Nadine MARTIN
Directeur de Recherche CNRS
Equipe Signal et Automatique pour la surveIllance,le diaGnostic et la biomecAnique
Département Images et Signal
ME CONTACTER / CONTACT ME
Mail : nadine.martin@gipsa-lab.grenoble-inp.fr

11 rue des mathématiques
Domaine Universitaire
BP 46
38402 Saint Martin d'Hères cedex

Bureau D1196
Tél.33 (0)4 76 82 62 69
Fax : 33 (0)4 76 57 47 90
PUBLICATIONS RECENTES / RECENT PUBLICATIONS
Les derniéres publications de la collection Gipsa dans HAL

AStrion assets for the detection of a main bearing failure in an onshore wind turbine

Xavier Laval, Guanghan Song, Zhong-Yang Li, Pascal Bellemain, Maxime Lefray, et al.. AStrion assets for the detection of a main bearing failure in an onshore wind turbine. 13th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies (CM2016/MFPT2016), Oct 2016, Paris, France. 〈hal-01399027〉

Vibration condition monitoring in a paper industrial plant: Supreme project

Mario Eltabach, Sophie Sieg-Zieba, Guanghan Song, Zhongyang Li, Pascal Bellemain, et al.. Vibration condition monitoring in a paper industrial plant: Supreme project. 13th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies (CM2016/MFPT2016), Oct 2016, Paris, France. 〈hal-01399036〉

Invited overview Keynote address, Signal processing for condition monitoring: exciting challenges ahead

Nadine Martin. Invited overview Keynote address, Signal processing for condition monitoring: exciting challenges ahead. First World Congress on Condition Monitoring, Jun 2016, London, United Kingdom. 〈hal-01644301〉

AStrion strategy: from acquisition to diagnosis - Application to wind turbine monitoring

Zhong-Yang Li, Timothée Gerber, Marcin Firla, Pascal Bellemain, Nadine Martin, et al.. AStrion strategy: from acquisition to diagnosis - Application to wind turbine monitoring. The International Journal of Condition Monitoring, the British Institute of Non-Destructive Testing, 2016, 6 (2), pp.47-54. 〈hal-01399043〉

An automatic approach towards modal parameter estimation for high-rise buildings of multicomponent signals under ambient excitations via filter-free Random Decrement Technique

Fatima Nasser, Zhongyang Li, Nadine Martin, Philippe Gueguen. An automatic approach towards modal parameter estimation for high-rise buildings of multicomponent signals under ambient excitations via filter-free Random Decrement Technique. Mechanical Systems and Signal Processing, Elsevier, 2016, 70-71, 〈10.1016/j.ymssp.2015.08.008〉. 〈hal-01233152〉

Frequency and damping ratio assessment of high-rise buildings using an Automatic Model-Based Approach applied to real-world ambient vibration recordings

Fatima Nasser, Zhongyang Li, Philippe Gueguen, Nadine Martin. Frequency and damping ratio assessment of high-rise buildings using an Automatic Model-Based Approach applied to real-world ambient vibration recordings. Mechanical Systems and Signal Processing, Elsevier, 2016, 75, pp.196-208. 〈10.1016/j.ymssp.2015.12.022〉. 〈hal-01319880〉

Automatic Characteristic Frequency Association and All-Sideband Demodulation for Detection of a Bearing Fault of a Test Rig

Marcin Firla, Zhong-Yang Li, Nadine Martin, Christian Pachaud, Tomasz Barszcz. Automatic Characteristic Frequency Association and All-Sideband Demodulation for Detection of a Bearing Fault of a Test Rig. Mechanical Systems and Signal Processing, Elsevier, 2016, 〈10.1016/j.ymssp.2016.04.036〉. 〈hal-01314866〉

AStrion strategy: from acquisition to diagnosis. Application to wind turbine monitoring

Zhong-Yang Li, Timothée Gerber, Marcin Firla, Pascal Bellemain, Nadine Martin, et al.. AStrion strategy: from acquisition to diagnosis. Application to wind turbine monitoring. Insight - Non-Destructive Testing & Condition Monitoring, British Institute of Non-destructive Testing, 2015, 57 (8), pp.6. 〈10.1784/insi.2015.57.4.XXX〉. 〈hal-01182982〉

AStrion data validation of non-stationary wind turbine signals

Guanghan Song, Zhong-Yang Li, Pascal Bellemain, Nadine Martin, Corinne Mailhes. AStrion data validation of non-stationary wind turbine signals. Insight - Non-Destructive Testing & Condition Monitoring, British Institute of Non-destructive Testing, 2015, pp.7. 〈10.1784/insi.2015.57.4.XXX〉. 〈hal-01182956〉

Automatic and Full-Band Demodulation for Fault Detection—Validation on a Wind Turbine Test Rig

Marcin Firla, Zhong-Yang Li, Nadine Martin, Tomasz Barszcz. Automatic and Full-Band Demodulation for Fault Detection—Validation on a Wind Turbine Test Rig. Advances in Condition Monitoring of Machinery in Non-Stationary Operations, 2015, Proceedings of the Fourth International Conference on Condition Monitoring of Machinery in Non-Stationary Operations, CMMNO'2014, Lyon, France December 15-17, 〈10.1007/978-3-319-20463-5_10〉. 〈hal-01212474〉

ENCADREMENT DE THESES / PhD THESIS SUPERVISED

Grenoble Images Parole Signal Automatique laboratoire

UMR 5216 CNRS - Grenoble INP - Université Joseph Fourier - Université Stendhal