimations of the previous method. A special integration algorithm was extended to operate on each gait cycle using a specially designed Kalman filter. The developed methods were also applied on various scenarios. Activity monitoring method was used in a PRIN’07 project to assess the mobility levels of individuals living in a urban area. The same method was applied on volleyball players to analyze the fitness levels of them by monitoring their daily life activities. The methods proposed in these studies provided a simple, unobtrusive and low-cost solution for monitoring and assessing activities outside of controlled environments.

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Despite several clinical tests that have been developed to qualitatively describe complex motor tasks by functional testing, these methods often depend on clinicians' interpretation, experience and training, which make the assessment results inconsistent, without the precision required to objectively assess the effect of the rehabilitative intervention. A more detailed characterization is required to fully capture the various aspects of motor control and performance during complex movements of lower and upper limbs. The need for cost-effective and clinically applicable instrumented tests would enable quantitative assessment of performance on a subject-specific basis, overcoming the limitations due to the lack of objectiveness related to individual judgment, and possibly disclosing subtle alterations that are not clearly visible to the observer. Postural motion measurements at additional locations, such as lower and upper limbs and trunk, may be necessary in order to obtain information about the inter-segmental coordination during different functional tests involved in clinical practice. With these considerations in mind, this Thesis aims: i) to suggest a novel quantitative assessment tool for the kinematics and dynamics evaluation of a multi-link kinematic chain during several functional motor tasks (i.e. squat, sit-to-stand, postural sway), using one single-axis accelerometer per segment, ii) to present a novel quantitative technique for the upper limb joint kinematics estimation, considering a 3-link kinematic chain during the Fugl-Meyer Motor Assessment and using one inertial measurement unit per segment. The suggested methods could have several positive feedbacks from clinical practice. The use of objective biomechanical measurements, provided by inertial sensor-based technique, may help clinicians to: i) objectively track changes in motor ability, ii) provide timely feedback about the effectiveness of administered rehabilitation interventions, iii) enable intervention strategies to be modified or changed if found to be ineffective, and iv) speed up the experimental sessions when several subjects are asked to perform different functional tests.

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L’analisi del cammino è uno strumento in grado di fornire importanti informazioni sul ciclo del passo; in particolare è fondamentale per migliorare le conoscenze biomeccaniche del cammino, sia normale che patologico, e su come questo viene eseguito dai singoli soggetti. I parametri spazio temporali del passo rappresentano alcuni degli indici più interessanti per caratterizzare il cammino ed il passo nelle sue diverse fasi. Essi permettono infatti il confronto e il riconoscimento di patologie e disturbi dell’andatura. Negli ultimi anni è notevolmente aumentato l’impiego di sensori inerziali (Inertial Measurement Unit, IMU), che comprendono accelerometri, giroscopi e magnetometri. Questi dispositivi, utilizzati singolarmente o insieme, possono essere posizionati direttamente sul corpo dei pazienti e sono in grado fornire, rispettivamente, il segnale di accelerazione, di velocità angolare e del campo magnetico terrestre. A partire da questi segnali, ottenuti direttamente dal sensore, si è quindi cercato di ricavare i parametri caratteristici dell’andatura, per valutare il cammino anche al di fuori dell’ambiente di laboratorio. Vista la loro promettente utilità e la potenziale vasta applicabilità nell’analisi del ciclo del cammino; negli ultimi anni un vasto settore della ricerca scientifica si è dedicata allo sviluppo di algoritmi e metodi per l’estrazione dei parametri spazio temporali a partire da dati misurati mediante sensori inerziali. Data la grande quantità di lavori pubblicati e di studi proposti è emersa la necessità di fare chiarezza, riassumendo e confrontando i metodi conosciuti, valutando le prestazioni degli algoritmi, l’accuratezza dei parametri ricavati, anche in base alla tipologia del sensore e al suo collocamento sull’individuo, e gli eventuali limiti. Lo scopo della presente tesi è quindi l’esecuzione di una revisione sistematica della letteratura riguardante la stima dei parametri spazio temporali mediante sensori inerziali. L’intento è di analizzare le varie tecniche di estrazione dei parametri spazio temporali a partire da dati misurati con sensori inerziali, utilizzate fino ad oggi ed indagate nella letteratura più recente; verrà utilizzato un approccio prettamente metodologico, tralasciando l’aspetto clinico dei risultati.

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L’analisi della postura e del movimento umano costituiscono un settore biomedico in forte espansione e di grande interesse dal punto di vista clinico. La valutazione delle caratteristiche della postura e del movimento, nonché delle loro variazioni rispetto ad una situazione di normalità, possono essere di enorme utilità in campo clinico per la diagnosi di particolari patologie, così come per la pianificazione ed il controllo di specifici trattamenti riabilitativi. In particolare è utile una valutazione quantitativa della postura e del movimento che può essere effettuata solo utilizzando metodologie e tecnologie ‘ad hoc’. Negli ultimi anni la diffusione di sensori MEMS e lo sviluppo di algoritmi di sensor fusion hanno portato questi dispositivi ad entrare nel mondo della Motion Capture. Queste piattaforme multi-sensore, comunemente chiamate IMU (Inertial Measurement Unit), possono rappresentare l’elemento base di una rete sensoriale per il monitoraggio del movimento umano.

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Lo studio dello sviluppo delle attività motorie fondamentali (FMS) nei bambini sta acquisendo in questi anni grande importanza, poiché la padronanza di queste ultime sembra essere correlata positivamente sia con la condizione di benessere fisico, sia con il mantenimento di alti livelli di autostima; si ritiene inoltre che possano contribuire al mantenimento di uno stile di vita sano in età adulta. In questo elaborato di tesi viene preso in considerazione un test di riferimento per la valutazione delle FMS, il TMGD – 2. Lo scopo è quello di fornire una valutazione quantitativa delle performance delle FMS, sulla base degli standard proposti dal protocollo TGMD-2, mediante una versione strumentata del test, utilizzando delle Inertial Measurement Unit (IMU). Questi sensori consentono di superare il limite posto dalla soggettività nella valutazione dell’operatore e permettono di esprimere un giudizio in maniera rapida e automatica. Il TGMD-2 è stato somministrato, in versione strumentata, a 91 soggetti di età compresa tra i 6 e i 10 anni. Sono stati ideati degli algoritmi che, a partire dai segnali di accelerazione e velocità angolare acquisiti mediante le IMU, consentono di conferire una valutazione a ciascuno dei task impartito dal TGMD – 2. Gli algoritmi sono stati validati mediante il confronto fra i risultati ottenuti e i giudizi di un valutatore esperto del TGMD-2, mostrando un alto grado di affinità, in genere tra l’80% e il 90%.