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A SAW wireless sensor network platform for industrial predictive maintenance

Ossété Gombé, Bérenger and Goavec Mérou, Gwenhael and Breschi, Karla and Guyennet, Hervé and Friedt, Jean-Michel and Felea, Violeta and Medjaher, Kamal A SAW wireless sensor network platform for industrial predictive maintenance. (2017) Journal of Intelligent Manufacturing. 1-12. ISSN 0956-5515

(Document in English)

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Official URL: http://dx.doi.org/10.1007/s10845-017-1344-0


Predictive Maintenance (PM) predicts the system health, based on the current condition, and defines the needed maintenance activities accordingly. This way, the system is only taken out of service if direct evidence exists that deterioration has actually taken place. This increases maintenance efficiency and productivity on one hand, and decreases maintenance support costs and logistics footprints on the other. We propose a system based on wireless sensor network to monitor industrial systems in order to prevent faults and damages. The sensors use the Surface Acoustic Wave (SAW) technology with an architecture composed of an electronic interrogation device and a passive sensor (without energy at the transducer) which is powered by the radio frequency transmitted by the interrogation unit. The radio frequency link transfers energy to the sensor to perform its measurement and to transmit the result to the interrogation unit - or in a description closer to the implemented, characterize the cooperative target cross-section characteristics to recover the physical quantity defining the transducer material properties. We use this sensing architecture to measure the temperature of industrial machine components and we evaluate the robustness of the method. This technology can be applied to other physical parameters to be monitored. Captured information is transmitted to the base station through multi-hop communications. We also treat interferences involved in both interrogator to interrogator and sensor to interrogator communications.

Item Type:Article
Additional Information:Thanks to Springer Verlag editor. The definitive version is available at : http://www.springer.com/business+%26+management/operations+research/journal/10845 Source : http://www.sherpa.ac.uk/romeo/search.php
HAL Id:hal-03513026
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Ecole Nationale Supérieure de Mécanique et des Microtechniques - ENSMM (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Other partners > Université de Franche-Comté (FRANCE)
Other partners > Université de Technologie de Belfort-Montbéliard - UTBM (FRANCE)
Other partners > SENSeOR SAS (FRANCE)
Laboratory name:
Deposited On:01 Dec 2017 08:47

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