174 research outputs found

    Proceedings - 30. Workshop Computational Intelligence : Berlin, 26. - 27. November 2020

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    Dieser Tagungsband enthält die Beiträge des 30. Workshops Computational Intelligence. Die Schwerpunkte sind Methoden, Anwendungen und Tools für Fuzzy-Systeme, Künstliche Neuronale Netze, Evolutionäre Algorithmen und Data-Mining-Verfahren sowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen

    Machine Learning based Early Fault Diagnosis of Induction Motor for Electric Vehicle Application

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    Electrified vehicular industry is growing at a rapid pace with a global increase in production of electric vehicles (EVs) along with several new automotive cars companies coming to compete with the big car industries. The technology of EV has evolved rapidly in the last decade. But still the looming fear of low driving range, inability to charge rapidly like filling up gasoline for a conventional gas car, and lack of enough EV charging stations are just a few of the concerns. With the onset of self-driving cars, and its popularity in integrating them into electric vehicles leads to increase in safety both for the passengers inside the vehicle as well as the people outside. Since electric vehicles have not been widely used over an extended period of time to evaluate the failure rate of the powertrain of the EV, a general but definite understanding of motor failures can be developed from the usage of motors in industrial application. Since traction motors are more power dense as compared to industrial motors, the possibilities of a small failure aggravating to catastrophic issue is high. Understanding the challenges faced in EV due to stator fault in motor, with major focus on induction motor stator winding fault, this dissertation presents the following: 1. Different Motor Failures, Causes and Diagnostic Methods Used, With More Importance to Artificial Intelligence Based Motor Fault Diagnosis. 2. Understanding of Incipient Stator Winding Fault of IM and Feature Selection for Fault Diagnosis 3. Model Based Temperature Feature Prediction under Incipient Fault Condition 4. Design of Harmonics Analysis Block for Flux Feature Prediction 5. Flux Feature based On-line Harmonic Compensation for Fault-tolerant Control 6. Intelligent Flux Feature Predictive Control for Fault-Tolerant Control 7. Introduction to Machine Learning and its Application for Flux Reference Prediction 8. Dual Memorization and Generalization Machine Learning based Stator Fault Diagnosi

    The Effect Of Direct Yaw Moment On Human Controlled Vehicle Systems

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    Advances in computing technology have had a profound impact on the design and development of modern vehicle systems. These advances have provided the basis for virtual design and testing in simulated environments, as well as the development of active control systems capable of providing improved vehicle safety, efficiency, and performance. Continued developments in hybrid powertrains and on-board computing will provide for greater amounts of control, through the integration of larger numbers of actuators and more complex control schemes. The intention of this research is to investigate the effects of advanced vehicle dynamics controls on the human operated vehicle system. Hybrid electric vehicle systems incorporating multiple electric drive motors are capable of actively distributing drive and braking torque to the individual wheels of the vehicle. The modulation of these torques can be used to optimize or alter the dynamic response of the vehicle, through the application of a direct yaw moment. A control structure capable of determining and dynamically allocating appropriate control signals for over-actuated vehicle systems is proposed. A dynamic simulation of a virtual prototype BMW 330i is utilized to evaluate the effects of active drive torque vectoring on vehicle response. The effects of the proposed system on the human operator are also evaluated, through the use of driver model in-the-loop simulations. The results presented indicate the promising potential of direct yaw moment control in modulating the response of human operated vehicle systems. The interactions between the human driver model and control systems were shown to be favourable. The scientific contributions and implications of the research are detailed, including application of closed-loop simulation to engineering education. Conclusions on the efficacy of developed models, methodologies and systems are given. Finally, recommendations on potential improvements and future research regarding vehicle modelling and motion control are provided

    A Survey on Human-aware Robot Navigation

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    Intelligent systems are increasingly part of our everyday lives and have been integrated seamlessly to the point where it is difficult to imagine a world without them. Physical manifestations of those systems on the other hand, in the form of embodied agents or robots, have so far been used only for specific applications and are often limited to functional roles (e.g. in the industry, entertainment and military fields). Given the current growth and innovation in the research communities concerned with the topics of robot navigation, human-robot-interaction and human activity recognition, it seems like this might soon change. Robots are increasingly easy to obtain and use and the acceptance of them in general is growing. However, the design of a socially compliant robot that can function as a companion needs to take various areas of research into account. This paper is concerned with the navigation aspect of a socially-compliant robot and provides a survey of existing solutions for the relevant areas of research as well as an outlook on possible future directions.Comment: Robotics and Autonomous Systems, 202

    Advanced Mobile Robotics: Volume 3

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    Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective

    Proceedings - 30. Workshop Computational Intelligence : Berlin, 26. - 27. November 2020

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    The proceedings of the 30th workshop on computational intelligence focus on methods, applications, and tools for fuzzy systems, artificial neural networks, deep learning, system identification, and data mining techniques

    DEVELOPING AND IMPLEMENTING A PRACTICAL MODEL OF REAL-TIME REDESIGN AND PROBLEM SOLVING FOR FRONTLINE HEALTHCARE PROFESSIONALS

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    This research develops and implements a practical model of real-time redesign and problem solving for front line healthcare professionals using systems thinking methodologies. Healthcare quality, safety and service issues have been well-documented and lamented, calling into question the current approaches for addressing these issues. The work environment for healthcare professionals has become overburdened with time pressure, workarounds, waste, and failure to learn from the small events which occur on a frequent basis at the front-line. Desensitization may occur until sentinel events stimulate an organizational reaction. Other industries have developed system engineering methodologies, including the Toyota production system, theory of constraints, six sigma and others, to address manufacturing quality, service and safety issues. Many of these concepts were developed within the context of a linear manufacturing environment, with solutions often derived "off-line" by external experts. Healthcare reality is considered more complex and requires adaptive approaches, suggesting that modifications based on complex adaptive systems theory may be necessary. The development of the model evolved based on key systems thinking principles adapted to meet the needs of the healthcare experience and introduced to front-line healthcare workers using on-line problem solving. This research includes real-time understanding of what is working or not working in the current condition as it occurs, the ideas of the staff to improve the patient experience, including asset-based problem-solving and introduction of system thinking and design principles using ideas from various systems engineering methodologies in a healthcare worker friendly way. The research focuses on the deep systems of the organization (or clinical microsystem) and ability of front line teams to redesign processes in real-time using rapid cycle mini-experiments and the results of the redesign. Using case study and action research design, the research analyzes the experiences of an intact work group of a clinical microsystem to test the implementation of a model, labeled an Excellence Makeover. The researcher acts as a participant-observer of the emergent experience and solutions from the staff. The model will then be analyzed and additional refinements will be suggested for additional research

    Aeronautical engineering: A continuing bibliography with indexes (supplement 272)

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    This bibliography lists 719 reports, articles, and other documents introduced into the NASA scientific and technical information system in November, 1991. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

    Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)

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    http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"

    2020 - The Twenty-fourth Annual Symposium of Student Scholars

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    The full program book from the Twenty-fourth Annual Symposium of Student Scholars, held on April 16, 2020. Includes abstracts from the presentations and posters.https://digitalcommons.kennesaw.edu/sssprograms/1021/thumbnail.jp
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