As the technology advances and vehicles become more computerized, the complexity of automotive electronics grows exponentially, thus creating a new level of challenge for detecting faults in systems with such overwhelming number of active components. The proposal of this research was to analyze the data from the Controller Area Network from two vehicles, evaluate different techniques for data mining and feature extraction and devise possible methods for fault detection that could be employed in any system with this level of complexity. The data used in this research was collected from an ordinary vehicle and an experimental vehicle test bed, the LabCar. The techniques evaluated in this research were based on proven mathematical methods that had original application in areas of statistics and digital signal processing. A detailed analysis of each of the techniques studied and their suitability for analysing complex non-linear systems were documented with basis on the data collected. The final stages of this research consisted of using these techniques to devise a model of the Controller Area Network bus and use it for finding faults in the network.
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Graduated with First Class Hons in Robotics and Automated Systems at The University of Plymouth, followed a distinct degree in MSc Electronics systems at the University of Warwick. Worked in many areas from automated testing systems to intelligent design for bipedal robot gait control.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As the technology advances and vehicles become more computerized, the complexity of automotive electronics grows exponentially, thus creating a new level of challenge for detecting faults in systems with such overwhelming number of active components. The proposal of this research was to analyze the data from the Controller Area Network from two vehicles, evaluate different techniques for data mining and feature extraction and devise possible methods for fault detection that could be employed in any system with this level of complexity. The data used in this research was collected from an ordinary vehicle and an experimental vehicle test bed, the LabCar. The techniques evaluated in this research were based on proven mathematical methods that had original application in areas of statistics and digital signal processing. A detailed analysis of each of the techniques studied and their suitability for analysing complex non-linear systems were documented with basis on the data collected. The final stages of this research consisted of using these techniques to devise a model of the Controller Area Network bus and use it for finding faults in the network. 112 pp. Englisch. Bestandsnummer des Verkäufers 9783844382655
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Vicente AlexandreGraduated with First Class Hons in Robotics and Automated Systems at The University of Plymouth, followed a distinct degree in MSc Electronics systems at the University of Warwick. Worked in many areas from automated. Bestandsnummer des Verkäufers 5475792
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -As the technology advances and vehicles become more computerized, the complexity of automotive electronics grows exponentially, thus creating a new level of challenge for detecting faults in systems with such overwhelming number of active components. The proposal of this research was to analyze the data from the Controller Area Network from two vehicles, evaluate different techniques for data mining and feature extraction and devise possible methods for fault detection that could be employed in any system with this level of complexity. The data used in this research was collected from an ordinary vehicle and an experimental vehicle test bed, the LabCar. The techniques evaluated in this research were based on proven mathematical methods that had original application in areas of statistics and digital signal processing. A detailed analysis of each of the techniques studied and their suitability for analysing complex non-linear systems were documented with basis on the data collected. The final stages of this research consisted of using these techniques to devise a model of the Controller Area Network bus and use it for finding faults in the network.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 112 pp. Englisch. Bestandsnummer des Verkäufers 9783844382655
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As the technology advances and vehicles become more computerized, the complexity of automotive electronics grows exponentially, thus creating a new level of challenge for detecting faults in systems with such overwhelming number of active components. The proposal of this research was to analyze the data from the Controller Area Network from two vehicles, evaluate different techniques for data mining and feature extraction and devise possible methods for fault detection that could be employed in any system with this level of complexity. The data used in this research was collected from an ordinary vehicle and an experimental vehicle test bed, the LabCar. The techniques evaluated in this research were based on proven mathematical methods that had original application in areas of statistics and digital signal processing. A detailed analysis of each of the techniques studied and their suitability for analysing complex non-linear systems were documented with basis on the data collected. The final stages of this research consisted of using these techniques to devise a model of the Controller Area Network bus and use it for finding faults in the network. Bestandsnummer des Verkäufers 9783844382655
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Taschenbuch. Zustand: Neu. Fault Detection in Automotive Network Embedded Electronics Systems | Signal processing analysis for fault detection of the Controller Area Network in automotive applications | Alexandre Vicente | Taschenbuch | 112 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844382655 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 106827670
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