|
Dietrich, André; Zug, Sebastian; Kaiser, Jörg
Detecting External Measurement Disturbances Based on Statistical Analysis for Smart Sensors (Inproceeding)
Procedings of the IEEE International Symposium on Industrial Electronics (ISIE), pp. 2067-2072, Bari, Italy, 2010.
(Abstract | Links | BibTeX | Tags: Fault-Tolerance, Sensors, Smart Sensors)
@inproceedings{dietrich2010statistics,
title = {Detecting External Measurement Disturbances Based on Statistical Analysis for Smart Sensors},
author = {André Dietrich and Sebastian Zug and Jörg Kaiser},
url = {http://eos.cs.ovgu.de/wp-content/uploads/2014/09/Detecting-External-Measurement-Disturbances-Based-on-Statistical-Analysis-for-Smart-Sensors.pdf},
year = {2010},
date = {2010-07-01},
booktitle = {Procedings of the IEEE International Symposium on Industrial Electronics (ISIE)},
pages = {2067-2072},
address = {Bari, Italy},
abstract = {The transducer process of a sensor is interference prone to environmental conditions or external disturbances depending on sensor type, measurement procedure etc. Dependable sensors are characterized by a broad independence of those factors or/and they can both detect situations that make a correct measurement impossible and validate the measurement result. In this paper we describe a statistical approach for the detection of faulty measurements caused by external disturbances. Our fault detection algorithm is based on a comparison of faultless reference measurements with current sensing values. Using this enhancement, a sensor becomes a real smart sensing device and supplies an additional validity estimation of each measurement. The approach was implemented and validated in a demonstration setup that integrates an infrared sensor array disturbed by a strong extraneous light.},
keywords = {Fault-Tolerance, Sensors, Smart Sensors}
}
The transducer process of a sensor is interference prone to environmental conditions or external disturbances depending on sensor type, measurement procedure etc. Dependable sensors are characterized by a broad independence of those factors or/and they can both detect situations that make a correct measurement impossible and validate the measurement result. In this paper we describe a statistical approach for the detection of faulty measurements caused by external disturbances. Our fault detection algorithm is based on a comparison of faultless reference measurements with current sensing values. Using this enhancement, a sensor becomes a real smart sensing device and supplies an additional validity estimation of each measurement. The approach was implemented and validated in a demonstration setup that integrates an infrared sensor array disturbed by a strong extraneous light.
|
|
Zug, Sebastian; Kaiser, Jörg
An approach towards smart fault-tolerant sensors (Inproceeding)
Proceedings of IEEE International Workshop on Robotic and Sensors Environments (ROSE2009), Lecco, Italy, 2009.
(BibTeX | Tags: Fault-Tolerance, Sensors)
@inproceedings{ EOS-2009.000-ZK,
title = {An approach towards smart fault-tolerant sensors},
author = {Sebastian Zug and Jörg Kaiser},
year = {2009},
date = {2009-11-01},
booktitle = {Proceedings of IEEE International Workshop on Robotic and Sensors Environments (ROSE2009)},
address = {Lecco, Italy},
keywords = {Fault-Tolerance, Sensors}
}
|
|
Schulze, Michael; Zug, Sebastian
Using COSMIC – A real world case study combining virtual and real sensors (Inproceeding)
5th MiNEMA Workshop, pp. 74-77, Magdeburg, Germany, 2007.
(BibTeX | Tags: Middleware, Sensors)
@inproceedings{ EOS-2007.000-SZ,
title = {Using COSMIC – A real world case study combining virtual and real sensors},
author = {Michael Schulze and Sebastian Zug},
year = {2007},
date = {2007-09-11},
booktitle = {5th MiNEMA Workshop},
pages = {74-77},
address = {Magdeburg, Germany},
keywords = {Middleware, Sensors}
}
|