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Dreuil-lès-Amiens, France

De Rybel T.,University of British Columbia | Singh A.,University of British Columbia | Pak P.,ESIEE Amiens | Marti J.R.,University of British Columbia
IEEE Transactions on Power Delivery | Year: 2010

An online signal injection approach based on a special current transformer is proposed as part of a solution for improving the test setup of transfer function diagnostics of transformers. However, the method is general and applicable to many types of substation equipment, such as circuit breakers and transmission lines. The system allows a high-power, high-frequency test signal to be injected directly on a high-voltage bus of an energized system. Due to the self-contained nature of the injector, no external power supplies or signal generators are needed and the design does not need to be ground-referenced. The system can thus be at the bus potential. In conjunction with wireless communication for control, no isolator bushings are required and the device can be constructed as a sleeve to be mounted around the busbar. This allows for economical retrofitting to existing installations. In this paper, the operational need for such an injection device is discussed, followed by the theory behind the proposed concept. Finally, a low-voltage, optically controlled, self-powered prototype is designed and demonstrated online to show the practical validity of the concept. © 2010 IEEE. Source


Li X.,ESIEE Amiens | Seignez E.,CNRS Fundamental Electronics Institute | Lambert A.,LIVIC | Loonis P.,ESIEE Amiens
Transactions of the Institute of Measurement and Control | Year: 2014

Driver drowsiness greatly increases the driver's risk of a crash or near-crash. It is recognized as one of the major causes of severe traffic accidents. In this paper, a novel non-intrusive surveillance system is proposed to estimate driver drowsiness by fusion of visual information about lane and driver with Dempster-Shafer theory. Based on expert knowledge and data statistics, various visual features extracted from lane and eye tracking are analysed for their correlation with driver drowsiness in the framework of the subjective 'observer rating of drowsiness'. The system is validated in real road scenarios and the experiment results demonstrate that it is promising in improving the robustness and temporal response of driver surveillance in real time. © The Author(s) 2013. Source


Li X.,ESIEE Amiens | Seignez E.,CNRS Fundamental Electronics Institute | Lu W.,CNRS Fundamental Electronics Institute | Loonis P.,ESIEE Amiens
IEEE Intelligent Vehicles Symposium, Proceedings | Year: 2014

Vehicle safety is the study and practice for minimizing the occurrences and consequences of traffic accidents. It is found that driver behaviors such as drowsiness, impaired driving and distraction are contributing factors to traffic accidents. In complex road surroundings, comprehensive analysis is more robust than separate evaluations which are broadly proceeded with. In this paper, we propose a vision-based nonintrusive system involving lane and driver's eye features to analyze driver behaviors. In the framework of evidence theory, evaluations of driver drowsiness and distracted and impaired driving performance are integrated to evaluate vehicle safety in real time. The system was validated in real world scenarios, and experimental results demonstrate that it is promising to improve the robustness and temporal response of vehicle safety vigilance. © 2014 IEEE. Source


Gazdac A.M.,Technical University of Cluj Napoca | Mabwe A.M.,ESIEE Amiens | Martis C.S.,Technical University of Cluj Napoca | Betin F.,UPJV | Biro K.,Technical University of Cluj Napoca
Proceedings - 2012 20th International Conference on Electrical Machines, ICEM 2012 | Year: 2012

This paper presents an analytical design algorithm and a finite element method (FEM) analysis of a novel type of machine, the dual-rotor Permanent Magnet Induction Machine. The algorithm is based on the simplified Magnetic Equivalent Circuit (MEC) of the machine. After presenting the sizing procedure, the main results obtained via FEM computation are analyzed. Two possible configurations of the PM rotor are studied and compared in terms of developed electromagnetic torque, Joule and iron losses, and electromagnetic field capabilities. © 2012 IEEE. Source


Li X.,ESIEE Amiens | Seignez E.,CNRS Fundamental Electronics Institute | Loonis P.,ESIEE Amiens
IEEE Intelligent Vehicles Symposium, Proceedings | Year: 2013

Driver drowsiness influences critically the driving safety and the lack of discerning the drowsy level precisely causes failure to take measures to prevent the accidents. In this paper, a novel intelligent surveillance system is proposed to estimate driver drowsiness based on the Observer Rating of Drowsiness (ORD) model integrated into evidence theory via fusion of lane and eye features. ORD is a subjective assessment of drowsiness that is reflected in people's physical appearance, behaviors and mannerisms. Its drowsiness model in five levels, which acts as the framework in evidence theory, is used to describe the driver's state. Based on expert knowledge and data statistics, various visual eye features are studied to enhance the robustness of this system. The system is validated in real world scenarios, and experiment results demonstrate that it is promising to improve the robustness and temporal response of driver surveillance in real-time. © 2013 IEEE. Source

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